This paper was commissioned as part of a series of reviews for the Working and Employment Challenge of the Beyond Current Horizons project on the future of education.  The reviews all focus on particular issues relating to work and employment.  This paper provides a series of ‘quick reviews’

The six topics are:

1. The importance of Science, Technology, Engineering and Mathematics (STEM)
2. Children’s work
3. Entrepreneurial activity and practices
4. Innovation and intellectual property rights
5. Emerging economies in virtual worlds
6. Possible negative effects of technological developments

For each topic any relevant and necessary definitions of key terms are set out alongside an overview of the importance and relevance of each topic to the UK economy and society. This is then followed by some contextual information regarding each topic. Appropriate recent statistics are given where possible. The main issues and areas of concern for each topic are discussed. Finally, for each topic, possible future directions and outcomes are presented.

Keywords: science, technology, engineering, maths, children, innovation, economics
1.       The importance of Science, Technology, Engineering and Mathematics (STEM)

1.1      Skills and qualifications STEM

It is well acknowledged that Science, Technology, Engineering and Mathematics (STEM) skills and work are important in all societies and economies. According to the Council for Industry and Higher Education (CIHE), the UK’s capabilities in STEM underpin the economy. The importance of STEM skills is likely to grow in the future in response to technological enhancements, the need for action related to environmental concerns, and as the UK’s knowledge economy expands. There are a number of concerns related to the future supply of people with STEM skills as well as the quality of these skills. Such concerns need to be addressed so that there will be sufficient, high quality STEM skills available in the labour market in the future to meet society’s needs and to maintain the UK’s position as a leading economy.

As the UK continues to develop as a knowledge economy, STEM education and employment opportunities are important issues to consider. The CIHE report, International Competitiveness and the Role of Universities, highlighted the relatively high proportion of employees in knowledge intensive service businesses that have science and engineering degrees (24%) STEM skills enhance people’s ability to generate new knowledge and to identify, adapt and use knowledge that is generated elsewhere and apply it for the benefit of businesses. It is not only the sectors that have been traditionally associated with “science” skills that rely upon the benefits of employing people with STEM skills. The Roberts Review (HM Treasury, 2002) highlighted the importance of having people qualified in STEM subjects for the UK economy as a key element for the R&D, innovation, education triangle.

STEM skills are particularly important in high added value sectors. The UK software development industry, for example, employs 1 million people and produces an annual GVA of £30bn (BCS, 2006). Software development is one sector where the importance of STEM skills is obvious. However, STEM skills are relevant in most, if not all, industries. As discussed below, STEM graduates work in various sectors.

1.2      Supply and quality of STEM skills

According to the Roberts Review (HM Treasury, 2002) and similar reviews, the most important issue related to STEM in the UK is the supply of STEM skills and the quality of these skills. A strong supply of individuals with qualifications in STEM subjects is necessary to realise Government’s ambitions for the UK. In guaranteeing this supply, all parts of the education system have a role to play – from the Key Stages of compulsory education, through to post-16/further and higher education. Various assessments suggest that the future supply of STEM graduates/postgraduates may fall short of demand, not only in the UK but also in the US and other world-leading economies. Various explanations for the problems related to the supply of graduates and postgraduates include:

• The number of students studying STEM subjects at lower levels of education greatly influences participation later on. Only 7% of pupils study triple science at GCSE[1], which restricts the likely number of students who will be interested in (or capable of) pursuing further studies in such areas
• STEM subject degree programmes are seen as harder to get into than many of the alternatives. Many require maths A-level, which is under pressure in uptake at secondary level with too few students in the opinion of many
• STEM department closures resulting from declining student interest makes studying such subjects even more unattractive
• Universities promoting STEM subjects less vigorously than others (in part due to higher costs such as expensive labs)
• High rates of growth in the number studying medicine – attracting higher quality applicants who would otherwise go for other STEM subjects.

1.2.1   STEM at compulsory education level

One of the sources of the decline in the number of STEM students is simply lack of interest of young people, at school level, in studying such subjects and working in related careers. Given school students’ lack of interest and therefore decreasing numbers of students undertaking study in STEM subjects at A-level, the number of suitably qualified STEM teachers is also a concern. With fewer teachers specialising in and teaching STEM subjects, there is further risk of less interest by students at school level. Furthermore, there is evidence that suggests that teachers are not interested in teaching these subjects and there is concern that teachers are not suitably qualified in STEM subjects to effectively teach the subject and to create interest in the subject areas amongst students.

According to CIHE, finding qualified teachers to teach STEM subjects is vital. The quantity and quality of STEM teachers will have impacts not only on the supply of future STEM graduates but also on the quality of these students’ skills. The Science and Innovation Framework 2004-2014 (HMT/DTI/DfES, 2004) suggests that a range of measures is necessary in order to enhance the teaching and learning of STEM subjects and to enhance the recruitment and retention of science teachers and researchers, in order to encourage more students to follow such course of study, and to thereby support the future needs of the science base and the economy for people qualified in such areas.

The Government is attempting to increase the number and quality of teachers in order to increase the number of young people choosing STEM subjects and subsequently follow a STEM-related career path.  All this is seen as helping the UK compete in the global economy. With the aim of achieving this, a £140 million strategy to educate the next generation of scientists and mathematicians and help recruit and train more science and maths teachers was announced in January 2008.[2]

1.2.2   STEM in Post-16, Higher and Further Education

The future supply of people with STEM qualifications will be determined mainly by the number of students who study such subjects after compulsory education. Of particular importance are the numbers educated to degree level and above. A great concern in the UK today is the relatively low uptake of STEM subjects at university.

There was an increase of 10% in the total number of university applications between 2002/3 and 2006/7. Over the same period, STEM applications increased by 12%.  However, the balance of students studying particular STEM subjects is also a concern. There are concerns about the mix of STEM graduates being produced, with worries that there is insufficient emphasis on core science and engineering subjects.  There was a fall of 15% in the numbers of engineering and technology graduates (23,300 to 19,700) over the decade to 2008.[3]

The number of undergraduate students who were studying physical science (Physics and Chemistry) as a proportion of all undergraduates fell from 5.5% in 1996 to 4.1% in 2000. The share studying engineering and technology fell from 9.3% to 6.3% from 1996 to 2000. However there has been encouraging increases in the numbers of applicants to STEM programmes more recently. The share of all university applications that were for maths places rose by 10% between 2006 and 2007. This share increased by 8% for mechanical engineering, 11% for chemistry and 12% for physics. There is concern though that these increases will not be sustained and that they may represent only temporary increases that will do little to guarantee a future supply of qualified STEM people.

According to NESTA, the total number of STEM graduates has increased by 10% since 1995. However, these graduates have been unevenly distributed across the STEM subjects. The number of graduates fell in engineering and technology and in the physical sciences while numbers increased in biological sciences, computer science and mathematical science.

The number of STEM graduates (excluding psychology and sports science graduates) at UK higher education institutions increased by 5% from 2002/3 to 2006/7.  The number of postdoctoral graduates increased by 18% over the same period. While the UK has a relatively large number of students studying STEM subjects, it has been argued that this is due to increases in those studying IT and biological sciences rather than mathematics, engineering, and the physical sciences. This is a source of concern. The DTI (2006) have highlighted the rapid growth in supply numbers, which have increased at a rate slightly higher than the average for all subjects. However, the DTI report notes that recent increases have been concentrated in computer sciences and subjects related to medicine and biological science, rather than in engineering and technology, physical sciences and architecture.

Beyond compulsory education and A-levels, a diminished interest in studying STEM subjects is shown by students. The Sainsbury Report (HM Treasury, 2001) referred to low numbers of students taking science subjects following compulsory education. There have been marked decreases in the numbers of applications to STEM-related post-secondary programmes. According to the British Computing Society (BCS, 2006), there was a 50% drop in the number of applications for computer science related courses between 2001 and 2006. Problems experienced by university STEM departments, in terms of student numbers, are worst in physical and chemical sciences, engineering and maths. Biological science departments have tended to experience less difficulty on the whole but within biological sciences numbers are uneven.

CIHE has argued that in all employment sectors where STEM graduates are at a premium, there are shortages of quality graduates and postgraduates with relevant IT and general STEM skills and experiences. Since 2002, the numbers of STEM graduates, excluding Engineering graduates, has increased significantly; however, the number of these students taking STEM A-levels has declined with noticeable drops in the numbers studying mathematics, computer sciences and physics. This will have implications for the numbers of graduates to come in these subject areas.

Another significant issue related to STEM at higher levels is the gender balance of those who study such subjects. This issue has been acknowledged as a problem at all levels for a significant period. Female participation levels are much lower in some fields than in others. In 2005[4], 15% of engineering and technology students were female. In the same year, females accounted for 24% of students in computer science, 38% studying maths, 41% in physical science and 64% studying biological sciences. There have been a range of initiatives launched to tackle this imbalance, with a great deal of work being put in by such groups as the UK Resource Centre for Women in Science, Engineering and Technology and Women into Science, Engineering and Construction (WISE). A number of websites have also been created to stimulate girls’ interest in STEM subjects and to provide valuable information.[5] However, CIHE points out that these figures have remained relatively stable over a number of years, perhaps indicating that the initiatives and policies aimed at improving female participation in STEM subjects should be reconsidered.

A shortage of graduates with numerical abilities is considered to be critical by CIHE business leaders (CIHE, 2009). This shortage will only worsen in the light of the current age profile of their workforce. UK businesses and the UK in general are vulnerable to competition from other countries due to such shortages. There is also a fear that businesses and universities rely too heavily on overseas expertise rather than growing UK-based expertise. There are skill shortages across a range of STEM disciplines and in particular specialisms (such as electrical and power systems engineering, pharmacologists with particular experience). CIHE also highlights the need to address the gender balance of people in STEM.

However, it is not all bad news. The annual report, Education at a Glance 2008 (OECD, 2008) indicates that the UK is doing better than average in supplying STEM graduates to the workforce. Amongst the OECD countries, the UK ranks 7^th in terms of its supply of STEM graduates – ahead of Germany (11^th), Italy (12^th), USA (15^th) and Spain (17^th) and better than the EU and OECD averages. DfES (2006) also concludes that the UK’s stock of science and engineering graduates fares well internationally, and that the quality of STEM graduates, as indicated by prior qualifications of entrants, is rising. It is important to note that without ensuring that a sufficient supply of STEM graduates is in the pipeline, the UK’s relative performance on this will not improve, and may indeed slip as other countries improve.

In 2007, just under 1 million people in the working age population in the UK had STEM qualifications at NQF level 5 and just over 2½ million had STEM qualifications at NQF level 4. Of such graduates and postgraduates, the vast majority were economically active and in employment, with only very small numbers unemployed. This reflects the patterns for those qualified in other subjects as well. A much greater percentage of people with qualifications lower than NQF level 4 are found to be economically inactive and/or unemployed. Qualifications in STEM subjects are associated with marginally greater likelihood of being economically active and in employment than is found for graduates in other disciplines, but the differences are small.

In A Degree of Concern (2006) and A Higher Degree of Concern (2008), the Royal Society provides a statistical review of trends relating to the supply of graduates with STEM qualifications. They highlight the importance of the Higher Education system in relation to the UK’s economic performance, particularly in the context of an increasingly competitive and inter-connected global economy. The UK’s HE system needs to equip students with the knowledge, skills and aptitudes to compete with the best in the world, while at the same time supporting much of the nation’s R&D activity.  The Royal Society reports recognise that the demand for and supply of STEM graduates are closely linked and that there is a need to encourage virtuous circles, where supply encourages demand and demand stimulates supply. Links between industry and universities are also a key area where more emphasis is needed to enhance collaboration and strengthen ties.

1.3      STEM Employment and Recruitment

With the exception of medicine, STEM graduates go on to work in a wide variety of industries. STEM graduates and postgraduates hold just over 3 in 10 jobs across all sectors, but this ranges from over 5 in 10 in non-marketed services (including education, health and public administration and defence), to not much more than 1 in 10 for the Construction sector.

The shares of firms that employ STEM graduates are significant across most sectors. Overall, 92% of all UK firms employ people with qualifications in STEM subjects. This varies amongst sectors with the share of firms employing STEM people varying from 89% of energy and water companies, 59% of construction firms, and 48% of manufacturers. Employers in the finance and insurance and professional services sectors also have relatively high demand for STEM skills. Highly numerate, analytical and problem-solving skills are particularly valuable in such sectors. About 61% of professional service companies and 94% of banking firms employ STEM-skilled people. Large numbers of STEM graduates have been drawn to the financial services sector owing to relatively high salaries paid out by companies in this sector for the top talent.

STEM skills play an important role in business and they are vital for research and development and innovation activity. Some 40% of employers across all sectors indicated that they require STEM skilled people to design and innovate new products and services. Value is also place on STEM skills in sales and marketing, as well as general management roles. STEM graduates are far from limited in their career options and studying such subjects does not close doors on their future prospects.

The CBI/Edexcel Education and Skills Survey 2008 indicated gaps in the workplace, with 59% of employers reporting difficulty recruiting STEM-skilled individuals. Some sectors reported suffering acute shortages. Experienced hires, graduates and technicians are shown to be in particularly short supply. In response to these recruitment difficulties, large firms in particular have been looking outside the UK for candidates with STEM skills. Of the large employers in the survey, 36% have looked to India and 24% to China in order to fulfil their STEM-skilled labour needs.

With firms recruiting STEM graduates from Asia there is a concern about the quality of these graduates’ qualifications. According to CBI/Edexcel there is concern over the “loose definition of ‘graduate’ in China” and differences in language, communication skills and problem solving styles may be key barriers to getting the most out of recruiting from abroad. However, as universities in China and India develop their courses and improve the quality of their graduates, the UK recruitment of STEM-skilled candidates from these countries is likely to increase.

The quality of STEM graduates is not only a concern about those coming from abroad but is also a significant issue related to UK graduates. It is not only shortages in supply that cause recruitment difficulties for employers. There is a perception held by many employers (42% in the CBI/Edexcel survey) that those graduates that do apply for jobs do not have the right skills. This is not thought to be as great an issue for employers in the financial services sector as it is for other sectors, as finance employers tend to offer high salaries to attract the top talent.  The HE system needs to ensure not only that there are sufficient numbers of STEM graduates to meet demand but also that the quality of these graduates is world-class. As the Royal Society (2006, 2008) has pointed out, the UK’s HE system needs to equip students with the knowledge, skills and aptitudes to compete with the best in the world, while at the same time supporting much of the nation’s R&D activity.

1.4      STEM-related policies, programmes and initiatives

A number of Government policies and initiatives have been introduced over the past decade to address the possibility of a future shortage of STEM skills in the UK labour force. The Annual Innovation Report 2008 (DIUS) has set out HEFCE’s commitment of £160 million to increase the demand for and supply of students studying strategic and vulnerable subjects. The majority of these funds is to be spent on STEM subjects. Very recently, the University of Birmingham has recently received £20 million to help fill the national skills shortage gap in science, technology and maths by hosting the National Higher Education STEM programme[6]. The programme is funded by HEFCE, with the aim of increasing the number of graduates with skills in STEM disciplines, in order to meet the needs of employers and to boost the UK economy.  It will aim to raise the aspirations of young people to entice them to study science at university level. The programme will develop innovative and transferable programmes and initiatives for expanding participation in STEM subjects in HE. The delivery phase of the programme is the three years from 2009 to 2012.

As discussed in Section 1.2 various groups and programmes have also been implemented to attempt to stimulate female interest in STEM and to address the gender imbalance that has been observed in these subjects for many years.

1.5      Future issues

The value of STEM skills in the UK economy is undeniable. Innovation is considered to be one of the key drivers of productivity and economic performance and STEM skills are thought by many to be key in enabling innovation activity. The innovation gap between the EU and the US is in part (23%) attributed to the lower share of people with tertiary education in Europe’s workforce.[7] The UK has set a target for R&D investment to reach 2.5% of GDP by 2014[8]. Meeting this target would require around 50,000 additional research staff. There is a danger that unless the number of graduates qualified in STEM subjects increases, this innovation gap will widen.

It is considered essential that the UK gets the supply of STEM skills right, otherwise the damage to the economy could be substantial.[9] According to NIESR, the UK lagging in terms of skills levels of engineers and scientists impacts negatively on the innovative activity associated with such skills. This translates further into a loss of competitiveness in terms of a loss of domestic market share, a loss of international trade share and lower levels of productivity (Mason and Wagner, 2002).

A number of developing and emerging economies, such as India and China, are adding to the level of international competition faced by the UK. In order to keep pace with the activities in such countries, the UK must increase its skill base. Globalisation, demographic change and the rapid pace of advancement in technologies exert pressure on the UK that requires immediate action in terms of ensuring the country has the capacity, including the skills base, to compete, and to avoid being left behind.

Demand for STEM skills is expected to rise. Based on Working Futures 2004-2014 (Wilson et al, 2006), CBI (2008) suggest that by 2014, 730,000 extra jobs will require candidates with STEM skills. Growth in employment is projected to be fastest for those with the highest level qualifications. The number of those in employment with no or few formal qualifications is projected to decline. The Working Futures 2004-2014 results generally suggest, with the exception of Medicine, that the “demand” for those qualified in most STEM subjects will grow significantly faster than the average for all subject groups.[10]

The age profile of the STEM workforce implies that there will be a significant need to replace those leaving the STEM workforce (as older workers reach retirement age in the coming decade). This replacement demand is at least equally important as so called expansion demands arising from projected increases in employment levels for such workers.

CIHE (2009) business leaders have identified a number of concerns relating to STEM. The leaders and managers of the future must be numerate. The UK is considered vulnerable as a nation due to over-reliance of businesses and university departments on STEM expertise from overseas. There are skill shortages across the range of STEM disciplines, as well as in particular specialisms (from electrical and power systems engineers to pharmacologists with in vivo animal experience). There is a particular need to persuade more girls to study STEM subjects. Businesses have been recruiting maths graduates from India and other Asian nations.

According to NESTA (2007), the UK’s R&D expenditure lags behind international competitors, STEM graduates are increasing but demand is likely to outstrip supply and links between businesses and universities are still challenged by university funding streams and cultural differences. Science policy needs to become more prominent, but more importantly it needs to become more sophisticated (NESTA, 2007).

Possible futures

Worst case scenario

• The supply and quality of STEM graduates and postgraduates in the UK declines further
• Initiatives to improve situation do not work
• UK slips as one of world leaders in STEM graduate supply
• The innovation gap with other countries widen
• STEM related employment goes offshore, especially as STEM graduates in other countries (India, China, EU) improve, and as there is a huge supply
• Jobs that cannot be offshored that require STEM skills are awarded to foreign graduates/STEM-skilled employees
• The UK’s R&D base declines
• The UK’s universities slip down international rankings because of the relatively poor quality of scientific research and output in terms of STEM studies.

Best case scenario

• More students gain interest in STEM subjects
• Supply issues are appropriately addressed
• Expansion of employment for those with STEM skills due to continuing trends towards innovation and green jobs
• The UK becomes a world leader in STEM skills – world leader in R&D – world leader in innovation
• More use of UK universities for international projects relevant to STEM.

Most probable scenario

• number of jobs requiring STEM skills to expand due to continuation of recent trend
• financial services continue to attract STEM graduates but no longer promising sky-high salaries after the recent financial crisis
• some STEM supply issues are addressed
• industry facelift to attract more students to STEM subjects
• use of international STEM qualifications.

2.      Children’s work

The majority of research on children’s work and child labour focuses on the negative side of this issue. There is much commentary concerned with the inappropriateness of child labour and how child labour often arises in response to impoverished living conditions.

In the UK context however, ‘children’s work’ does not typically refer to the sinister exploitation of children but instead refers to children’s willing participation in part-time or vacation time employment. That is not to say that exploitive child labour does not take place in this country nor that children who willingly work are not exploited in some cases, but it is not the large problem here that it is in developing countries, or in the UK in the late 19^th and early 20^th centuries.

Child labour and youth employment are two very different things. While child labour has very definite negative connotations, youth employment is typically viewed as a positive experience for children while growing up. In UNICEF publications, ‘child labour’ conventionally refers to children working before they reach the minimum ages for employment in their country (16 in the UK). It has been redefined to refer to all young people engaged in harmful employment, whether they are school-age or older.

Youth employment, in contrast, is considered a more positive activity in which young people are consensually employed in jobs that adhere to particular laws and regulations and pose no danger or risk to the health and safety of the young person. However, even when employed in more acceptable forms of work, the employment situations of many young people and children do not always abide by all regulations.

2.1      ‘Acceptable’ children’s work

In the UK, many young people (under the age of 18 or 16) are engaged in various types of employment outside of their normal schooling. Survey research has consistently shown that between one-third and one-half of school age children are in paid employment at any given time. Before they leave school, between two-thirds and three-quarters of children will have held a paid job (Mizen et al, 1999). Pinpointing the actual numbers of children in paid employment in the UK however, is not straightforward due to large discrepancies in the definitions of what constitutes legal child labour and because of the degree of unseen child work. Hobbs and McKechnie (1997) reviewed various estimates of the numbers of children undertaking paid work in Britain. Their findings are summarised in Table 1

Table 1: Best estimates of children working in the UK

Source: Hobbs, S. and J. McKechnie (1997) Child Employment in Britain: A Social and Psychological Analysis. Table 2.4, p33.

There is evidence that employment of children (or youth), especially school students, is on the rise in the UK and the USA. Between 1968 and 1991 there was a marked increase in the rates of part-time working amongst 16 to 18 year olds in full time education in the US (Dustman et al 1996) according to data from the Family Expenditure Survey. In the Republic of Ireland in 1994, one-quarter of lower secondary students and 31% of upper secondary students were engaged in regular part-time work. The types of jobs performed vary from part-time work in shops and restaurants, to paper rounds, to babysitting. Jobs undertaken by children often comprise unskilled, manual work with unusual working arrangements which may leave children vulnerable to exploitation.

Regulations and legislation regarding children’s work in the UK

UK law specifies the types of work and conditions under which children or youths may be legally employed. Employers wishing to employ children under school leaving age must get a permit from the local authority. This permit must be signed by the employer and one parent of the child. Some of the key features of children and employment regulations in England and Wales are:

• Types of work – no one under the minimum school leaving age (16 years) is permitted to do anything more than light work. They are not allowed to do work that is likely to cause harm to the child or to do work that will affect attendance at school or participation in work experience. Children are prohibited from working in factories, construction, transport, mines and on registered merchant ships. Local authorities may impose further restrictions on the types of work children are permitted to perform.
• Younger children – children under the age of 13 can only work under special circumstances. Once aged 13 years, children can undertake light work. At age 16 years, a person will be classed as a young worker with different rules.
• Hours – For those children who are legally permitted to work, they are not allowed to work:
  • during school hours on any school day
  • for more than 2 hours on any school day or for more than 12 hours in any week in which required to attend school
  • for more than 2 hours on a Sunday
  • for more than 8 hours (5 if under 15) on any day which is not a school day or a Sunday
  • before 7am or after 7pm
  • for more than 35 hours (25 if under 15) in any week in which not required to attend school
  • for more than 4 hours in any day without a break of one hour.
  • The law does not make any prescription about the wages to be paid to children who work. Minimum wage legislation does not apply to workers under the age of 16.

Children’s reasons for working and possible benefits and negative effects

The motivations of children for undertaking work vary. Children are not necessarily driven to employment by poverty, although this is the reason in some cases. In the context of youth employment, children have jobs for a number of reasons that are more matters of choice than circumstance. In some cases, the work may be in an area that interests the child or they may undertake work in order to have a learning experience. Many children take jobs because of the extra money that they can earn to spend on leisure interests. A number of children who have jobs report that they enjoy their work and appreciate it because it gives them a sense of independence and also teaches them about the value of money.

The UNICEF Working Children Survey (Spring 2004) questioned students between the ages of 12 and 16 about their attitudes toward work and the involvement in employment. They found a number of children who indicated that they worked outside the hours permitted by law and a number worked longer hours than allowed. More than 40% of the young people surveyed indicated that their parents had helped them find their job. The majority of students questioned felt that work was valuable both socially and financially. Some respondents indicated that working did add pressure to them for performance at school. For young people, over the age of 18, Mizen et al (1999) found that students are not interested in full-time work or in acquiring long-term or secure employment due to the constraints of University coursework.

In the US, it has been generally accepted for the past 30 years or so that youth employment is a standard feature of adolescent development (Mortimer and Finch 1996). There seems to be a consensus in the US that moderate levels of work, in relatively benign jobs, is beneficial for children through increasing self-reliance and independence (Mizen et al 1999). Working more than 20 hours per week however, has been correlated with a range of adolescent problems. Similarly, a study from Ireland found that working part-time was associated with underperformance at upper secondary level and was also found to be associated with increased drop-out (McCoy and Smyth, 2007).  In 1999, Mizen et al noted that it was then a reliably accepted idea that “paid employment is an extensive feature of contemporary British childhood … that extends beyond the realms of traditional ‘children’s work’, into a range of jobs characteristic of the service sector more generally.”

A MORI Poll, Class Struggles, carried out for TUC[11] found that more than 100,000 school children had played truant in order to work in 2001. Boys were more likely than girls to take such actions. The survey indicated that 1 in 4 children under 13 years of age undertook paid work. Extrapolated to the entire UK population in this age group results in a total of 289,000 working. A significant proportion of the survey’s sample reported that they had worked outside legal working hours for their age group. The survey also found that most working children (31.5%) earned less than £2.50 per hour.

2.2      The more negative aspects of children’s work

Child labour is often considered a problem of only developing nations. However, UNICEF indicates that it is a problem in the industrialised world as well, with some children doing work that is hazardous or otherwise unacceptable. This is often the case for children who have been trafficked into the country. The EU Directive on the Protection of Young People at Work was established in 1994.  This aimed to reduce discrepancies regarding youth employment in the member states. The Directive sets out minimum standards for all EU countries regarding the employment of children and young people. The UK was slower than a number of other EU countries to modify its laws in accordance with this Directive.

The fact that workers under the age of 16 are not covered by minimum wage regulations, leaves children who work open to exploitation by employers looking to cut costs. Children under school leaving age are not legally entitled to paid holiday from work. As a subset of the labour force, the child workforce has little or no bargaining power or weight in the labour market. There have been 38 prosecutions in the UK for the improper employment of children since records began in 2000 (UNICEF).

Walsh (1990) observed that one main advantage to employers of hiring students is a reduction in labour costs. Employers are able to pay students (under the age of 16) lower rates than they are required to pay workers over the minimum school leaving age. Employers may also be able to use student workers more flexibly than other segments of the labour force as these students may not accrue the necessary qualifications for some legal entitlements (Curtis and Lucas, 2000). The TUC’s survey (2000) found that students were paid £4.37 per hour on average and that 3% of student workers were being paid rates below minimum wage.

The Commission on Vulnerable Employment has indicated that young workers, who are not entitled to the same rates of minimum wage as other workers are more likely to face exploitation. They also cite evidence that young people are more likely to face exploitation at work than are older workers. The MORI survey’s findings support the notion that younger workers face exploitation. 75% of children aged 11 to 15 years were reported to work and 30% of those with term time jobs reported working for more than the maximum numbers each day. Almost a third of the sample were paid £2.50 per hour or less. Nearly 20% working during term time were paid less than £2 per hour. While illegal, 25% of children under the age of 13 indicated that they worked during the term or during summer holidays.

Despite there being a number of regulations in place to protect young workers, the vast majority (79%) of children who work in the UK do so without a permit (UNICEF). There is also evidence that a proportion of these working children are exploited by the people they work for or face hazardous working situations. Taylor (1998) found that despite having initially agreed to hours of work that would not interfere with their academic studies, many working students later found themselves feeling pressured to work less convenient hours.

Children who are trafficked into the UK face even greater risks and are more prone to being exploited than those who are more visible and ‘protected’ by child employment regulations. Some trafficked children are smuggled into the country for the sole purpose of employment. For others, their vulnerable position leaves them open to being exploited in work (or worse). Some work extremely long hours in poor or dangerous conditions. Some children, most notably those from China, are bonded and must work in order to pay back their bonds. In a number of cases traffickers and employers of trafficked children threaten the safety of the child or his family in his home country in order to force the child to work. Children who have been trafficked into the country to work have been found working in restaurants, on farms and factories, in criminal activities, providing domestic labour and working in the sex industry. A UNICEF study (2003) found that 250 child trafficking cases had been uncovered in the UK since 1998.

2.3      The future of children’s work

Focusing on the more ‘acceptable’ types of children’s work (as discussed in Section 2.1), the numbers of children in such employment is likely to increase in the future if current and recent trends continue. Even greater increases may be seen as children seek their own financial independence, so they can fund ever increasing costs of leisure (e.g. video game consoles typically cost over £100 and games can cost anything from £20 to £80 each). Increasing competition for entry into post-secondary education and for employment opportunities later in life may also motivate children to undertake employment earlier in order to build up their learning and work experiences and to indicate their drives and ambitions.

As mentioned in Section 2.2, laws covering the employment of children in this country are not overly stringent and according to many are fragmented. The Better Regulation Task Force (2004) notes that the laws regarding child employment in the UK are relatively old, with piecemeal adaptations and local by-laws that often compound the problems that exist in interpreting and enforcing these laws. This leaves room for breaches of regulations to occur. In the future, either the laws regarding children and employment will be enhanced and greater enforcement of these laws exercised or children’s employment will continue to pose potential hazards and injustices for children. If unscrupulous employers see that they can cut costs by employing young people in jobs that are suitable only for adults, then children may be exploited for the monetary gains of these people. Educating children on the protection that the law offers them in work is also necessary to empower these children in employment matters.

More positively, if employers were to engage with children’s agencies, schools and government bodies, jobs could be designed that would be age-appropriate and provide good learning/work experiences for children while enhancing the performance of businesses. With the development of new technologies and the dissemination of such technologies, children may also be provided with greater opportunities to exercise their creativity and fulfil their own interests while at the same time capitalising on these things for monetary gains. One example could be that young people may work part-time, independently, to design or manage websites for other people or companies, or design or get involved in other aspects of game design and ‘virtual’ worlds (for further discussion see Section 5). Such ‘jobs’ may lead onto business opportunities or career directions for these young people in adult life.

Possible futures

Worst case scenario

• Children are forced to take on more paid work, even if they do not wish to do so for their own interests, in order to help support family
• children work in inappropriate jobs that are not of interest to them and pose dangers to their health, safety, development and welfare
• employers opt for cheap child workers in order to cut costs, particularly in the absence of tighter enforcement of child labour laws
• trafficked child workers continue to fly below the radar and are an unseen part of the labour force
• more use of child labour in foreign countries in order to cut costs of manufacturing and to provide cheap products to the UK.

Best case scenario

• employers engage with schools to create work opportunities that enhance the well-being and development of children
• children choose whether to work or not, without the stress of having to work out of financial necessity
• through work, children’s entrepreneurial skills are developed and they acquire skills that help them in later life and ultimately contribute to the country’s economic performance
• trafficking and exploitation of children in work is drastically reduced due to improved regulation and enforcement.

Most probable scenario

• reorganisation of laws relating to children’s work
• more public awareness of child trafficking and the use of these children in work which should pressure authorities to further clamp down on such activity
• the dissemination of information through the internet may result in children being more aware of their rights which would empower them in the labour market
• children may become more aware of the potential benefits of work and may seek out opportunities that meet their own interests, while giving them some financial independence.

3.      Entrepreneurial activity and practices

3.1      Importance of entrepreneurial activity in the UK

Enterprise is noted as one of the five key drivers behind productivity growth in the UK. Entrepreneurial activity takes many forms and makes a substantial contribution to the country’s economy.  Stel et al (2005) found that nascent entrepreneurship positively impacts GDP in rich countries (see also Davidsson, 2006). The Lisbon Agenda considers raising regional entrepreneurship levels to be one of the main policy instruments to tackle Europe’s problem in keeping up with productivity growth by existing and emerging economic powers.

3.2      The UK’s entrepreneurial performance

Entrepreneurship has become a common notion in today’s British popular culture.  Television programmes like the BBC’s Dragons’ Den, and other reality programmes that follow fledgling companies or show individuals competing for start-up funds, have become more common and gained huge numbers of viewers. The aim of such shows and the media coverage of entrepreneurial activity is to stimulate interest and further activity. However, sometimes this exposure can downplay the real risks and the level of skill and knowledge required to start a successful business.

According to HM Treasury (2008) report, Enterprise: Unlocking the UK’s Talent, there has been considerable progress in promoting a enterprising economy over the past 10 years. Business survival rates are higher than ten years ago (92% of new VAT registered businesses are still registered after one year and 71% after three years). Productivity growth in small firms has been greater than that in large firms since 1998.

In 2005, the number of young people indicating aspirations to start up in business was 200,000 greater than in 2002. There are currently a record number of businesses operating in the UK. There were 4.5 million businesses in the UK at the start of 2006 which was more than 750,000 more than in 1997. There are a number of reasons for the significant increase in business numbers, including:

• the rise in population
• influx of entrepreneurial immigrants
• the development and roll out of modern telecommunications, and
• tax incentives for smaller companies.

It is important to note that more businesses does not necessarily mean that the UK is more ‘entrepreneurial’, as research by the University of Sheffield found that the business start-up rate per 1,000 inhabitants fell between 1997 and 2004.[12] This research also found evidence that some private sector entrepreneurial activity is crowded out by the public sector.

While the World Bank has ranked the UK second in Europe, and in the top ten countries in the world, on measures of ease of doing business, the UK lags behind the US in some indicators. The US has 20% more businesses per head than the UK. A significant part of this gap is explained by considerably lower rates of women’s enterprise activity in the UK. The rate of growth exhibited by new businesses once they are established is also greater in the US than in the UK.  Some 40% more US businesses achieve high growth than do UK businesses. More than a third of established businesses in the UK have no ambition to grow.

The fear of failure is also greater in the UK than in the US. In the US, 23% of people say that such fear would prevent them from starting a business, while 36% of people in the UK indicate fear of failure as a barrier to staring a new business (GEM, 2007). In the early part of the current recession, start-up activity in the UK appeared to have remained resilient in the UK.[13] There was a decline in the Spring of 2008 which resulted in the numbers for the year being only marginally lower than they were in 2007. In the three months to September 2008, the number of new businesses that started up fell by just 4% to around 129,000. Barclays has reported no significant decline in the number of people wanting to start their own ventures going into 2009. Despite this resilience to date, the number of start-ups in 2009 is expected to fall significantly (Barclays).

The UK has a higher proportion of adults starting their own businesses than other European countries, and the UK’s levels of entrepreneurial activity are better than those in continental Europe. The UK also has better sustainability ratios (ratios of established businesses to start-ups) than the US and Canada. In the UK, the proportion of people operating established businesses is 93% of the start-up rate, indicating that the majority of ventures are successful.

The GEM UK 2007 indicates that there are regional differences in the levels of entrepreneurial activity taking place in the UK. In 2006, London, the South East, the South West and the East Midlands had the highest levels of early stage entrepreneurial activity in 2006 but they experienced declines in 2007. While three of these four regions remained the highest activity regions in 2007, the decline in early stage entrepreneurial activity in the East Midlands was sufficient to decrease the regions ranking to 8th place. There were increases in early entrepreneurial activity in Scotland, the North East, Northern Ireland, Yorkshire and the Humber, the North West and the West Midlands. The West Midlands had the 4^th highest level of activity in 2007.

There was an increase in entrepreneurial activity in the Northwest from 4.6 to 4.9% between 2006. This region is observed to have higher levels of entrepreneurial activity amongst 18 to 24 year olds than the UK average (4.7% vs 3.8%).

The GEM UK 2007 report also notes gender differences in early entrepreneurial activity with men more likely to be engaged in such activity than women. In 2007, this difference between the sexes was greatest in Northern Ireland. The South West had the highest level of female entrepreneurial activity in 2007 at 4.6%. Men are also found to have more positive attitudes towards entrepreneurial activity than women.

3.3      The future

According to the Global Entrepreneurship Monitor United Kingdom 2007 Monitoring Report (GEM UK, 2007), the UK has generally positive attitudes towards entrepreneurial skills and the perception of start-up opportunities compared to the other G8 countries. The monitoring report compares Global Entrepreneurship Monitor (GEM) measures of entrepreneurial activity in the UK with participating G7 countries, and the large industrialised or industrialising nations of Brazil, Russia, India and China (BRIC). It also summarises entrepreneurial activity within Government Office Regions of the UK

The Government has done much to develop awareness, aspirations and motivations regarding enterprise. Amongst young people aged 14 to 30, there as been a 22% increase since 2003 in the number who intend to start a business and a 50% increase in the number taking part in enterprise training activities.

According to CIHE, the competitive capability of the UK will rest more than ever on enterprise and innovation in products, services and management. CIHE emphasises that developing entrepreneurial graduates is essential to future success of the UK economy.

Enterprise: Unlocking the UK’s Talent outlines some of the future challenges and opportunities that the UK may face in terms of optimising the economic and wider benefits of enterprise for the UK. The Government has a vision of a society in which the contribution of entrepreneurs and enterprise is encouraged and valued and therefore wants to encourage a culture of enterprise. The UK needs to improve some people’s perceptions, particularly with reference to the country’s relatively high ‘fear of failure’. Countries with higher rates of fear of failure tend to have lower rates of entrepreneurial activity. In developing a culture of enterprise the Government has made a number of policy proposals including actions regarding insolvency rules, starting a women’s enterprise campaign, and starting a Global Entrepreneurship Week.

In order to position itself in good stead, the UK also needs to ensure that it has sufficient enterprise knowledge and skills to meet future challenges and opportunities. The Government has committed a further £30 million to extend enterprise education from secondary schools into primary and tertiary education. The Government is also taking steps to increase workforce skills training and to improve access to business support.

The availability of finance to people who want to start up businesses is also an important factor which is proving a great challenge given the current economic downturn. At the beginning of 2009, the Business Secretary, Lord Mandelson, has pledged £35m for start-ups in North West with the ambition that “nurturing and protecting start-ups and young businesses through this downturn will lead us into the upturn that will follow”. Barclays increased the amount of lending to small and medium enterprises by 6% to about £15 billion in the past year and has pledge to make at a least a further £1.5 billion available to this group of businesses in 2009.

In the future there are many potential opportunities on which an enterprising nation may capitalise. New business opportunities will come from the development and growth in countries such as China, India and Brazil. The disposable incomes of people in these countries will grow, creating export opportunities for the UK. These new markets have already been proving fruitful. Between 2002 and 2006, UK exports to China and India increased by, on average, 19% and 14% per year, respectively.

The development of the UK as a Knowledge Economy also presents opportunities for entrepreneurial activity. New technologies and services themselves present opportunities for new businesses to develop or for established businesses to grow. New industries will also be created, such as green industries. The environmental goods and services sector in the UK has an estimated turnover of £25 billion and employs 400,000 people.[14] New technologies that will need to be developed for the low-carbon economy will present potentially lucrative opportunities for people wishing to start a business.

Possible futures

Worst case scenario

• the credit crisis and financial downturn worsen, resulting in very limited financial support being available for start-ups, young businesses and SMEs
• the UK fails in its attempts to promote a culture of enterprise and lacks the skills, knowledge and attitudes necessary to take advantage of future opportunities
• growth becomes restricted due to inadequate entrepreneurial performance.
• women’s entrepreneurial activity rates increase substantially and help to close gaps with the US
• the UK’s culture of enterprise attracts more outside investment in UK businesses and increases the number of foreign businesses being set up and operated in the UK
• young people see starting their own businesses as viable options for future careers
• UK start-ups and SMEs increase their ambitions for growth and make strategic decisions to achieve growth.

Best case scenario

Most probable scenario

• women’s involvement likely to increase
• credit and finance moderately constrained in the short to medium term
• after the financial downturn, lenders are likely to be more careful than before in lending criteria used to evaluate start-up business’ and SMEs’ applications for borrowing. This would not necessarily be a negative outcome as suitable criteria may ensure that the majority of businesses that start up are likely to succeed
• enterprise education to take more prominent role in young people’s education, thus enhancing the entrepreneurial skills and knowledge base of the future workforce.

4.      Innovation and intellectual property rights

4.1      The importance of innovation

Like enterprise, innovation is also considered one of the five key drivers of productivity. BERR defines innovation simply as the “successful exploitation of new ideas.” This includes all innovation, including non-technological. According to BERR, innovation is central to better jobs, economic growth and prosperity. Innovation is vital to increasing the UK’s competitiveness, improving the economy and increasing the quality of life. Innovation can also help to meet challenges such as climate change and pollution.

For businesses, innovation can result in sustained or improved growth, through enabling entry into new or different markets, and through improving day to day performance. Businesses may innovate through product innovation, process innovation and strategic innovation. For consumers, innovation is important in creating new or improved products and services, with greater value for money, and in improving the overall standard of living.

Innovation is an increasingly important issue, as companies who do not innovate will not maintain their competitiveness because if they themselves do not innovate than someone else will do so and will gain an advantage. Businesses may need to innovate for a number of reasons (DIUS 2008):

• to gain competitive advantage or to respond to competition
• to create efficiencies
• to improve customer satisfaction
• to reposition the business in the market, and
• to comply with new regulations.

These factors, and a number of others, motivate businesses to innovate and may also influence the level and type of innovation undertaken by businesses.

Those companies that adopt innovations created by others, or who seek to innovate themselves, face a number of potential advantages and opportunities. For innovating companies and individuals, Intellectual Property Rights (IPR) is a vital issue that comprises an important part of their business operation and strategy.

4.2      UK’s innovation performance

The UK is identified as an Innovation Leader in the 2007 edition of the European Innovation Scoreboard, placing the UK in the leading group with Japan, US and several EU countries. The 2005 UK Innovation Survey results indicated that 57% of UK enterprises were involved in innovation activity. The 2007 UK Innovation Survey showed an increase in activity to 64% of firms. Product or process innovations have been implemented by around a quarter of businesses, while around a third of enterprises have undertaken some form of strategic innovations. A positive correlation was found between firm size and innovation activity. Extending the concept of innovation activity to cover enterprises that invest in preparing for future innovation, or amending their organisational structures and strategies, results in 66% of UK businesses being considered innovators over the UK Innovation Survey 2007 survey period (2005-2007).

A much greater share of economic activity and employment was found in businesses that innovate. Almost 45% of employment was found to be in businesses having one or more forms of strategic innovation. The DIUS survey indicates that there are both regional and sectoral differences in the level of innovation taking place in UK businesses. The largest share of innovators with plans for future product or process innovation was found in knowledge intensive services. The ‘other services’ sector was found to have the lowest share of businesses with innovative inclinations (54%). Construction witnessed the greatest increase in innovation activity between the 2005 and 2007 CIS surveys. The lowest share of innovation active businesses was found in the London (55%) while the greatest share was found in Eastern England (69%). Where no innovation activity was indicated, the DIUS surveys in 2005 and 2007 found the most influential factor to be market conditions limiting the need for innovation.

The fourth Community Innovation Survey (2007) ranked the UK 12^th in the EU in terms of the percentage of all enterprises that are innovation active among all enterprises. In 2007, 43% of all businesses in the UK were innovation active. Higher rates were found for Germany (65%) and Ireland (52%) while the EU27 average (42%) was just below the UK figure, as was the rate in France (33%).

The DIUS Annual Innovation Report 2008 overviews the UK’s performance in innovative activity.  In terms of businesses’ investment in research and development (R&D) (a fundamental component of innovation), the UK ranks 5^th in the G7 countries. R&D performed by the largest companies increased by 5% from 2005 and 2006 in real terms. The UK’s number of US patents granted per head is ranked 5^th in the G7. In 2006, the UK spent 1.75% of GDP on R&D, representing a 4% real increase since 2005.

DIUS has set out a number of the strengths and weaknesses of the UK innovation system. These strengths and weaknesses are detailed in Table 2.

Table 2: Summary of strengths and weaknesses of the UK innovation system

Source: DIUS (2008) Innovation Nation – Background analysis: strengths and weakness of the UK innovation system. Table 1.

4.3      Intellectual Property Rights

According to the Gowers Review (HM Treasury, 2006), “in today’s economy, knowledge capital, more than physical capital, will drive the success of the UK economy.”  In light of this, intellectual property (IP) rights are more important than ever before. With technological advances and increased capabilities to freely share information, IP rights are vital to protect the work and competitiveness of companies and Governments. IP rights are bound by the regulations set internationally but they are of significant concern for the UK as a nation as they are essential to ensuring that the benefits from innovation that takes place in the UK are reaped by the country.

The Community Innovation Survey identifies a number of innovation protection methods which, some of which may be considered forms of intellectual property rights. These methods include:

• Registration of design
• Trademarks
• Patents
• Confidentiality agreements
• Copyright.

According to the 2007 survey, confidentiality agreements were considered to be of high importance by 18% of businesses. The proportion of respondents attaching high importance to the measure of innovation protection increased for all methods between the 2005 and 2007 surveys[15]. This may be indicative of a greater need to protect businesses’ innovative and intellectual property or could indicate the increased awareness of this need and of ways to ensure protection.

The Gowers Review set out an intellectual property system meant to be fit for the digital age. The review suggested strengthening IPR enforcement through a number of avenues. The review also suggested ways to support businesses in relation to IPR and how to set out IPR while maintaining a balance between freedoms and protection.  Since the Gowers Review, Trading Standards officers have been given powers of search and seizure in relation to certain kinds of offences which include copyright violations. In 2008, the Government pledged a further £5 million to assist Trading Standards officers to undertake these new duties.

It is important the IP rights regulations and laws are themselves innovative and that they change over time to reflect the risks and security issues associated with IP and new developments. The UK’s Intellectual Property Office has published a consultation regarding IP which was concerned with four main issues: access to works, incentivising investment and creativity, recognising creative output, and authenticating works. The Strategic Advisory Board for IP Policy (SABIP) was launched in effort to consider the strengths and weaknesses of IP in the context of a rapidly changing environment. SABIP recognises that growth rates are higher in the creative sector than in the economy as a whole and that rapid technological change and globalisation have brought into question many aspects of the existing copyright system. SABIP considers the development of a copyright agenda for the 21^st century as timely and necessary. Digital Britain also identified IP as a key issue for the UK’s digital economy.

4.4      The Future

According to BERR “success in the future will come from businesses increasing the added-value of their products, processes and services.” Given this future importance, nine strategic EU priorities for innovation have been set out (see table 5.1).

Table 3: Strategic EU priorities for innovation

Source: BERR (see www.berr.govuk/dius/innovation/page38831.html)

The future of innovation, especially technological innovation, in the UK is closely linked to developments in the supply and quality of STEM workforce[16]. STEM-skilled people are necessary for R&D and for scientific innovation to take place. Should the fears over the supply of STEM graduates not be confronted and allayed, the future of innovation in the UK will be tightly constrained. However, if the UK keeps up its supply and quality of STEM workforce, then the country will be well placed to take advantage of future opportunities that innovation activity may provide.

The future will present numerous opportunities for innovation of which the UK Government and businesses will want to take full advantage. New customers, production patterns, technologies and expectations will provide great opportunities for employment, businesses and even new industries[17]. It is important then that the UK continue to innovate and to increase its capacity to innovate in order to ensure it is ready to take advantage of future opportunities.

The increasing importance of the environmental agenda is one area that will certainly pose further opportunities in the future. As consumers continue to make businesses aware of their concern for the environment and their desire for ‘green’ products and services, businesses will need to come up with new ways of working and new or modified products and services to meet these tastes. Companies whose products/services are not capable of been ‘greened’ will either go out of business or will have to come up with innovative solutions to move into other sectors. The green consumer will also require new, to date unheard-of products that will fit in with greener living. This demand will provide opportunities for existing businesses to enhance their own products/services to fill this requirement or to create new products/services to fit the need.

5.      Emerging economies owing to technological change

This section looks at types of emerging or new economic activities that may constitute significant areas of work and activity in the future. These emerging economies were probably unimaginable for most people 5 to 10 years ago. However, as video games and virtual worlds become more sophisticated and increasingly allow people to interact online, their prominence in everyday life will increase as well. Also, as internet access and people’s interest in technology has increased other opportunities have arisen.

Some of the issues to be discussed here include the opportunities presented by massive multi-player online role-playing game (MMPORG) and the use of virtual or synthetic worlds for business and leisure purposes. These are not yet mainstream activities but by the time that people born since the late 1980s are in work and form the majority of the labour force, these relatively novel opportunities and ways of working may become widely used and accepted and contribute significantly to employment and GDP.

5.1      Virtual/synthetic worlds

Virtual worlds are computer based simulated environments intended for users to inhabit and in which users interact through avatars. Virtual worlds are shared spaces that allow multiple users to take part simultaneously. Things take place immediately in the virtual world once an action has been taken by a user. Virtual worlds are not completely alien concepts as they have much in common with the real world. Forces like gravity and cause and effect are exhibited in both, and things like the economy and market are important features of virtual worlds.

Virtual worlds offer new ways for groups of people to interact, exchange information and conduct business over the internet. There are a number of types of virtual worlds serving various purposes. Some virtual worlds are gaming worlds (eg World of Warcraft and other MMORPG). Other virtual worlds are mainly operated for social networking and online communities (eg There.com). Virtual worlds are sometimes created to facilitate immersive education, or corporate collaboration. Business oriented virtual worlds support a wide range of activities including e-commerce, virtual events, marketing and branding, customer service and interaction, recruitment, advertising, and product demonstration. Virtual worlds may be used to build customer loyalty and to gain valuable feedback through focus groups.

These worlds also create new opportunities for business, providing venues for customers to socialise, collaborate, purchase goods, train and play.  While relatively new, virtual worlds represent a significant opportunity for business and economic benefits to the economy. In the US, there has been significant investment in virtual world-related companies over the past few years. According to Virtual Worlds Management, venture capital and media firms invested more than US$425 million in 15 virtual world-related companies (with US$50 million concentrated in just two acquisitions) in the fourth quarter of 2007. There were investments of US$493 million invested in virtual world-related companies in the first three quarters of 2008 with US$148.5 million in 12 virtual world-related companies in the third quarter. Of these investments, the greatest shares are in companies with entertainment spaces (.e meant for leisure and entertainment use rather than education or business). Over US$1 billion was invested in 35 virtual world operations in the year to October 2007.[18] While these are large sums of money, they are still dwarfed by corresponding investments in the real economy.

Second Life is a relatively common example of a virtual world. Second Life was created by Linden Lab and opened to the public in 2003. Since its launch it has gained more than 2 million members. This three dimensional virtual world is accessed through the internet. Users download a client program and through this they can create avatars (characters) and other items (houses, furnishings, etc). Members of the Second Life world pay membership fees. This virtual world has its own virtual and economy with a currency, Linden dollars ($L), that has traceable exchange rates with money in the real world ($US).

Users interact in many ways in the Second Life virtual world. More savvy users create various items which they can sell/rent to other Second Life inhabitants. Residents can take part in numerous activities, in public or private, in the Second Life world. There are group activities, learning activities and more unsavoury activities taking place in Second Life.

While Second Life is a fairly well-heard of virtual world, it has not been without its problems since its launch in 2003.[19] A number of companies have entered the Second Life environment hoping to capitalise on marketing and advertising opportunities. This has proved relatively unsuccessful. Other problems have been encountered due to the sometimes fuzzy line separating virtual activities from reality. Second Life has shut down casinos due to the prohibition of online gambling in the US. Tax authorities in the US also have difficulty determining the appropriate tax treatment of money generated through such virtual worlds as Second Life. The use of virtual worlds for unlawful or unsavoury activity is also a problem and there have been cases in Second Life where things such as real child pornography have been exchanged between members.

Second Life’s membership is high.  However, there is concern that interest has been waning. The number of active members is believed to be much lower than the total number of members. Restrictions placed on this virtual world because of its notoriety are having effects on its popularity. The availability of other virtual worlds with free membership, such as There.com[20] and yoowalk.com, or with different foci increases the level of competition faced by Second Life.

5.2      Economic and business opportunities presented by virtual worlds

A number of business opportunities have come from the existence of virtual worlds such as Second Life and massively multi-player online role-playing games (MMORPG) such as World of Warcraft. These new environments present opportunities:

• for real business processes to occur in the virtual world
• for new employment opportunities to be generated in the real world through satisfying demand for various virtual commodities
• for producing and expanding these types of environments and games, and
• for policy proposals to be investigated through virtual ‘experiments’.

Companies such as Intel, Cisco, IBM, Stanford University and Diageo all hold regular internal and occasionally external meetings of their employees avatars in virtual worlds.[21] Military and emergency services have also been using virtual worlds and simulation games that enable training.

Forbes.com set out 10 ways to make real money in virtual worlds. Virtual worlds allow for people to make real-world money as[22]:

1. Gold Farmer – considered an ‘easy’ way to make money, involves spending a lot of time playing games with the sole objective of collecting as much of the game’s currency (typically gold coins) or weapons. The gold, weapons or other items are then sold to other gamers (with less time to play) through onsite trading (eg ebay). This is a popular pursuit in Asia where companies have been found to pay employees to work shifts of eight hours or more and then sell the accumulated wealth to players in Europe or America. According to Edward Castronova, trading of real dollars for gold pieces is more than $1 billion each year. [23]
2. Prostitute – the world’s oldest profession has infiltrated the virtual world, perhaps even more than it is practiced in the real world. In Second Life, prostitutes receive Linden dollars for services rendered online. This game currency can then be exchanged with others for real money. In 2007, a sex business in Second Life sold for US$50,000 on ebay.
3. Power Leveller – this involves playing games to advanced levels on behalf of other players who do not have enough free time to advance in the game as they would like to. EZGamers for example, will log into a game as a person’s character and play on their behalf. Prices charged for this service vary but a full 24 hours of focused play would cost about $25.
4. Merchant – games and environments like Second Life often allow for users to create unique virtual items such as clothing, weapons, home furnishings which they may then sell in game for virtual currency or elsewhere online (eg ebay) for real money.
5. Designer – Second Life users and other similar virtual worlds often desire custom-designed clothes to create beautiful avatars. Manufacturing virtual designer goods is relatively easy and the manufacturing costs are zero. While virtual clothing sells for relatively little virtual currency, bulk selling adds up and can result in real money gains. Listings for clothing and furniture can be found on ebay.
6. Architect – Similar to the idea for designers, people in games like Second Life, particularly those who spend much time in virtual worlds, like having nice virtual things and a home is one of these. Often the residents do not have the ability or want to build/design these things themselves so third parties may create an opportunity through selling such to players. Pre-built buildings in second life are traded on the game’s SL exchange with a castle, for example, selling for the equivalent of $53.
7. Gambler – this operates in pretty much the same way in virtual worlds as in real life. Virtual winnings can be exchanged for real world currency. A number of Las Vegas casinos had set up operations on Second Life but in 2007, gambling was abolished from Second Life as US laws prohibit online gambling and the treatment of virtual world gambling came into question.
8. Beggar – most online games allow players to give others in the game money or goods. While most players would give very little, if one has enough time, one could accumulate enough virtual goods/currency to exchange for a more substantial amount of real money.
9. Selling your character – once players are bored with a game, and if they have advanced sufficiently in that game, they may choose to sell on their virtual character to other players.  A student at the University of Virginia sold his World of Warcraft character on ebay for $1,200.
10. Landlord – property is available on Second Life (and other similar virtual worlds) but the most desirable properties are bought up very quickly. Virtual landlords, with sufficient land, may sell property to new players. In Second Life, this activity has netted relatively large sums of money for a number of individuals. One Second Life property trader reportedly owns virtual property worth US$250,000.

5.3       Open Source technology

Open Source is an approach to design, development and distribution offering practical accessibility to a product’s source (goods and knowledge) (Wikipedia). The most commonly known type of open source product is software. According to the Open Source Initiative, the definition of open source does not just apply to access to software’s source code but also to the distribution terms of which must meet the following criteria[24]:

• Free distribution
• Source code
• Derived works
• Integrity of the Author’s source code
• No discrimination against persons or groups
• No discrimination against fields of endeavour
• Distribution of license
• License must not be specific to a product
• License must not contaminate any other software.

The open source (OS) approach has been empowered by advances in ICTs and the proliferation of internet to homes and businesses. The term is now used with reference to software, hardware and user generated content. The OS approach involves the free sharing of code (in the case of software) which people can use, amend and change for their own purposes. The source code, as set out above, is free for use and redistribution and there is nothing to prohibit people from using it as a basis for the development of a product that they go on to market commercially.

This approach is becoming more and more mainstream, with significant economic impacts. The Standish Group International estimated that open source software (OSS) cost traditional software companies US$60 billion in 2008. The global loss due to use of proprietary software rather than OSS is estimated to be more than US$1 trillion per year with losses in the US thought to be at least US$400 billion.[25]

Perhaps the most well known example of OSS is Linux, an operating system that was first introduced in the early 1990s. The Linux Foundation values the Linux ecosystem at US$25 billion. It is used all over the world in applications such as the New York Stock Exchange, mobile phones, supercomputers and consumer devices. In a White Paper[26], the Linux Foundation (2008) estimated that building the Fedora 9 distribution of Linux would have cost US$10.8 billion had it been a more conventional proprietary development. Developing the Linux kernel alone is valued at US$1.4 billion.

The use of OSS in enterprises is becoming more commonplace, particularly in response to the possible cost savings that such software presents. Government too is moving towards more widespread use of OSS in order to save money. The feasibility of OSS use in schools has also been highlighted by the British Educational Communications and Technology Agency (Becta, 2005). However, to date, the Government has not modified its procurement policies in order to capitalise on the use of OSS.

The viability of open source hardware is also coming to the fore. OS hardware, typically computing and electronics hardware, is designed, developed and distributed in a similarly collaborative manner as OSS. Free information is shared on the hardware’s design, schematics, guides, associated software and so on. These details are then free to be developed further by users, and by-products can typically be sold. Arduino is an example of a company based on open source hardware. This company produces the Arduino circuit board, the design of which they have made open source. This allows others to produce copies of the board, redesign it and sell boards which copy the Arduino board design. The only caveat is that subsequent versions/creations based on the Arduino board must be on the board’s original Creative Commons license, so that new versions are equally free and open as the original.

The idea of open source software and hardware implies very different business models than the conventional development of such products. In the case of open source hardware, one way in which companies operate is in producing ‘kits’ that enable consumers to build the product themselves and to make alterations/changes as they require. MAKE magazine is devoted to DIY technology projects and has detailed 60 open source hardware projects in 2008.[27]

Open source inventors/designers may often launch their projects without concern over how to make money from them. The inventors of projects (software or hardware) that become widely used often then become the main point of expertise for users, which may lead to opportunities for consultancy and development services in a more conventional manner. An alternative economic approach regarding open source hardware is that companies may create such hardware and market it. This hardware will then be copied by competitors but the inventor of the open source hardware should have the capacity to stay ahead of competitors, given the feedback and suggestions they receive from the user community. This is particularly true for quality issues as the original quality of such hardware may not be replicated by competitors, thus the inventor can stay ahead on quality grounds.

Related to open source hardware, or at least to users’ capabilities to make changes to and copy new technologies, is the idea of reverse engineering.  Individuals may reverse engineer products to figure out how they work and how they can enhance and change these products to suit their purposes and to use them for other applications. This can be a negative issue for companies as it undoubtedly involves some illegal copying of products, however, for others it may extend the usefulness and thus market life of other products, resulting in greater incomes for some companies.

5.4      Future opportunities

The future opportunities presented by open source technologies are numerous. The newly installed US president has already commissioned Sun Microsystems to assess the implications of open source for Government and to make recommendations on how it can optimise the benefits of OS technologies. The British Government has performed analyses of the feasibility of OSS for schools (see Becta above) and for Government departments and agencies.  However, its use is not yet universal in Government. As individuals, businesses and governments increasingly look to cut costs, open source technologies will become more mainstream, thus reducing profitability of proprietary software companies. Perhaps such companies will become redundant in the future?

Open source technologies also present opportunities to address inequality in society, especially for developing countries. Open source results in software and hardware being cheaper and more widely available thus poorer countries may be able to catch up with the technologies that are used in richer countries as open source is used in more and more applications.

The 10 ways to make money in virtual worlds described above (Section 5.2) are likely to continue, and many may take on more significance in the future as games become more and more popular and as more people in the world increase their levels of disposable income.

According to Zhao et al (2000), virtual worlds present greater opportunities for human-centric work than do the more traditional ways of working and workplaces. Personal motivation and the satisfaction of personal decision-making are common features of online communities. As more human-centric work becomes more valuable to many people and seen as a more productive means of working by many, the organisational forms in online environments may be more commonly used for work than they currently are.

The types of virtual worlds that exist in the future will help to shape the opportunities that may arise from them. Current investment trends in virtual world-related companies shows that more investors are becoming interested in virtual worlds for youth and children. Virtual worlds for these groups, such as Club Penguin (owned by Disney), are popular, with growing memberships. There is a definite market here.  There are even online payment systems such as Ukash being developed for children who usually don’t have credit cards which are the most used type of online payment method. There is also a version of Second Life explicitly meant for teenagers aged 13 to 17[28].

From entrepreneurs to large multinational corporations, interest in virtual worlds is growing quickly. In the future, the corporate use of virtual worlds looks set to grow for activities such as meetings and staff training. Use of virtual worlds for such activities could help businesses to improve their productivity through reducing costs. Virtual activity could also save them time, money and resources. As companies use virtual worlds to generate revenue through marketing, branding and advertising, new and innovative forms of interactive advertising will arise. This could possibly compete with the use of typical real-world advertising media such as posters and billboards. Virtual worlds may also enhance collaboration through flexible application sharing.

In the future, hybrid types of virtual worlds are likely to arise for gaming, social networking, immersive education, corporate collaboration, business activities and focus groups. While no one predicts that virtual worlds will replace real physical interactions, they may enhance such meetings and will enhance the 2-dimensional internet.

With increased use of virtual worlds and increased opportunities to make real money from such worlds, it is inevitable that some people will take advantage of opportunities to commit crime in these virtual worlds. Already, child pornography has been exchanged in virtual worlds. The use of more online trading with real world money may also lead to increased opportunities for identity theft and fraud. Harassment and bullying that takes place online may also have significant real world impact on individuals, particularly vulnerable people such as children. The negative aspects of technological advance are discussed in Section 6.

6.      Possible negative effects of technological development

While technological developments are generally considered to be of great benefit to society and the economy, there are also often negative effects associated with advances in technology and the proliferation of such technologies amongst the population. Almost all technological developments have some negative social and economic effects in today’s world. Whilst the monetary value of some negative social effects may be difficult, near on impossible, to measure, it is possible that the negative side of technology advancement can sometimes outweigh the positive effects. Whatever the impact, the negative implications of advances in technology are important and should not be dismissed.

6.1      Work and the workplace

6.1.1   Telecommunications – remote working and offshoring

Most technological advances impact on the nature, form and content of work, and on the workplace itself. Some of the negative impacts particularly affect how work is performed and the productivity of workers. Developments in telecommunications, such as the widespread use of internet networks and the resulting increase in the ability of employees to work remotely has been hailed largely as a benefit to businesses and workers. In an ideal world, remote working gives employers virtually the same access to their employees they would have if they were working onsite, and employees can produce the same output remotely as they could if in the office. For employees, remote working can help solve problems created by conflicting work and home responsibilities by allowing for more flexibility of the work environment.

However, in some cases, remote working can create problems for both employer and employee. The quality of work may be an issue, as there may be difficulties with some employees working with no supervision, or there may be some things that simply cannot be done as well away from the office as they could be done onsite (eg collaborative work or work requiring physical outputs). For employees, being remotely connected to one’s work sometimes results in increased working hours as workers may be ‘on-call’ and are expected to be reached whenever needed for work purposes. For some people the technologies that allow them to work from home (or wherever) may be frustrating. The division between work and home life may be blurred by such working situations. People who work from home or elsewhere outside their company’s environs may also miss out on the social interaction that occurs with colleagues and clients in the workplace. This interaction can also be beneficial for knowledge sharing and the generation of ideas. Working remotely does not typically permit such informal and/or unplanned interaction to occur.[29]

Developments in telecommunications have also allowed some companies to move particular departments that do not require face-to-face contact with customers/users to remote or overseas locations. This has been a big development for customer service departments, particularly in the banking sector. Customers in the UK who call their bank to speak to someone about customer service issues may speak to a representative who is actually sitting at a desk in India or Canada. There have been many complaints from consumers voicing dissatisfaction with such service. But offshoring these and other services helps companies to cut costs.  If customers are displeased enough to stop doing business with a company then that is a significant negative outcome for the company. From the view point of employees in the UK, offshoring business functions puts some people here out of jobs.

6.1.2   Robotics and automation

Other advances that have impacted on work are robotics and manufacturing machinery that permits much of the manufacturing process to be automated. Automated bank machines and store checkouts have also been important cost-reducing technologies that have grown popular. Such technologies have allowed many companies to improve productivity significantly. On the negative side, however, many people have lost jobs due to automation. From a social perspective, the use of machines for banking (eg ATMs) and retail shopping (eg self-serve kiosks) may also be considered to have a negative impact on people’s day to day social interaction. The use of automated systems for customer services is also considered a negative development in many people’s opinions.

6.1.3   Use of internet at work

While the internet has benefited work and business in a number of ways, the personal use of internet by employees while at work is less beneficial to worker productivity and companies’ bottom lines. The CBI (2008) conducted a survey that indicated  that employees’ personal use of the internet while at work costs employers in the UK as much as £10.6 billion each year. The average UK employee spends 1.5 hours per week, or ten days per year, using the internet at work for personal reasons. Employers estimate that 4.4% of working time is lost in this way, with an average annual cost of £939 per employee. [30]

6.2      Social effects

6.2.1   Cyberbullying/cyber-harassment

Definitions and forms of cyberbullying

The Department for Children Schools and Families (DCSF), in its Guidance on preventing and responding to cyberbullying, states that cyberbullying is “the use of Information and Communications Technology (ICT), particularly mobile phones and the internet, deliberately to upset someone else”. According to the website www.stopcyberbullying.org, cyberbullying is:

when a child, preteen or teen is tormented, threatened, harassed, humiliated, embarrassed or otherwise targeted by another child, preteen or teen using the Internet, interactive and digital technologies or mobile phones. It has to have a minor on both sides, or at least have been instigated by a minor against another minor.

If an adult is involved or becomes involved in such a matter, it is then termed ‘cyber-harassment’ or ‘cyberstalking’.

According to a government study in the UK[31], more than one third of children aged 12 to 15 have faced some sort of cyberbullying. Cyberbullying/harassment is a serious matter that did not exist before various telecommunications technologies were created and became readily available and accessible to young people and children. While bullying and harassment are not new phenomena amongst children and teenagers, the means through which such activity may take place have changed dramatically with the advent of mobile phones and affordable internet services. Children and young people are very capable in using the latest telecommunications technology, and many have significant presence on the web. Cyberbullying can involve a number of actions on the part of the bully, including:  posting false or embarrassing information about the subject of the bullying on Facebook, MySpace or Bebo profiles, sending threatening or degrading emails or text messages directly to the subject, or circulating embarrassing information about the subject to others via text or email. In some cases, the bully may steal the victim’s password and send inappropriate or embarrassing messages to others or may use the victim’s password to inappropriately change the person’s profile.

A related term ‘happy-slapping’ describes a fad in which someone unexpectedly physically attacks another person and the assault is recorded, typically on a mobile phone’s video camera. These videos are often circulated to others via phone or email, and sometimes the ‘happy-slapper’ posts the video on the internet.

Statistics

The incidence of cyberbullying varies considerably between surveys and depending on the age group in question. Estimates vary from 11% to over 30%. Goldsmiths carried out research for the Anti-Bullying Alliance (ABA) in 2006 which found that 22% of 11 to 16 year olds had been victims of cyberbullying. According to the MSN cyberbullying report in 2006, 11% of 12 to 15 year olds in the UK had experienced cyberbullying. In a four year study on bullying, Noret and Rivers found that 15% of the more than 11,000 children in their sample had received nasty or aggressive text messages and emails. This demonstrated a year on year increase in the number of children subjected to bullying through new ICT. In research conducted as part of the DCSF cyberbullying information campaign, it was found that 34% of 12 to 15 year olds had been victims of such activity. Despite discrepancies in the actual percentages of young people who are victims of cyberbullying, the overall conclusion is that this problem is significant in the lives of many children in the UK and other countries.[32] Furthermore, with the increasing use of ICT by children and the greater importance that such technologies have in this generation’s daily activities, cyberbullying is likely to continue to be a growing problem.

Legislation and policy

As a form of bullying, cyberbullying is covered by the range of education law that deems bullying unacceptable and outlines that the school community has a duty to protect its members (students, teachers and staff). The Education and Inspections Act (EIA) 2006 sets out some legal powers which are more directly related to cyberbullying. It gives head teachers the power to regulate, to a reasonable extent, the conduct of pupils when they are situated away from the school grounds. This is particularly relevant for cyberbullying as it is very likely to take place outside of school but it has definite ramifications for school life. Some cyberbullying activities may be deemed criminal under a variety of different laws, including the Protection from Harassment Act 1997 and the Public Order Act 1986.

The Government has undertaken a number of initiatives in attempts to raise awareness and reduce the incidence of cyberbullying, particularly amongst children and teenagers. Guidelines for dealing with cyberbullying have been published by DCSF.[33] A number of organisations have websites devoted to providing information on cyberbullying and information on the help that is available to victims and their families.[34] Directgov also provides information for young people in relation to cyberbullying, its effects, how to prevent it and where to get help.

Effects of cyberbullying

While bullying is not a new phenomenon, cyberbullying is a relatively new concept with impacts on its victims that are also additional to those suffered by victims of ‘traditional’ bullying. Use of ICT to bully and harass enables the bully to reach more people fairly easily and quickly whereas traditional bullying is a more face-to-face, one-on-one activity. Reaching more victims means that the problem of cyberbullying may have greater overall impacts. The ease with which information can be shared in cyberspace also means that embarrassing or hurtful rumours, pictures or information related to victims can be shared with large numbers of people furthering the harm that this exposure causes.

New ICT also permits bullying to take place at times when face to face contact is impossible thus cyberbullying may be perpetrated 24 hours a day, 7 days a week. This results in the victim having no reprieve from the bullying and feeling vulnerable wherever he/she may be. New technologies also allow for increased anonymity of bullies, again creating more vulnerability for victims.

The effects of cyberbullying on victims vary. Depression, anxiety and other mental health issues may arise from cyberbullying. This can affect victims’ performance in school and relationships with others. In some cases, the negative behaviour escalates to the point where there is actual physical violence or harassment between the bully and victim. A number of cases have come to light in the media of young people committing or attempting suicide after being victimised by cyberbullies.

Workplace cyberbullying and harassment can have financial consequences for the victim and the organisation as it can lead to absenteeism and reduced productivity. Where the bullying affects the victim to the extent that they resign from their position the victim and his family may suffer financial hardships which may contribute to the break down of relationships.

With today’s young people and younger generations being considered ‘digital natives’ they are more adept at using ICT and other new technologies. These technologies are increasingly a part of their daily lives such that their virtual lives and real lives merge. With such increased use come increased opportunities for cyberbullying to take place. In the workplace, cyberbullying and harassment is increasingly problematic as ICT technologies become commonplace in most organisations. As social networking websites, video sharing websites and blogspaces become increasingly common and accessible, the incidence of cyberbullying and its impacts on victims may become more widespread and increasingly serious in nature.

6.2.2   Education sector

Advances in technology, like the internet and its wide coverage and ease of access, have had profound effects on education both in terms of content and how subjects are taught. Classrooms now have more than just blackboards and chalk. Electronic whiteboards, digital projectors and things like PowerPoint presentations are common means of delivering information to students in the classroom. While these new teaching aids have been considered improvements there may be some students for whom these devices lack the personal touch that they require to learn effectively.

The proliferation of home internet connections and the use of the internet by producers of knowledge to disseminate their work freely/widely has increased the opportunity for students to commit plagiarism if they are so inclined. Other technological developments however, have improved the tools available to teachers and providers to detect such plagiarism. Cheating in examinations using mobile phones for texting answers is also a relatively recent phenomenon made possible by developments in telecommunications technologies. A survey conducted by the student newspaper, Varsity, found that just under half of undergraduates who took their poll had submitted someone else’s work under their own name. Law students were found to be the most likely to plagiarise (62%).[35]

Advancing technologies have also had some negative impacts on the quality of students’ education. Text messaging, for instance, and the abbreviated slang many people use in texts is thought to have had a negative effect on many young people’s and children’s ability in spelling and grammar. There have been ideas put forth that the system of spelling and grammar in the English language should change to accommodate text language rules, however, the general consensus appears to be that text messaging has had a negative effect on the literacy of some young people and children.

6.2.3   Identity theft and internet fraud

In 2000, CNN reported that the internet and online commerce was allowing criminals to use false identification to commit crimes. Since that time, increased use of authentification and other security measures have helped to mitigate the risk of identity theft and other forms of online fraud. However, in 2005, Dr. Emily Finch of the University of East Anglia asserted that increasing use of technology actually worsens identity theft and that human vigilance is the best defence against identity fraud[36]. Criminals themselves use technology to their advantage to clone bank and credit cards, steal people’s personal identification numbers (PIN), to produce counterfeit money, to produce false travel documents such as passports and find ways of circumventing technological security measures.

Phishing is the process by which a person or persons fraudulently attempts to obtain sensitive or confidential information including usernames, passwords and financial details by representing oneself as a trustworthy company or person in email or other electronic communications. Phishing emails often take the form of an email from ‘your bank’ requiring you to verify your password. Many phishing scams fraudulently represent themselves as originating from banks, financial institutions, social networking sites and IT administrators within companies. Data breaches in 2008 have been estimated to have cost companies £700 billion worldwide. Phishing scams and trogan keystroke loggers were found to be behind UK online bank fraud in 2004 that totalled around £12 million.

6.2.4   Terrorism

The internet and cheap mobile phones have allowed for some terrorist networks and for individuals with extreme views to communicate, increase membership and support, coordinate actions, and raise funds. The number of terrorist sites increased exponentially over the last 10 years from less than 100 to more than 4,800 two years ago.[37] However, these numbers likely underestimate the true presence of such sites and information online. Terrorist websites can offer information on constructing bombs or can serve as virtual training grounds for terrorist activities. A number of terrorist groups and extremists have their own websites with discussion pages where members/viewers share their opinions and ideas related to terrorism with the hopes of raising membership and morale. Terrorist networks use the internet and related technologies in a number of ways to benefits their organisations. According to the United States Institute of Peace contemporary terrorists use the internet in eight different ways:

1. psychological warfare
2. publicity and propaganda
3. data mining
4. fundraising
5. recruitment and mobilisation
6. networking
7. sharing information, and
8. planning and coordination.

Recent examples of the use of the internet and other new ICT by terrorist organisations includes the development of a new generation of encrypted software called “Mujahidden Secrets 2”. This software gives security to users that allows them to communicate freely through email without being observed by intelligence agencies or authorities. It has also been reported that Al-Qaeda want to create an online Jihad University.[38] There is also evidence of online gambling being used by terrorist networks to launder money and videos, blogs and virtual training platforms are believed to be used for recruiting and training terrorists.

Legislation and policy relating to terrorism and the internet and ICTs

The Terrorism Act 2006 prohibits the encouragement of acts of terrorism and the dissemination of terrorist publications. This Act deems inciting terrorism over the internet a criminal offence and those found guilty of such an offence may be jailed for up to seven years.

One of the key priorities related to preventing terrorism that is set out by in the European Union Counter-Terrorism Strategy is to “develop common approaches to spot and tackle problem behaviour, in particular the misuse of the internet.”

6.2.5   Pornography, sexual predators

With its free flow of information and connections between users all over the world, the internet has become an ideal forum for finding, viewing and sharing pornographic material. Most readily available statistics regarding pornography on the internet come from the US. The number of pornographic webpages in the US has been found to be 244.7 million while in the UK the number is estimated around 8.5 million. The internet pornography industry in the US had revenues of US$2.5 billion in 2005 and US$2.84 billion in 2006.[39]

Whether or not adults’ use of pornography is a bad thing is a very subjective matter; the exploitation of children in pornography and their exposure to pornographic material on the internet is generally agreed to be unacceptable. As children are starting to use the internet at younger ages and as they are more and more knowledgeable about use of the internet and other technologies, it is very likely that many young internet users come across pornographic material at some time. In the US, the average age at which a child is first exposed to internet pornography is estimated to be 11 years. Approximately 90% of 8 to 16 year olds have viewed pornography online.[40] The likelihood of children accidentally encountering pornographic images online is elevated by the links between children’s characters and pornographic websites.

The use of children in pornography and the exchange of child pornography on the internet are perhaps the most disturbing issues. According to the Guardian, the number of websites offering child pornography to UK internet users increased by 75% in 2005.[41] In 2003 the National Centre for Missing and Exploited Children (US) estimated that 20% of all internet pornography involves children. The US Customs Service estimated that 100,000 websites offer illegal child pornography. As of December 2005, child pornography was a US$3 billion per year industry.[42]

The widespread availability and large use of pornography on the internet is thought by a number of people to lead to breakdowns in families and relationships. In 2003, two-thirds of the 350 divorce lawyers who attending a meeting of the American Academy of Matrimonial Lawyers indicated that the internet was a significant factor in divorces with excessive interest in cyberporn being an issue in more than half of such cases.[43]

Grooming children for sexual exploitation or other harmful treatment has also been propagated through new technologies. Internet and online communication has proven to be a common means used by some people to make contact with young children (and older people as well) with the ultimate aim of exploiting the subject. Grooming involves befriending and gaining the trust of a child for the purposes of creating a situation where the child may be sexually exploited. Chatrooms, virtual worlds, and email communication are commonly used methods of contact and the anonymity such forms of communication afford to people has allowed many to pose as other children in order to enhance the level of trust between them and potential victims.

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This document has been commissioned as part of the UK Department for Children, Schools and Families’ Beyond Current Horizons project, led by Futurelab. The views expressed do not represent the policy of any Government or organisation.

[2] DCSF, Press Notice 2008/0017, “£140m boost to science and maths teaching in schools”, January 2008 (http://www.dcsf.gov.uk/pns/DisplayPN.cgi?pn_id=2008_0017)

[3] www.onrec.com/newsstories/21255.asp

[4] CIHE figures

[5] e.g. www.futuremorph.org, www.equalfuturez.net

[6] University of Birmingham, Press Release, 16 December 2008 (http://www.newscentre.bham.ac.uk/press/2008/12/16STEMprogramme.shtml)

[7] Pro Inno Europe (2005) European Innovation Scoreboard 2005 (http://www.proinno-europe.eu/docs/Reports/Documents/EIPR2006-final.pdf)

[8] HM Treasury (2004) Science and Innovation Investment Framework: 2004-2014

[9] Brockbank, S. (2008) “The UK STEM skills shortage” The Life Science Centre.

[10] The projections of employment by discipline for various occupational and sectoral categories take no direct account of changes in the flows emerging from the educational system (i.e. the supply side). They therefore conflate both supply and demand influences. They indicate the numbers that might be expected if recent trends continue.

[11] See www.hrmguide.co.uk/general/child_workers.htm for some highlight findings of the 2001 survey

[12] R. Tyler “Saving small firms has become big business in Westminster”, thetelegraph.co.uk, 29 December 2008,  (http://www.telegraph.co.uk/finance/comment/3982481/Saving-small-firms-has-become-big-business-in-Westminster.html)

[13] The Telegraph, 5 January 2009. “Start-ups remain resilient despite recession” (http://www.telegraph.co.uk/finance/yourbusiness/4125906/Start-ups-remain-resilient-despite-recession.html)

[14] HM Government (http://www.hmg.gov.uk/newopportunities/opportunities/ future_opportunities.aspx)

[15] DIUS (2008) Persistence and change in UK innovation 2002-2006

[16] See section 1 for more on the importance of STEM and its implications for innovation

[17] Cabinet Office (2008) Getting On, Getting Ahead

[18] Bailey, D. “Real dangers lurk in virtual worlds”, www.computing.co.uk

[19] Dell, K. “Second Life’s real-world problems” www.time.com

[20] Basic membership is free in There.com but a premium membership requires payment of monthly fees.

[21] Sawabey, P. “Serious business in virtual worlds” (2007) www.information-age.com

[22] Forbes.com (2007) “Ten ways to make real money in virtual worlds” (www.forbes.com/2006/08/07/virtual-world-jobs_ex_de_0807virtualjobs.html)

[23] http://www.econtalk.org/archives/2008/01/edward_castrono.html

[24] See http://www.opensource.ac.uk/mirrors/www.opensource.org/docs/definition.html for full definition

[25] BBC online, “Calls for Open Source Government” by Maggie Sheils (http://news.bbc.co.uk/1/hi/technology/7841486.stm)

[26] McPherson, A., B. Proffitt and R. Hale-Evans (2008) “Estimating the Total Development Cost of a Linux Distribution” The Linux Foundation (http://www.linuxfoundation.org/publications/estimatinglinux.php)

[27] “Open source hardware 2008 – The definitive guide to open source hardware projects in 2008” (http://blog.makezine.com/archive/2008/11/_draft_open_source_hardwa.html)

[28] http://teen.secondlife.com – basic membership is free in this version of Second Life

[29] The use of virtual meeting places for work purposes (as discussed in section 5) is thought to present a possible solution to this problem as in theory it allows for people’s avatars to meet and discuss things without planning to do so.

[30] CBI Press Release “Over 90 minutes a week spent on personal websurfing at work” (http://www.cbi.org.uk/ndbs/Press.nsf/0363c1f07c6ca12a8025671c00381cc7/94d596bf6bcd69708025745e003b722b?OpenDocument)

[31] Cyberbullying – Safe to Learn: Embedding anti-bullying work in schools, DCSF (2007).

[32] Recent studies in the US, Poland and Japan have found similar results to those in the UK (see Gardner, W. (2008) “Cyberbullying: a whole-school community approach” ChildRight, February 2008: pp. 25-28. According to Smith et al (2005) studies have shown that 13 per cent of children in Australia have been exposed to cyberbullying by year 8 while in the US 42 per cent o f9 to 13 year olds had been bullied online and 53 per cent admitted that they had bullied someone else online.

[33] Cyberbullying – Safe to Learn: Embedding anti-bullying work in schools, DCSF (2007).

[34] For example, www.stopcyberbullying.org, www.kidscape.org.uk/cyberbullying/

[35] Guardian.co.uk “Universities review plagiarism policies to catch Facebook cheats” (http://www.guardian.co.uk/education/2008/oct/31/facebook-cheating-plagiarism-cambridge-varsity-wikipedia) 31 October 2008

[36] Thomson, I. (2005) “Technology accused of aiding ID theft – Another blow to ID cards”, www.vnunet.com/2141845 .

[37] Kaplan, E., “Terrorists and the internet” (http://www.cfr.org/publication/10005/#2). Updated 8 January 2009.

[38] Harding, T. (2009) “Terrorists launder cash through online gambling” Telegraph.co.uk (www.telegraph.co.uk/scienceandtechnology/technology/4060727)

[39] Statistics from Internet Filter Learning Centre (http://www.internet-filter-review.toptenreviews.com/internet-pornography-statistics.html)

[40] Statistics from Internet Filter Learning Centre (http://www.internet-filter-review.toptenreviews.com/internet-pornography-statistics.html)

[41] “Massive rise in child porn sites” (http://www.guardian.co.uk/technology/2006/feb/26/news.childrensservices) 26 February 2006.

[42] www.internet-filter-review.com

[43] www.divorcewizards.com

Some insights regarding brain function tend to resonate with existing educational attitudes and concepts, and may be helpful in strengthening and consolidating existing practice. Examples of such insights arise from research on

• Brain plasticity. This emphasises the extent to which the structure and function of the brain can respond to environmental influences including education. Such studies tend to emphasise the general importance of educational influence on neurocognitive development, and will always find favour amongst those who feel passionate about the value and promise of education. (eg Immordino-Yang presented two complimentary case studies of boys who had undergone the surgical removal of an entire brain hemisphere (Immordino-Yang, 2007). Both were able to develop language and social skills far beyond expectations, by developing individual processing strategies that exploited the functionality associated with the remaining hemisphere).
• The role of phonological processing skills which includes an understanding of reading processes and reading difficulties. Studies have linked dyslexia to reduced functioning in areas of the brain associated with phonological processing, and have demonstrated that both the reading difficulties and thus reduced functioning are amenable to remediation using approaches that emphasise sound-spelling relationships (Shaywitz et al, 2004). Ongoing research continues to emphasise the importance of modern “phonics” approaches in the classroom.
• Creativity that shows that the inclusion of remotely associated concepts increases activity in brain regions linked to creative effort, supporting the use of such strategies as a means to foster creativity (Howard-Jones et al, 2005).
• Visualisation that shows visualising an object recruits most of the brain areas activated by actually seeing it (Kosslyn, 2005), supporting the use of visualisation as a learning tool.

However, although such neuroscientific studies may play a vital role in consolidating existing educational attitudes in some areas, perhaps the more salient influence of neuroscience in education will arise from more counter-intuitive findings. That is, it may be the educationally-relevant findings about brain function that are more surprising in their content and implications that stimulate the more dramatic changes in educational thinking and practice.

By definition, however, it is difficult to predict surprises. Yet, there are some areas of neuroscience research where results already appear to challenge the types of assumptions teachers work with, and may soon give rise to new directions. These areas will, therefore, now be given particular focus.

Early Numeracy

The acquisition of much formal mathematics relies on our ability to learn rules and procedures. This has been demonstrated by a neuroimaging study involving adults who were asked to calculate answers exactly. Researchers observed increased activity in areas of the brain involved in word association and language activity, the left frontal and angular gyri (Dehaene et al, 1999), as these adults pursued mathematical procedures by following formal mathematical steps that could be linguistically encoded. However, when the same individuals attempted to estimate answers, bilateral activity in the intraparietal sulci was linked to our more ancient and language-independent ability to approximate. Such an ability appears early in development. Even at six months, most of us can approximately differentiate between large numbers of items for ratios of between 1:2 and 2:3 (Starkey and Cooper, 1980) and it seems that we share this approximate number sense with other animals (Boysen and Capaldi, 1993). Such early mathematical ability is likely to have a critical role in ‘bootstrapping’ our capacity to formally grasp exact differences and procedures (credited to Spelke and Carey in Johnson, 2004; see also Carey, 2004), and should provide an improved basis for developing initial mathematical understanding of number and for remediating pupils’ difficulties in achieving this. For example, dyscalculia has been linked to a deficit in our ‘premathematical’ estimation abilities (Butterworth, 2008) and a study of low birth-weight adolescents with numerical difficulties revealed less gray matter in an area of the intra-parietal sulcus (Isaacs et al, 2001). Further research is needed to confirm the direction of cause and effect in such studies, but insights from brain imaging research are contributing to models of mathematical development useful in developing interventions. For example, in one intervention based on these concepts, it was demonstrated that children with dyscalculia showed considerable improvements in a broad range of calculation abilities when basic numerical and conceptual knowledge were focused upon at an early stage of mathematics education (Kaufmann et al, 2003). Dehaene has also used his own findings to develop educational software aimed at remediating dyscalculia. The software is based on the hypothesis that dyscalculia derives from a core deficit in number sense, or in relating number sense to numerical symbols (Wilson et al, 2006)

Another example of the potential influence of neuroscience on mathematics education comes from research into the role of fingers in early mathematical development. Since one might consider mathematics as a cognitive ability, the use of fingers to support calculation can be looked down upon as evidence of mathematical weakness. However, finger gnosis (being able to differentiate between different fingers in response to, say, one or more being touched) has been identified as a strong predictor of mathematical ability (Noel, 2005). Links between finger discrimination and mathematical ability have been studied in both children and adults. A functional Magnetic Resonance Imaging (fMRI) study has shown that, although behavioural outcomes can be the same, the activities produced when fingers are involved in approximating tasks vary with age (Kaufmann et al, 2008), suggesting their contribution varies with development. Eight year-old children produce an increase in activity in the intraprietal sulci when fingers are involved, but not adults. Kaufmann suggests fingers represent concrete embodied tokens involved in the estimation of number magnitude – an intimate involvement with our basic “number sense”. On this basis, children should not be discouraged from using fingers and teachers may be able to exploit their natural role more fully (Kaufmann, 2008). For example, in one intervention based on such ideas, new arrivals at three Belgian schools were identified as having poor finger gnosis and some of them received two-weekly 30 minute sessions of finger training for eight weeks (Gracia-Bafalluy and Noel, 2008). After training, these children were significantly better at quantification tasks than those who had not received the training.

Research on the relationship between our “animal number sense” and the early learning of mathematical concepts has only just begun. However, the concepts emerging are sufficiently well established and different to previous ideas of mathematical development to suggest the potential for improved educational practice in primary school classrooms in the next 1-2 decades.

Adolescence

It may be natural to consider that a teenager is essentially a young adult, with a fully formed brain but lacking the social experiences of his/her elders. However, scientific investigation has revealed a very different picture, with frontal and parietal regions still undergoing radical structural changes until the late teens, relative to other areas of the brain which appear more fully developed. Synaptic pruning (the cutting back of neural connections) and myelination (improving the efficiency of neural connections) also continue throughout adolescence (Sowell et al, 2003) in frontal regions. Such change in specific regions suggests the teenage brain may be less ready than an adult brain to carry out a range of specific processes, including directing attention, planning future tasks, inhibiting inappropriate behaviour, multitasking, and a variety of socially-orientated tasks. Although more research is needed, some psychological research backs this up, even showing a “pubertal dip” in some areas of performance, such as matching pictures of facial expressions to descriptors. In this task, 11-12 year olds perform worse than younger children (McGivern et al, 2002). Discontinuities have also been shown in abilities underlying social communication, such as taking on the viewpoint of another person, or so-called ‘perspective-taking’ (Blakemore and Choudhury, 2006; Choudhury et al, 2006). Some parts of what might be described as a “social brain” network are also activated differently in teenagers compared with adults when thinking about intentions (Catherine et al, 2008) and brain regions responsible for the control of impulses appear less well functionally connected in adolescents’ than in adults’ brains (Steven et al, 2007). Teenagers also appear to activate different areas of the brain from adults when learning algebraic equations, with this difference associated with a more robust process of long-term storage than that used by adults (Luna, 2004; Qin et al, 2004). Adolescents, then, are not simply older children or younger adults, and cognitive development cannot be expected to proceed in a continuous linear manner. Apart from explaining some of the difficulties teenagers experience, such changes also suggest how and why adolescence can be a potentially sensitive period for learning, within and beyond academic contexts. For example, teenagers often tend to perceive risks as smaller and more controllable than adults, and they are generally more vulnerable than adults or children to a range of activities which are inappropriately risky, such as gambling and drug taking. Appropriate decision making appears to require a balanced engagement between harm-avoidance and reward orientating processes that is regulated by processes within the prefrontal cortex, where teenage development may lag (Ernst et al, 2005). Imaging studies comparing adults and adolescents show reduced activity in these prefrontal areas when making risk-based decisions (Bjork et al, 2007; Eshel et al, 2007), and this reduced activity correlates with greater risk-taking performance (Eshel et al, 2007). Such studies provide new insights into how adolescent risk taking may be linked to neuro-maturational events and these insights may influence educational perspectives on teenage behaviour, helping to understand a potentially problematic, and sometimes even dangerous, period of children’s development (Baird et al, 2005).

It seems likely that these and future findings from neuroscience may generate new educational approaches in future years (eg strategies that take a more informed account of the temporary lagging of cognitive function in some areas). Findings on the adolescent brain are potentially illuminating and should stimulate educational changes, although the rate at which these will occur is difficult to predict. Paus believes that “the time is right for evidence-based, large-scale studies of interventions aimed at facilitating youth development. Neuroimaging-based approaches hold considerable promise, providing both the evidence as well as novel insights about the role of the environment in shaping the adolescent brain” (Paus, 2008). However, do such beliefs reflect an awareness of the considerable ethical, social and political issues that would be involved with such studies? Neuroimaging studies of interventions aimed at remediation of difficulties associated with dyslexia have already been carried out, but remediation of character (one of the five “c”s of positive youth development (Lerner, 2005)) would take neuroethical dilemmas to a new level.

Motivation

A burgeoning number of findings from neuroscience has supported some fresh educational thinking about motivation, including the type of intense engagement provided by computer gaming (Gee, 2003). Previous explanations of gaming motivation involve issues of fantasy, challenge and curiosity (Malone, 1981) but these appear inadequate in explaining the attraction of some traditional games such as “snakes and ladders” and “bingo”, or simple (but popular) computer games such as Tetris. This attraction may be due more to elements of chance-based uncertainty. The attraction of uncertainty is now gaining closer neuroscientific investigation, but it is a phenomenon well established by psychological experimentation (Atkinson, 1957) which has shown moderate risk taking (50% chance) heightens motivation.

Recent neuropsychological understanding of reward involves consideration of ‘wanting’ and ‘liking’ as two dissociable components, with the wanting of a reward being coded by levels of dopamine release in mid brain areas (Berridge and Robinson, 2003). The predictability of an outcome has been shown to influence this activity. In primates, it has been shown that maximum dopamine is released when the likelihood of receiving reward for success is about half way between totally unexpected and completely predictable, ie 50% likely (Fiorillo et al, 2003). Dopamine levels in this area of the human brain have been linked to our motivation to pursue a variety of pleasures, including sex, food, gambling (Elliot et al, 2000) and computer gaming (Koepp et al, 1988). The link between the predictability of an outcome and mid-brain dopamine activity is, therefore, helpful in explaining why humans are so attracted to activities involving elements of chance (Shizgal and Arvanitogiannis, 2003). Activity in this area has been studied non-invasively in humans during gaming using fMRI. These fMRI studies have shown that patterns of dopamine activity are predicted less by reward in ‘real’ absolute terms and seem more to do with winning the particular game being played. Activity can increase with reward size (Knutson et al, 2001) but, rather than being proportional to absolute monetary reward, activation peaks at the same level for the best available outcome in different games (Nieuwenhuis et al, 2005). The complex relationship between reward and motivation is thus strongly mediated by context.

When uncertainty is encountered in more real world instances, there are potentially more complex effects of context created by the social environment. These are illustrated by the way our natural attraction to uncertainty falls off when the task is perceived as educational. Students generally prefer low levels of academic uncertainty and choose problems well below moderate (<50%) challenge (Clifford, 1988; Harter, 1978) unless these are presented as games, when students will take greater risks (Clifford and Chou, 1991). This may suggest that individuals can be deterred from tackling academic tasks with higher levels of uncertainty due to the implications of failure for social status and esteem. In research involving classroom-based applications, these concepts provide a means to understand how learning games with elements of pure chance can increase uncertainty without impacting negatively on self-esteem, thereby raising motivation (Howard-Jones and Demetriou, in press – now published on-line). Neurocomputational modelling is now providing the tools to study the reward system in more detail (Elliott and Deakin, 2008).These techniques allow estimation of how dopaminergic activity in the reward system varies with the progress of a game. Such activity also mediates attention in the short term, and these models can predict when declarative learning (the type of greatest interest to educators) will occur during an educational game (Howard-Jones et al, 2009).

Neuroscience is providing concepts that are proving useful in understanding learning games and motivation in the classroom, particularly amongst males (Hoeft et al, 2008). However, introducing chance-based uncertainty into learning can conflict with the principle of reward consistency that is traditionally valued by education (OfSTED., 2001). Our increasing understanding of this region of the brain has, therefore, the potential to prompt a significant departure from present educational thinking.

Early screening for some developmental disorders

Event-Related Potentials (ERPs) refer to a set of distinct electrical signals emitted by the brain and detectable using a non-invasive technique involving the attachment of electrodes to the scalp. Some ERP waveforms of newborn infants have been identified that can differentiate between children who will later, at eight years old, be poor readers or be dyslexic (Molfese, 2000). Measurement of ERPs has been shown as an effective method of predicting dyslexia in new-borns with and without a family history of dyslexia (Guttorm et al DATE) and such techniques could form the basis of very early screening, so that children at risk of dyslexia are able to benefit as quickly as possible from suitable intervention(s). See also discussion by Friedrich of neural markers and specific language impairment (Friedrich, 2008). Such techniques and possibilities are not limited to literacy. Another type of ERP has been identified that is sensitive to children’s response to numerical distance (Szucs et al, 2007) that may be a helpful neural marker for magnitude processing in infancy. This signal may provide an early indicator of later educational risk in respect of mathematics.

The use of neural markers to provide very early detection of educational risk is an area identified by Goswami where a neuroscience approach may provide particular promise for education (Goswami, 2008).

Cognition and the Brain in the Curriculum: Curriculum Aims and Content

i) The influence of research on cognitive training (‘Brain training’)

There is increasing evidence to show that the cognitive training can reduce risk of Alzheimers (Wilson et al, 2002) and in normally functioning older adults. A 5-year study has shown that training can provide sustained improvements in a range of cognitive functions in this age group (Ball et al, 2002).

A study by Willis et al (2006) showed sustained improvements in targeted function over five years, following an intervention that consisted of only 10 sessions of about 60-75 minutes each. Positive effects were also been observed on daily functioning (phone, laundry, cooking etc) (Willis et al, 2006).

There is thus good evidence to show that brain function can be trained, in the sense that repeated practice on exercises that focus on a cognitive function, can produce improvement in that cognitive function. There is less evidence confirming impact on everyday functioning not specifically targeted by the training. As research continues, however, such evidence is emerging (Mahncke et al, 2006; Willis et al, 2006) and we are understanding more about the impact of training cognitive function on other, non-targeted areas. Most notably, it has been convincingly shown that fluid intelligence, which is seen as a good predictor of professional and academic achievement, can be improved by rehearsing working memory exercises, specifically an exercise based on the N-back test (Jaeggi et al, 2008). Unlike most other studies which have been undertaken with older participants including those at risk of dementia, the average age of the participants in this study was 25, demonstrating the relevance of this type of cognitive training to the younger population.

In terms of developing cognitive function amongst children, it is the targeting of WM, together with the closely allied concept of attention that has again produced the most interesting results. In a study involving children with ADHD, training of WM was found to successfully transfer to non-targeted areas of behaviour, producing improved complex reasoning skills and reduced parental ratings of ADHD symptoms (Klingberg et al, 2005). Training of visual and auditory attention has been found to benefit literacy achievement for children with dyslexia (Chenault et al, 2004), and a study using ERPs with children with specific language impairment (SLI) showed that neural mechanisms of selective auditory attention and the associated language difficulties can be remediated through auditory attention training (Stevens et al, 2008).

The research from science converges with other forces encouraging educators to move further away from content towards thinking skills and, more specifically, the training of cognitive function. Advances in technology are likely to continue improving our access to information, with some commentators believing this will increase the need for specialisation as it increasingly places “any human knowledge at the fingertips of any human” (Stewart, 2008). Such advances may, therefore, make it desirable for learners to be better at manipulating information than encoding and recalling it, with demand for specialisation making it more difficult to predict and include the type of content that an individual may benefit from in the initial stages of their education. These factors may combine with a burgeoning dialogue with neuroscience that also encourages greater emphasis upon cognitive function generally within education – since cognitive function is a central construct of cognitive neuroscience – and some way towards a redefinition of the aims of education as an attempt to “nurture” the brain and its processes. Increasing interest in the training of cognitive function as a means to enhance learning potential is also reflected in current public interest in “brain training” products, although it should be noted that no quality research exists that evaluates the claims made by the manufacturers of these products, or even the design principles upon which they are based. This public enthusiasm with the commercial products has already begun to extend itself to some schools.

ii) Teaching about the brain

There has also been a broader interest in the development of children’s cognitive function, in ways that include emotional aspects of behaviour. These include the development of “Executive Function” (EF) – an umbrella term referring to the underlying processes responsible for children’s ability to direct, maintain and focus their attention, manage impulses, self-regulate behaviour and emotion, plan ahead and demonstrate flexible approaches to problem solving. EF skills are predictive of academic achievement (Bull et al, 2008), and social and emotional development (Hughes, 1998). For this reason, attempts have been made to find ways of developing EF skills and some interventions in schools have reported positive results in terms of improved behaviour (Greenberg, 2006).

Unlike simple cognitive training, such programmes require learners to understand and reflect upon their behaviour in terms of a set of mental processes. They are thus delivering an explicit, if sometimes ill-defined, psychological content into the curriculum of many schools. These programmes are becoming associated with protecting the mental health of children as well as improving academic standards and behaviour. They have been explicitly linked to neuroscience by some experts (Greenberg, 2006), although (in the opinion of the author) such links would benefit from further scientific scrutiny and consensus. What does appear clear, however, is that the school-based curriculum education is becoming influenced by attempts to directly attend to the development of executive function, in order to promote emotional well-being, mental health and academic achievement. It has been known for some time that the level of education can influence mental health in later life, but there are now growing voices for educators to become actively involved in fostering the mental health of their learners. A 2005 policy paper produced by the Sainsbury foundation (together with the NHS confederation) predicts “By 2015, mental wellbeing should be a major concern for schools, from dedicated classroom time to the overall approach of the school towards its pupils and staff” (SCMH, 2005, p13.

It can also be predicted that advances in neuroscientific understanding may broaden the aims of education further still, thereby influencing the curriculum and the ways in which it is delivered. For example, rising levels of obesity amongst children has drawn new attention to the importance of exercise in schools, but this may gain further emphasis as neuroscientific understanding emerges about the processes by which exercise is linked to learning (Hillman et al, 2008). Understanding the processes by which even short bouts of exercise improve subsequent learning (Winter et al, 2007) makes it foreseeable that regular exercise breaks during the school day will become more popular as a means of raising academic standards and fostering mental and physical health. Although it is certainly not a good example of science, evidence for the likelihood of such developments arises from the popularity of Brain Gym. The principles of Brain Gym are unscientific and bizarre (Hyatt, 2007), but its popularity in the face of unfavourable media exposure must surely derive, in part, from its associations with academic achievement and neuroscience. Such associations, in the case of Brain Gym, do not withstand scrutiny, especially in terms of neuroscience, but it is likely that the authentic value of exercise in learning will become well understood by educators in future years. It can be predicted that, by 2025, neuroscience will have contributed to developing scientifically sound and educationally evaluated methods of incorporating frequent exercise breaks into the school day and these will have become established in most schools.

Part of the success of introducing such elements into the curriculum will depend on ensuring learner motivation, and this may depend on learners understanding something of neurocognitive function. Such understanding may have other benefits. It has been reported that providing learners with a basic knowledge of the brain can, by itself, provide significant help in improving self-image and academic achievement (Blackwell et al, 2007). In this study with adolescents, researchers informed learners about the structure and function of their brain, how learning changes the brain by producing new neuronal connections and about brain plasticity, and provided the clear message that the pupils themselves were in charge of this process. This promoted a positive change in classroom motivation. Grades for the control group, who had not received the intervention, continued downward while this trend was reversed for the intervention group.

Neuroscience-related issues arriving without invitation

The potential changes so far discussed are expected come about through initiatives involving educators, and their final form is likely to be mediated by educational understanding, sensitivities and opinions. Some influences involving neuroscience, however, may arrive without invitation.

One such issue is the use of cognitive enhancers. In the US, students are increasingly using prescription drugs in order to provide cognitive enhancement and thereby support their studies. Usage varies widely from one university to the next, with an average figure of 6.9% of students indulging in non-medical use of prescription stimulants (McCabe et al, 2005). In another study, however, that surveyed 1811 students at a large Southeastern US university, 34% reported the illegal use of ADHD stimulants (eg methylphenidate), mostly to improve their cognitive function during periods of fatigue and stress (DeSantis et al, 2008).

The production of new and stronger drugs for cognitive enhancement is likely to increase, driven partly by efforts to combat the effects of Alzheimer’s disease. One such drug is donepezil (marketed as Aricept) that increases levels of acetylcholine (ACh). ACh is thought to modulate the rate at which neural connections adjust themselves when learning, with increases in ACh thus able to bring about increases in learning rate. Donepezil reduces cholinesterase that mops up ACh, thereby increasing levels of ACh and improving cognitive function, including memory, amongst those suffering from Alzheimers (Roman and Rogers, 2004). The potential value of this drug for other users was demonstrated in a study that administered donepezil to healthy young adults for only 30 days, and revealed significant improvements in episodic memory performance (Gron et al, 2005).

Scientists have been speaking out in positive terms about the “new enhancement landscape” for healthy adults (Gazzaniga, 2005). In a recent article in Nature, one group of scientists suggested that the growing demand for cognitive enhancement should be responded to, and that the response should begin by “rejecting the idea that enhancement is a dirty word.”(Greely et al, 2008) However, a modest UK consultation showed more ambivalence (Horn, 2008), with concerns raised that included

• possible side and long term effects including personality change
• the devaluation of ‘normal’ achievement and the intrinsic value of effort and motivation in learning
• inequality if such drugs are expensive
• pressure to use such drugs and the exacerbation of an already over-competitive culture.

It seems likely that the use of cognitive enhancers amongst the general UK population will increase as public sensitivity diminishes and the drugs become more socially acceptable. This will stimulate significant ethical debate amongst educators. Some educational institutions may, with parental permission, choose to introduce drug testing. Since there are few clear precedents for the issues involved with these drugs (it is debatable whether a comparison with the use of drugs in sport is helpful) there may, for some time, exist a diverse range of attitudes and practices amongst learners and educational institutions in respect of cognitive enhancers. This may impede the development of any necessary legislation.

The influence of neuroscience on educational professional development

Psychology returns, accompanied by some neuroscience, to initial teacher training

Our burgeoning understanding of the human brain and mind, particularly in regard to the issues raised above, will increase the likelihood of some elements of psychology returning to initial teacher training. When teachers consider learning processes, they consider mental rather than neural processes, although in the future we can expect constructions about these mental processes to be increasingly informed by neurobiological understanding. Neuroscience, in itself, remains largely meaningless in educational terms, except insofar as it informs our psychological concepts about the learner’s mind. However, neuroscientific concepts are helpful in formulating and communicating educationally-relevant concepts about the mind (Howard-Jones, 2008).

The emergence of neuro-educational research and new types of educational professional

Although appearing under many different names (eg educational neuroscience, neuroeducational research, neuroscience and education) a field of research at the interface between neuroscience and education is becoming established. This provides some support for the prediction made by some that, in the future, hybrid professionals will emerge with expertise in both neuroscience and education (Pickering and Howard-Jones, 2007; Szucs and Goswami, 2007).

Developments that may occur in the future, but not by 2025

Genetic profiling in mainstream education

The area where genetic knowledge is first likely to impact, and appears likely to do so before 2025, is in the area of learning difficulties. Gene-based diagnoses of learning difficulties will be able to predict general learning difficulty as well as difficulties within specific areas such as maths (Plomin, 2008). Such very early predictions, combined with emerging educational understanding of effective interventions, will provide the soonest possible implementation of appropriate interventions. Genetic knowledge will provide opportunities for new levels of personalised learning and these should ameliorate or even prevent the manifestation of some learning difficulties.

Ultimately, genetic knowledge should allow educational programmes to be better tailored to suit all individuals according to their genetically-informed educational profiles. It has been suggested that, in the future, “Educogeneticists” will be able to provide informed recommendations to schools and families about how a child’s education may be planned in order to optimise academic outcomes (Grigorenko, 2007). Genetics may, therefore, be considered to have considerable educational potential beyond the early identification and amelioration of learning difficulties. This wider application, however, will only add further controversy to a plethora of ethical issues and questions about using genetic knowledge in education: what may result when genetic testing proceeds without full understanding of the educational intervention that may be needed? Who makes the decisions about testing and interventions, and by what processes? What precautions are needed to prevent this new educational opportunity feeding demand for genetic engineering and eugenics?

Since biotechnology companies are now marketing genetic tests directly to the public, it is possible that this issue may arrive without educational invitation by 2025, as with cognitive enhancers. One can imagine that, by 2025, all parents will have the opportunity to independently purchase a genetic profile of their child and ask what their school intends to do about it. However, whilst the educational application of smart pills requires only that a bottle is opened and a pill consumed, there remains much educational (or “edu-genetic”) research necessary in order to utilise genetic knowledge in mainstream education. This knowledge gap and the ethical issues mentioned above will provide some barrier to progress. Due to the potential benefits to individual learners, public attitudes are likely to become increasingly positive and demands for edugenetic approaches will grow, but it seems unlikely that schools will develop established approaches to genetically-based differentiation of mainstream teaching and learning by 2025.

Brain-Computer interfaces (BCIs) in mainstream education and ‘brain reading’

Brain-computer interfaces have developed the potential to provide valuable aid to some profoundly disabled individuals. For example, severely paralysed patients can control prosthetic limbs and computer cursors by thought alone. Non-invasive approaches often adapt the type of technology used by ERP and EEG measurements, using a patient’s electrical brain activity sensed by electrodes placed on the scalp. The EEG/ERP signal is analysed and interpreted automatically by a computer, which then produces an appropriate output. In this way, the user can generate some rudimentary signal to the outside world by producing the pre-defined type of thought that the computer is programmed to decode. For example, by imagining different body motions (eg left versus right hand), the user can generate different EEG signals that can be translated by the computer into responses to binary (yes/no) questions with high, but not perfect, accuracy (Neuper et al, 2006). As illustrated in this example, there are presently significant limitations upon the amount of information such BCI interfaces can communicate. These limitations arise from the noisiness of the signal and the variability of the signals produced by different individuals. Improvements in technology alone may not be sufficient to overcome these limitations, since significant advances may require greater neurobiological and psychological understanding of the signals themselves.

At present then, although the usefulness of non-invasive BCIs for the profoundly disabled may be possible in the next 1-2 decades, the likelihood of the wider population using them to communicate with everyday technology is something for the very far distant future when both our technology and, perhaps more importantly, our understanding of brain function is unimaginably superior than at present.

Similar issues limiting the advances in BCI’s over coming years will also apply to ‘brain reading’. Some experiments have shown that imaging technology can reveal socially sensitive and relevant information, such as racial group identity and unconscious racial attitudes. For example, white subjects with more negative evaluations of black faces showed increased amygdalic activity in response to unfamiliar black, compared with white, faces. There has also been some success in identifying the correlates of deception (Nunez et al, 2005) and such knowledge may be applied in counter-terrorism efforts in the future. Such examples, however, tend to compare a very small set of conditions, and results could only be used to differentiate between a correspondingly small set of possible alternatives regarding mental content (eg truth/lies). As with the notion of using a BCI to access one’s computer in an everyday sense, the possibility of reading the everyday contents of a learner’s mind will be science fiction until well beyond 2025. As Farah suggests (p1126) in relation to brain-reading, “even a major leap in the signal-to-noise ratio of functional brain imaging would leave us with gigabytes of more accurate physiological data whose psychological meaning would be obscure.” (Farah, 2002)

Improbable educational advances involving neuroscience

There are considerable differences between the views of educators and scientists about how neuroscience is relevant to education, although consensus is emerging in both areas that the relevance exists. Perhaps unsurprisingly, educators associate neuroscience chiefly with those brain-based concepts already commonly found in schools (Pickering and Howard-Jones, 2007). Unfortunately, these concepts are often not well supported by existing science, yet educational expectations of how neuroscience may influence education in the future are likely to be strongly influenced by these neuromyths. This was illustrated in 2000 when scientists Uta Frith and colleague Sarah-Jayne Blakemore were commissioned by the Teaching and Learning Research Programme (TLRP) to carry out a review of neuroscientific findings that may be of relevance to educators (Blakemore and Frith, 2000). This review attacked a number of unscientific myths and highlighted some scientific areas of potential interest to educators. In January 2001, to promote further discussion about a possible research agenda, the TLRP wrote to scientific and educational institutions, asking for comments on the report by Blakemore and Frith. Respondents were particularly asked to provide “identification of key research questions, … their priority … and estimate of their tractability (in terms of return on research effort)”. While scientists indicated areas such as learning disorders, memory and plasticity, educational respondents identified areas such as multiple intelligences and learning styles, which are problematic as robust and well-defined scientific concepts suitable for orientating neurocognitive research. The report on the consultation concluded that no collaborative research agenda had yet emerged (Des Forges, 2001).

Indeed, perhaps the most immediate benefit of the increased dialogue between neuroscience and education has been to highlight the large number of neuromyths that have developed within education. Some of the most prominent will now be listed below, none of which are likely to receive support from neuroscience in the coming years and should become less prominent by 2025, despite the hopes of many educators.

Multiple Intelligences (MI) Theory

Gardner’s MI theory proposed that, rather than a single all-purpose intelligence, it is more useful to describe an individual as possessing a small number of relatively independent intelligences (Gardner, 1983). Possible candidates for these intelligences include linguistic, musical, logical-mathematical, spatial, bodily-kinaesthetic, intrapersonal sense of self, interpersonal and Gardner has later proposed other possibilities such as naturalistic and existential intelligence (Gardner, 1999). MI theory is in direct opposition to the idea of a unitary general intelligence factor ‘g’, reflecting overall brain efficiency and the close interconnection of our mental skills. MI theory resonates with many educators, who see it as a robust argument against IQ-based education.

In a critical review of the evidence for MI theory, Waterhouse examined the empirical scientific evidence (Waterhouse, 2006). MI theory claims to be drawn from a wide range of disciplines including neuroscience. Indeed, Gardner has claimed “accumulating neurological evidence is amazingly supportive of the general thrust of MI theory”. However, Waterhouse points out that the general processing complexity of the brain makes it unlikely that anything resembling MI theory will ever emerge from neuroscience. Cognitive neuroscience is exploring the brain in terms of processes (vision, hearing, smell, etc) but not in terms of seeing intelligence, auditory intelligence or smelling intelligence. In the realm of neuroscience, it neither appears accurate or useful to reduce the vast range of complex individual differences at neural and cognitive levels to any limited number of capabilities.

Despite the absence of MI theory in the neuroscience literature, teachers heavily associate MI theory with neuroscience. (To confirm this, the author returned to the data collected from the 150 UK teachers who were asked the question “Please list any ideas that you have heard of in which the brain is linked to education” (Pickering and Howard-Jones, 2007). Of those teachers who responded to this question (121), most listed no more than 2-3 ideas. Of these, MI theory occurred 17 times (14%)).

Thus, in educational terms, MI theory appears like a liberator – providing teachers with the ’scientific’ license to celebrate diversity. In terms of the science, however, it seems an unhelpful simplification as no clearly delineated, limited set of capabilities arises from either the biological or psychological research.

Learning Styles

In educational terms, an individual’s learning style can be considered as a set of learner characteristics that influence their response to different teaching approaches. A survey in 2004 identified 71 different models of learning styles (Coffield et al, 2004) and our own survey showed almost a third of UK teachers had heard of learning styles, with most of those who used this approach reporting it as effective (Pickering and Howard-Jones, 2007). As with MI theory, which is also often interpreted by educators as a means to identify preferred modes of learning, the promotion of learning styles has benefited from a strong association with neuroscience. Many learning style models have a distinctly biological justification, with one of their major proponents, Rita Dunn, commenting that “at least three fifths of style is biologically imposed” (Dunn et al, 1990).

Very many educational projects have pursued improvement through tailoring programmes to meet individual learning styles but, as yet, there is no convincing evidence that any benefit arises. A review of such studies, concluded that matching instruction to meet an individual’s sensory strengths appears no more effective than designing content-appropriate forms of education and instruction (Coffield et al, 2004). Perhaps the best known inventory of learning styles within education is the one categorising individuals in terms of their preferred sense modality for receiving, processing and communicating information: visual, auditory or kinaesthetic (VAK). In a laboratory study of memory performance, participants’ own self assessment of their VAK learning style was shown to be out of line with more objective measures, and memory scores in different modalities appeared unrelated to any measure of dominant learning style (Kratzig and Arbuthnott, 2006). There was, instead, evidence that participants’ self-rating as kinaesthetic learners was related to visual performance, that they were self-rating their learning styles in ways possibly promoted by the inventory itself, and objective evidence from memory testing that suggested visual and kinaesthetic/tactile tasks were tapping the same underlying memory process. The authors concluded that educators’ attempts to focus on learning styles were “wasted effort”.

In approaches such as VAK, the implicit assumption appears to be that, since different modalities are processed independently in different parts of the brain, differences in the efficiency of these parts results in a clear modality-based method of classifying how learners are able to process information most efficiently. However, as pointed out by Geake, this flies in the face of what we know about the interconnectivity of the brain(Geake, 2008). Geake refers to a recent piece of experimental research in which five year olds showed themselves able to distinguish between groups of dots even when the numbers were too large for counting (Gilmore et al, 2007). They were then asked to repeat the task in auditory mode by counting clicks, and reproduced almost identical levels of accuracy. Geake points out that this is because input modalities in the brain are very interlinked. As yet, no evidence arising from neuroscience, or any other science, supports the educational usefulness of categorising learners in terms of their sensory modality or any other type of learning style. In the meantime, educators continue to be drawn to VAK as means to implement a type of differentiation between learners.

Learning styles based on these ideas are likely to diminish in their popularity as awareness grows of their ineffectiveness and lack of scientific basis. By 2025, one can be hopeful that differentiation of learners may be informed by a better understanding of the development of literacy, mathematical and other skills, and this understanding will undoubtedly be informed by insights from cognitive neuroscience. More speculatively, it is also possible in the more distant future (but not by 2025 – see above) of genetically-informed profiling of individual learners.

Left-Brain Right Brain

Another popular way of categorising learning style is in terms of “left-brain right-brain” theory(Springer and Deutsch, 1989). According to this theory, learners’ dispositions arise from the extent to which they are left or right brain dominant. It is true that some tasks can be associated with extra activity that is predominantly in one hemisphere or the other. For example, language is considered to be left lateralised. However, no part of the brain is ever normally inactive in the sense that no blood flow is occurring. Furthermore, performance in most everyday tasks, including learning tasks, requires both hemispheres to work together in a sophisticated parallel fashion. The division of people into left-brained and right-brained takes the misunderstanding one stage further. There is no reliable evidence that such categorisation is helpful for teaching and learning.

Educational Kinesiology (Brain Gym)

Educational kinesiology (or Edu-K, also often sold under the brand name of Brain Gym) was developed by Paul and Gail Dennison as a means to ‘balance’ the hemispheres of the brain so they work in an integrated fashion and thus improve learning (Dennison, 1981). Whatever the flaws in its theoretical basis (which are many and fatal), there is a lack of published research in high quality journals to make claims about the practical effectiveness of programmes such as Brain Gym to raise achievement. Of the studies published elsewhere, the lack of information about the exercises undertaken and/or the insufficient or inappropriate analysis of the results undermine their credibility (Hyatt, 2007). However, it may also be that programmes such as Brain Gym are contributing to learning, but for entirely different reasons than those used to promote them. As discussed above, there is an emerging body of multidisciplinary research supporting the beneficial effect of aerobic exercise on selective aspects of brain function of importance to education (Hillman et al, 2008). However, these advantages appear linked to the aerobic nature of the exercise, which is low in Brain Gym.

Implicit learning

Work with artificial grammars, in which participants are able to acquire grammatical rules by observing examples of artificial language, demonstrates our ability to learn implicitly, ie without being able to report explicitly what has been learnt. Such experiments have contributed to enthusiastic calls for more educational focus on implicit learning (Claxton, 1998). However, there are considerable barriers to the practical application of such ideas, making their usefulness to education questionable and causing some scientific authorities to label them a new source of neuromyth (Goswami, 2004). A non-specialist interpretation of the phenomenon of implicit learning might involve ideas about absorbing information and concepts from the environment without attending to them, but such ideas have no scientific basis. For example, in the artificial grammar scenario, formal rules may be acquired without the learner consciously formulating them, but the learner must pay considerable attention to the examples of artificial language in order to facilitate this. In a more real world context, we may also implicitly develop understanding about, for example, the motivations of people around us, without being able to articulate how we have achieved this. Again, however, this is only possible by paying attention to the behaviour of those people. “Implicit learning” does not equate to “learning without attention”, and it seems unlikely that such concepts will become usefully applied in education in the coming years.

A brain-based science of learning?

Although researchers at the interface of neuroscience and education have done much to counter the neuromyths prevailing in schools, they may also be guilty of inadvertently creating one. There has been much enthusiasm amongst policy makers for the creation of a “new” science of learning (OECD, 2002; OECD, 2007). This may be because neuroscience seems a more secure basis for learning theory, with its images of blood flow appearing more concrete than abstract psychological concepts. Indeed, it has been experimentally determined that including references to the brain (even irrelevant ones) increases the satisfaction of a reader (Weisberg et al, 2008). However, as with social and experiential perspectives on learning, the biological perspective is, on its own, limited in terms of what it can tell us. A science of teaching and learning which is chiefly based upon the brain is unlikely to develop in the foreseeable future, because neuroscientific perspectives struggle with many concepts (such as meaning and autonomy) that are central to educational aims and understanding (Howard-Jones, in press). On the other hand, this brief review has emphasised that greater inclusion of biological perspectives in educational thinking, alongside other perspectives, is increasingly desirable and probable.

Summary

It is anticipated that the following educational developments involving neuroscience may arrive by 2025:

• New educational approaches will become established for the teaching and learning of mathematics in the early years, as a result of insights from cognitive neuroscience.
• Adolescents will become recognised as a more distinct group of learners and educational approaches will be developed that are better tailored to meet their social, emotional and educational needs
• A new understanding of motivation will be developed and new approaches to engaging learners will become established (eg in areas involving the use of games) informed by insights into the brain’s reward system
• Early screening will be available for a range of learning disorders, using neural markers and genetic testing.
• Attendance to the training of some targeted cognitive functions, including working memory, will feature across year groups in the National Curriculum
• The reflective understanding and development of executive function will feature in the National Curriculum for young learners
• Understanding of mental health issues will become a stronger feature of the curriculum, as the aims of education become broader. This will include a basic understanding of brain function, with the associated academic benefits that such an understanding may bring.
• Exercise breaks will become a feature of the curriculum, as the link between exercise and academic achievement becomes clearer, and the UK struggles with increasing levels of obesity.
• The use of drugs to enhance cognitive function will become commonplace, remaining chiefly unchecked by legislation as the government remains unwilling to intervene in the absence of clear public consensus. The attitudes and practices amongst different groups of learners and educational institutions will diverge.
• Psychology, and some neuroscience, will become an established feature of teachers’ professional development and training.

• There will be no brain-based science of learning that is meaningful in educational terms, but a new field of neuro-educational research will become established, together with the development of professionals trained in both education and the relevant natural sciences (eg cognitive neuroscience, genetics). Biological perspectives will become an increasingly important component of educational understanding, practice and policy making.

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Commonly used abbreviations :

fMRI – functional Magnetic Resonance Imaging (fMRI)

OfSTED – Office for Standards in Education, Children’s Services and Skills

ERP – Event Related Potential

EEG – Electroencephalogram

ADHD – Attention Deficit Hyperactivity Disorder

WM – Working Memory

EF – Executive Function

SLI – Specific Language Impairment

ACh – Acetylcholine

BCI – Brain Computer Interface

MI – Multiple Intelligences theory

VAK – Visual Auditory Kinaesthetic

SCMH – The Sainsbury Centre for Mental Health

Note that reward is being used here in the psychological sense, i.e. as a process, or set of processes, by which behaviour is reinforced.

In the type of N-back task used in this research, participants are asked to observe a sequence of digits or letters, and asked to recall the item that was N items back

Memory processes will, however, still remain of key importance in education although semantic memory (for knowing “how to”) may increase its significance relative to declarative memory (explicit recall of facts and events)

An extreme view of this redefinition has been provided by Koizumi: “… education should be designed to guide and inspire the construction of the basic architecture for information processing in the brain by preparing and controlling the input stimuli given to the learners.” Koizumi, H. (2004) The Concept of ‘Developing the Brain’: A New Science for Learning and Education, Brain and Development, 26, 434-41. p435.

For example: http://www.ltscotland.org.uk/ictineducation/gamesbasedlearning/sharingpractice/braintraining/introduction.asp

WM is usually considered one component of EF

Programmes through the curriculum can promote mental health … important characteristics of such programmes include those that enable children to correctly identify and regulate one’s feelings…” DfEE. (2001) “Promoting Children’s Mental Health within Early Years and School Settings.” (Nottingham, Department for Education and Employment), p10

Invasive BCIs involve the implantation of electrodes, produce cleaner signals and perform a little better, but clearly these are not likely to become acceptable amongst those who suffer no serious disability and so these devices are not considered here.

This document has been commissioned as part of the UK Department for Children, Schools and Families’ Beyond Current Horizons project, led by Futurelab. The views expressed do not represent the policy of any Government or organisation.

In recent decades, many OECD member countries have undergone a transformation from an industrial to a knowledge economy (Bell, 1973; Drucker, 1993). The knowledge economy is based on “the production and distribution of knowledge and information, rather than the production and distribution of things” (Drucker, 1993, p182). Knowledge workers manipulate symbols rather than machines, and create conceptual artifacts rather than physical objects (Bereiter, 2002; Drucker, 1993; Reich, 1991). These analysts emphasize the importance of creativity, innovation, and ingenuity in the knowledge economy; some scholars now refer to today’s economy as a creative economy (Florida, 2002; Howkins, 2001).

We are entering an age of innovation, and creativity will grow in importance due to several broad societal and economic trends:

1. Increasingly globalized markets result in greater competitiveness, even for industries that historically had been protected from significant challenge

2. Increasingly sophisticated information and communication technologies result in shorter product development cycles, increasing the pace of innovation and change

3. Increasingly sophisticated information technology is spreading the scope of automation into sectors of the economy that formerly required active human involvement, including increasingly advanced service and knowledge work, thus obsoleting those job categories that do not involve active, daily creativity

4. Global labor market competition has resulted in low-skill, low-creativity jobs moving to extremely low-wage countries such that OECD labor forces can no longer compete

5. Increasing wealth and leisure time in OECD countries (and beyond) have increased the demand for the products of the creative industries. As of 2007, the creative industries represented over 11% of U.S. GDP (Gantchev, 2007).

These trends result in regional, economic, and organizational shifts – such as flexible specialization, regional economies structured around a loose network of small producers, and short product runs – that place creativity at a premium (Jeffcutt and Pratt, 2002, p. 226).

An economic school of thought known as new growth theory argues that creativity and idea generation are central to today’s economy; the driver of economic growth is technological change (Cortright, 2001; Lucas, 1988; Romer, 1990; Solow, 1956, 1994). In this view, knowledge is an intrinsic part of the economic system – a third factor, added to the traditional two of labor and capital (Florida, 2002; Romer, 1990). Peters and Humes (2003) noted that “economic progress and expansion has always depended on new ideas and innovation … What has changed, perhaps, is that knowledge is now recognized as being at least as important as capital (physical and financial)” (p1). New growth theory implies that those nations that thrive will be the ones that succeed at innovation – generating and applying new knowledge.

The creative industries have been defined by the UK Department of Culture, Media, and Sport (DCMS) as “those activities which have their origin in individual creativity, skill and talent and which have a potential for wealth and job creation through the generation and exploitation of intellectual property” (DCMS, 1998); these sectors include advertising, designer fashion, film, video-games, and architecture and art. In the UK, national policy since the late 1990s has emphasized the creative industries as part of a broader strategy of becoming a “competitive knowledge economy” (DTI, 1999; NACCCE, 1999).

However, new growth theory suggests that all industries today necessarily involve creativity (eg Jefcutt and Pratt, 2002). In the age of innovation, creativity is of concern not only for economic sectors traditionally thought to involve creativity. OECD nations have responded by developing national policies “for encouraging knowledge generation, knowledge acquisition, knowledge diffusion, and the exploitation of knowledge” in science, research, and education (Peters and Humes, 2003, p2). Concrete efforts fall into two broad categories: enhancing the knowledge-generating potential of society, and reforming educational institutions to deliver learning that supports creative work.

To enhance the knowledge-generating potential of society, countries focus on the identification of institutional, societal, and communication structures that foster the diffusion and exploitation of knowledge. Organizational systems that foster retention and dissemination of knowledge are referred to as knowledge management systems. National systems that foster retention and dissemination of knowledge include infrastructure efforts that bring people together – transportation and communication networks.

To deliver learning that supports creative work – through schools and also in lifelong learning – national governments have focused on educational institutions. How might such institutions be reformed to most effectively foster learning for creativity? Information delivery is not enough – educational institutions need to prepare individuals to generate new knowledge. And because knowledge grows and changes so rapidly, learning must continue through the lifespan. The educational system must expand beyond compulsory formal schooling.

Since the first OECD report on the knowledge economy in 1996, the OECD played a leading role in exploring the implications of this shift:

OECD analysis is increasingly directed to understanding the dynamics of the knowledge-based economy and its relationship to traditional economics, as reflected in ‘new growth theory’. The growing codification of knowledge and its transmission through communications and computer networks has led to the emerging ‘information society’. The need for workers to acquire a range of skills and to continuously adapt these skills underlies the ‘learning economy’. The importance of knowledge and technology diffusion requires better understanding of knowledge networks and ‘national innovation systems’. (OECD, 1996; emphasis in original)

In the years following this prescient report, OECD’s CERI project generated a series of reports about the implications of this historic shift for educational institutions (OECD, 2000, 2001, 2003, 2004).

In the first half of this report, I present a brief summary of recent research on creativity, collaboration, and learning, to provide an important background to the task of envisioning possible futures. I then identify five factors that shape a multi-dimensional space of possible futures: technology, customization of learning, diffusion of learning, organizational learning and innovation, and the role of educational professionals. Then I draw on recent research and these five factors to elaborate on six scenarios that were first presented in What Schools for the Future? (OECD, 2001).

Broadening our conceptions of creativity

Psychological research on creativity-from the 1960s focus on personality, through the 1970s and 1980s focus on cognition-have been limited to creative outputs that are highly valued in the West: fine art painting, basic science, and symphonic compositions. As a result, the exceptional creators that have been studied have been those who have excelled in one of these traditional European genres. In his 1993 book Creating Minds, Howard Gardner discussed seven exemplary creators: Freud, Einstein, Picasso, Stravinsky, (T.S.) Eliot, (Martha) Graham, and Gandhi. In his 1996 book Creativity, Mihaly Csikszentmihalyi interviewed 100 exceptional creators, almost all of whom attained their eminence through science or the fine arts.

These forms of creativity will play an important role in the creative societies of the future. But from an education and policy making perspective, these forms are unlikely to provide leverage for increasing the overall creativity of a society and an economy; specifically, they represent a small fraction of the overall revenues accruing to the creative industries. Pratt (2004) has argued that the term “creative industries” implies an individualistic view, such that artsy types are the “creatives” and others are not; thus he prefers the term “cultural industries”. The focus on fine art painting has resulted in a neglect of filmmaking, graphic arts (including website design), and animation (including video-games). The focus on basic science has resulted in a neglect of applied science, engineering, and technology, the source of many financially successful innovations. The focus on art music has resulted in a neglect of improvisational performance, of rock bands, of electronica, and music videos – all of which have substantially broader societal dissemination as well as larger economic impacts.

The traditional response has been to argue that high art forms represent the purest essence of the human creative impulse, and that these “lower” forms are made less pure by their revenue-generating potential. But this traditional response is almost impossible to defend any more, when artists themselves have been increasingly challenging this hierarchy and these divisions. In the 1960s, pop artists like Andy Warhol and Roy Lichtenstein broke the boundaries between high and low art, incorporating elements of advertising graphics and comic strips into their paintings. The Fluxus group began experimenting with performance and installation art, and in the following decades, installation art has become increasingly dominant within the mainstream art world. In the 1970s, the New Hollywood era in film was a major creative break in movie production. In the 1980s, the advent of MTV and its music videos enabled a new burst of creativity among dance choreographers and film artists. Any serious treatment of creativity in the early years of the 21^st century must consider the full range of human innovation. A complete explanation of creativity must also explain comic strips, animated cartoons, movies, music videos, mathematical theory, experimental laboratory science, the improvised performances of jazz and rock music, and the broad range of performance genres found in the world’s cultures (Sawyer, 2006c).

A focus on European high art forms implicitly privileges a set of values that is culturally and historically specific – at a time when innovation economies are found around the globe. In recent years, scholars in fields such as anthropology and sociology have examined the nature of creative genres in non-Western cultures, and have found that most of these non-Western genres are very different from European high art forms (Becker, 1982; Layton, 1991; Sawyer, 2006c). For example, many non-Western cultures have different conceptions of the individual and of creative activity that lead them to downplay the degree of originality in their works, and to emphasize their continuity with tradition (whereas in Western cultures, creators generally call attention to the originality in their works and emphasize how they break with tradition). A complete explanation of the global shift to an innovation economy requires a profound exploration of the broad range of human creative expression.

The increasing importance of collaborative creativity

Most studies of creativity have been conducted by psychologists. This research tends to focus on cognitive processes during and leading up to the moment of insight (eg Ward, Finke and Smith, 1995). This moment almost always occurs when the individual is alone, in isolation; as the peak experience in creative lives, its salience fascinates us and calls out for study. As a result, many creativity researchers have focused on the moment of creative insight, and attempted to analyze it as a psychological or cognitive process.

However, close studies of how creativity occurs in the real world reveals that the mythical moment of insight is misleading. The innovations that impact our world rarely emerge, fully formed, from a single moment of insight. Rather, they typically involve many small “mini-insights,” perhaps one or more each day; and the primary work of the creator is to bring those serial insights together over time, to result in effective innovation. Here are two typical reports from exceptionally creative individuals:

Literary critic Wayne Booth: “My creative periods tend to be sort of spread out rather than moments of actually clear illumination….generally speaking, it’s a matter of hard work and steady progress rather than moments of total transformation and clarity.” (in Csikszentmihalyi and Sawyer, 1995, p357)

Sculptor Nina Holton: “You have these ideas, and then you work on them. As you work on them, you get new ideas….One makes the other one come out.” (in Csikszentmihalyi and Sawyer, 1995, p353)

This requires conscious expertise on the part of the creator – to structure the work day so that these mini-insights continue to emerge, to implement systems and practices to enable each insight to spark the next, and to enable the aggregation of multiple insights to result in the eventual emergence of a worthwhile idea.

These mini insights are deeply embedded in a broader social process (Csikszentmihalyi and Sawyer, 1995). The periods of hard work which precede and follow the insight are fundamentally social, deeply rooted in the social group of colleagues and in the individual’s internalized understanding of the creative domain itself. The balance of hard work and idle time which emerges from these interviews can also be viewed as a balance between social interaction and individual isolation. As Csikszentmihalyi and Sawyer (1995) wrote, based on an interview study with 60 exceptional creators:

we found that creative individuals had a strong subjective awareness of external social or discipline influences at each creative stage. When asked to describe a moment of creative insight, they typically provided extended narratives that described not just a single moment but a complex, multi-stage process, with frequent discussions of interpersonal contact, strategic or political considerations, and awareness of the paradigm, of what questions were interesting as defined by the discipline …. The moment of creative insight … is surrounded and contextualized within an ongoing experience that is fundamentally social. (p334)

A psychological focus on the individual is contradicted by the empirical record in a second, more important, way: in the great majority of innovations throughout history, the small insights that eventually led to the innovation each were generated by different individuals. This research is consistent with sociological approaches such as the production of culture perspective (Peterson and Anand, 2004), as described by Pratt (2004):

The value of this perspective is that it seeks to present cultural outputs as the result of collective innovation by a number of participants whose participation is various, but linked together by the organization of production. Thus, it directs our attention to the analysis of complex organizational forms, as well as individual positioning within them, that constitute particular cultural forms. Production in this sense is not only suggestive of creative and innovative ideas, but also of the conditions under which these ideas may be mobilized (p118).

Innovations emerge from complex social systems, with constant communication, collaboration, and knowledge sharing, to accomplish the necessary process of enabling ideas to spark later ideas, and to enable a social process whereby the multiple component insights could be brought together appropriately to generate an effective innovation.

Collaboration in social networks accelerates innovation because more individuals can have more ideas. The challenge, of course, is to design effective organizational systems so that ideas build on each other, rather than opposing and canceling each other out; so that ideas accumulate over time to result in the emergence of creativity, rather than deteriorating in a political morass of failed projects.

In today’s economy, the most important forms of creativity – movies, television shows, big science experiments, music videos, compact disks, computer software, video-games – are joint cooperative activities of complex networks of skilled individuals. The creative products that US society, for example, is best known for today – including movies, music videos, and video-games – are all made by organized groups of highly specialized individuals.

In today’s creative society, even creative genres that have traditionally been associated with solitary individuals are reshaping around collaboration. For example, writing seems a uniquely solitary activity; however, much creative writing today is deeply collaborative. The scripts of all movies and television shows are created by teams of writers, each contributing throughout the process (Sawyer, in press). The internet has enabled new forms of collaborative writing. The best known is the wiki: a web page that anyone may modify at any time, such as the online encyclopedia Wikipedia. Also well known is the community of bloggers, known as the blogosphere; this likewise represents a collective social phenomenon. Most bloggers provide links to other bloggers who write on the same topic, and frequently reference each other’s postings in their own.

Some writers have begun to form writers’ collaboratives – groups of writers who work together to author a single text, which is then published under the name of the collaborative and not any individual author. Two online writer communities that I turned up with an October 2008 internet search were Protagonize (www.protagonize.com) and StoryMash (www.storymash.com).

Various information technologies, including the internet, have enabled new forms of collaboration such as mash-ups and modding. A “mash-up” is a new combination of two existing products; it can refer to music or video sampling, but more commonly refers to web applications that combine data from more than one source. The Google Maps application supports mash-ups by allowing its mapping data to be used on other sites; for example, the WikiCrimes web site combines this map data with user postings of crime locations (http://www.wikicrimes.com). Mash-up sites often support broad collaboration by allowing all users to contribute; any user of WikiCrimes can mark the location of a crime.

“Modding” occurs when a user of a product modifies the product to better suit his or her needs. Modding is particularly common in strong user communities, where users collaborate to share their new modifications. Many examples of modding are found in extreme sports. As an example of modding, extreme bike jumpers often lift their feet off the pedals while in mid-air. This results in a problem: the bike pedals spin around during this time, making it difficult for the biker to get his feet positioned back on the pedals again at the end of the maneuver. One bike jumper modified the pedals to address this problem by inserting a small circle of foam padding on the pedal axle next to the pedal, thus preventing the pedals from spinning in midair but still allowing the pedals to be used when on the ground (Luthje, Herstatt and von Hippel, 2002). Many examples of modding are also found in software; dedicated video-gamers often reverse-engineer and modify their game’s program. An example is the widespread modding of the LEGO Mindstorms robotic control system (Koerner, 2006).

Theorizing collaboration

To explain the creativity of complex collaborating groups, we need a theoretical framework that allows us to understand how groups of people work together, and how the collective actions of many people result in a final created product. These forms of creative production involve distributed cognition-when each member of the team contributes an essential piece of the solution, and these individual components are all integrated together to form the collective product. Most of today’s important creative products are too large and complex to be generated by a single individual; they require a team or an entire company, with a division of labor and a careful integration of many specialized creative workers.

In the 1980s and 1990s, cognitive science underwent an important shift away from a focus on isolated individuals, toward a situated view of knowledge (Greeno, 2006; Robbins and Aydede, 2008). Cognitive scientists were deeply influenced by several strands of research including the ethno-methodological focus on meaning-making found in studies of situated cognition (eg Suchman, 1987); Hutchins’ (1995) work on collective cognition; and activity theory, practice theory, and sociocultural theory, based in American pragmatism and in the Soviet psychology of Vygotsky (as in works by M. Cole, B. Rogoff, and J. Wertsch). These studies documented many complex activities in which individuals participate as but one component in a distributed socio-technical system. Many of these studies take an anthropological approach to the study of task-focused work teams, and these studies have helped scholars to better understand how individuals and technological artifacts function in complex systems of activity. Such studies include the Lancaster study of air traffic control (Dourish, pp64-68) and collaborative virtual environments like DIVE and MASSIVE (Dourish, pp88-91). These studies demonstrate that social action is embedded, that social order emerges from practice, and that individuals and technological artifacts are unavoidably “embedded in a set of social and cultural practices” (Dourish, 2001, p97).

The concept of situated cognition is closely related to the concepts of embodiment and mutualism (Prinz, 2008). “Embodiment” is the notion that before computers can be truly intelligent they must move out into the world and become “embodied” in moving, acting robotic devices (Clark, 1997). Embodiment is central to Dourish’s (2001) discussion of what he calls tangible computing, a term meant to encompass Norman’s “invisible computing” and Weiser’s “ubiquitous computing.” For Dourish (2001), embodiment “means being grounded in everyday, mundane experience” (p125) and is “the property of our engagement with the world that allows us to make it meaningful” (p126).

“Mutualism” is the position that mind cannot be separated from the physical and biological world (Still and Costall, 1991). Mutualism shares with situated cognition a desire to avoid reductionism to any one explanatory factor – whether the physical brain (contrasted with the mental), or the individual mind (contrasted with the sociotechnical system). Mutualism shares an interest in exploring holistic phenomena that emerge from processes of complexity. As Pickering writes, “mutualism aims for emergence without mystery” – it rejects reductionist explanation of complex systems, but without arguing for any spooky non-material forces (Pickering, n.d.). Thus, the mental cannot be reduced to physical causes. Pickering allies this position with critiques of cognitivism including the embodiment tradition starting with Winograd and Flores (1986) and with connectionism (Bechtel and Abrahamsen, 1991).

Among education researchers, these theoretical approaches have been broadly influential, leading to what I call a sociocultural approach (Sawyer, 2005). Within socioculturalism, I include cultural psychologists, Vygotskian educational theorists, and those studying situated action in learning environments (Cole, 1996; Forman, Minick and Stone 1993; Greeno and Sawyer, 2008; Lave and Wenger, 1991; Rogoff, 1990; Suchman, 1987; Valsiner, 1998; Wertsch, 1998). This is a broad definition, because each of these areas holds to subtly different theoretical positions; but they can be grouped for our purposes because they generally hold to a view that the individual and the social are inseparable; the education researcher cannot meaningfully distinguish between what is internal to the individual and what is external context. As the prominent sociocultural psychologist Barbara Rogoff (1990) has argued, “The child and the social world are mutually involved to an extent that precludes regarding them as independently definable” (p28).

Sociocultural approaches are broadly compatible with two prominent traditions in the study of collaboration and learning: First, researchers working within a Piagetian socio-cognitive framework have emphasized the mediating role played by conflict and controversy (Bearison, Magzamen and Filardo, 1986; Doise and Mugny, 1984; Miller, 1987; Perret-Clermont, 1980); second, researchers working within a Vygotskian framework have emphasized how participants build on each other’s ideas to jointly construct a new understanding that none of the participants had prior to the encounter (Forman, 1992; Forman and Cazden, 1985; Palincsar, 1998).

The learning sciences

Soon after the turn of the century, education researchers began to publish books and reports exploring the implications for formal schools of the transition to the age of innovation (eg Bereiter, 2002; Hargreaves, 2003; Sawyer, 2006b). As this transformation continues in the future, knowledge and learning will become increasingly important. For career success, each individual worker will be expected to know a great deal more, and to continually learn to adapt to a changing technological and competitive environment. However, this knowledge must be of a type that can support creative work. The field that studies how different forms of knowledge align with different forms of learning is called the learning sciences (Sawyer, 2006a). Learning sciences is an interdisciplinary field that studies teaching and learning. The learning sciences has been deeply influenced by the above shifts in cognitive science, away from a focus on individual mental representations and processes, toward distributed cognition, situativity, and embodiment. Learning scientists study learning in a variety of settings – not only the more formal learning of school classrooms, but also the more informal learning that takes place at home, on the job, and among peers. The goal of the learning sciences is to better understand the cognitive and social processes that result in the most effective learning, and to use this knowledge to redesign classrooms and other learning environments so that people learn more deeply and more effectively. The sciences of learning include cognitive science, educational psychology, computer science, anthropology, sociology, information sciences, neurosciences, education, design studies, instructional design, and other fields. In the remainder of this report, I draw on learning sciences findings to identify a set of recommendations for how societies can respond to key trends through 2025 and beyond.

Sawyer (2006d) has argued that schools cannot effectively respond to the shift to a knowledge-based creative economy without first moving beyond widely held assumptions about schooling that include the following:

• Conception of knowledge. Knowledge is a collection of facts and procedures.
• Conception of schooling. The goal of schooling is to transfer facts and procedures into students’ heads.
• Conception of the teacher. The teacher is the individual who possesses these facts and procedures, and whose mission is to transfer them to students.
• Conception of curriculum. Simpler facts and procedures are to be transferred first; later facts and procedures progressively build on top of these simpler ones.
• Conception of assessment. The success of schooling can be determined by administering paper-and-pencil tests that determine how many of these facts and procedures the student has internalized.

Collectively, this set of traditional assumptions has been called, variously, a transmission and acquisition model (Rogoff, 1997), the banking metaphor (Freire, 1989), instructionism (Papert, 1993), and the standard model (OECD, 2008).

The problem is that this standard model was designed for the industrialized economy of the early 20^th century. Although schools based on this model have been effective at transmitting a standard body of facts and procedures to students, they are not able to support students in mastering the kinds of knowledge required for creative work. But the structural configurations of today’s schools make it very hard to create learning environments that result in deeper understanding. One of the central underlying themes of the learning sciences is that students learn deeper knowledge when they engage in activities that are similar to the everyday activities of professionals who work in a discipline. This focus on authentic practice is based on a new conception of the expert knowledge that underlies knowledge work in today’s economy. In the 1980s and 1990s, scientists began to study science itself, and they began to discover that newcomers become members of a discipline by learning how to participate in all of the practices that are central to professional life in that discipline. And increasingly, cutting-edge work in the sciences is done at the boundaries of disciplines; for this reason, students need to learn the underlying models, mechanisms, and practices that apply across many scientific disciplines, rather than learning in the disconnected units that are found in many standard model science classrooms.

I have argued (Sawyer, 2008) that learning environments that prepare learners for the knowledge economy will look very different from this standard model. Key characteristics include the following:

Deeper conceptual understanding. Rather than simple accumulation of facts and skills, learners construct deeper conceptual understanding and the ability to think and problem solve with their knowledge.

Availability of diverse knowledge sources. Learners can acquire knowledge whenever they need it from a variety of sources: books, websites, and experts around the globe.

Collaborative group learning. Students learn together as they work collaboratively on authentic, inquiry-oriented projects.

Assessment for deeper understanding. Tests should evaluate the student’s deeper conceptual understanding, the extent to which their knowledge is integrated, coherent, and contextualized.

I elaborate each of these characteristics in the four following sections.

Deeper conceptual understanding

By the 1980s, cognitive scientists had discovered that children retain material better, and are able to generalize it to a broader range of contexts, when they learn deep knowledge rather than surface knowledge, and when they learn how to use that knowledge in real-world social and practical settings. In the late 1980s, these learning scientists began to argue that standard model schools were not aligned with the knowledge economy.

Studies of knowledge workers show that they almost always apply their expertise in complex social settings, with a wide array of technologically advanced tools along with old-fashioned pencil, paper, chalk, and blackboards. These observations led many cognitive scientists to a situated view of knowledge, as described above, and learning sciences researchers have adopted this situated view (Greeno, 2006). “Situated” means that knowledge is not just a static mental structure inside the learner’s head; instead, knowing is a process that involves the person, the tools and other people in the environment, and the activities in which that knowledge is being applied. This perspective moves beyond a transmission and acquisition conception of learning that is implicit in the standard model; in addition to acquiring content, what happens during learning is that patterns of participation in collaborative activity change over time (Rogoff, 1990).

In the knowledge economy, memorization of facts and procedures is not enough for success. Educated graduates need a deep conceptual understanding of complex concepts, and the ability to work with them to generate new ideas, new theories, new products, and new knowledge – through complex cognitive operations such as conceptual elaboration and conceptual combination. They need to be able to critically evaluate what they read, to be able to express themselves clearly both verbally and in writing, and to be able to understand scientific and mathematical thinking. They need to learn integrated and usable knowledge, rather than the sets of compartmentalized and decontextualized facts emphasized by instructionism. They need to be able to take responsibility for their own continuing, life-long learning. These abilities are important to the economy, to the continued success of participatory democracy, and to living a fulfilling, meaningful life. The standard model of schooling is particularly ill-suited to the education of creative professionals who can develop new knowledge and continually further their own understanding.

Diverse knowledge sources

In the standard model, the teacher is assumed to possess all of the knowledge. In the type of learning suggested by learning sciences research (for example, scaffolded constructivist activities such as inquiry- and project-based learning) students gain expertise from a variety of sources – from the internet, at the library, or through email exchange with a working professional – and the teacher will no longer be the only source of expertise in the classroom. Learners will acquire knowledge from diverse sources; of course, expert support from the teacher can facilitate these learning processes, but the teacher’s involvement will not be one of transmitting knowledge.

Collaboration

In the first part of this report, I emphasized the increasing importance of collaboration, both in creativity and in learning. In addition to this body of research supporting the educational benefits of collaboration, the innovation economy demands graduates who are highly skilled at creating together in groups (Sawyer, 2007). But in standard model schools, there is a belief that a student only knows something when that student can do it on his or her own, without any use of outside resources. There is a mismatch between the standard model and the situated, collaborative knowledge and practice that I described above.

Assessment

David Guile (2003) has explored the implications of the knowledge economy for educational institutions and for the policy debate. He begins with the concept of “credentialism” (Young, 1998), one possible response to the shift to the knowledge economy. Credentialism is the belief that education is about the acquisition of pre-existing knowledge; the goal of educational institutions should be to ensure that “the vast majority of the population achieve qualifications or certified skills and knowledge that relate to their future employment” (Guile, 2003, p92). Learning is conceived of as the acquisition of certified knowledge and skills, and lifelong learning is conceived of as a continuing accumulation of qualifications.

Guile goes on to point out that this conception of knowledge and learning is inadequate – mastering existing knowledge and skills is not sufficient to generate the new knowledge that the innovation economy requires. First, credentialism assumes that knowledge and skills are decontextualized commodities to be acquired; when in fact, in knowledge-intensive workplaces knowledge is situated – embedded in contexts and social practices (Greeno and Sawyer, 2008; Lave and Wenger, 1991). Furthermore, the key need is for workers who are capable of continuing innovation, and the certifications granted by today’s educational institutions provide no measure of that capability (Guile and Fonda, 1999; Young, 1998).

The danger is that policy makers could attempt to address the educational needs of the creative society by providing credentialist solutions. In fact, this has been the primary form of response in the UK and the EU (Guile, 2003), and the United States, with the 2001 passage of the No Child Left Behind legislation, with its core focus on standardized test measures.

As I argue below, the schools of the future will increasingly result in customized learning. Yet today’s assessments require that every student learn the same thing at the same time. The standards movement and the resulting high-stakes testing are increasing standardization, at the same time that learning sciences and technology are making it possible for individual students to have customized learning experiences. Customization combined with diverse knowledge sources enable students to learn different things. Schools will still need to measure learning for accountability purposes, but we don’t yet know how to reconcile accountability with customized learning.

In today’s high-stakes testing environment, learning sciences researchers need to demonstrate that their methods result in better student outcomes (Pellegrino, Chudowsky and Glaser, 2001). Today’s standardized tests assess relatively superficial knowledge and do not assess the deep knowledge required by the knowledge society. Standardized tests, almost by their very nature, evaluate decontextualized and compartmentalized knowledge. For example, mathematics tests do not assess model-based reasoning (Lehrer and Schauble, 2006); science tests do not assess whether pre-existing misconceptions have indeed been left behind (diSessa, 2006; Linn, 2006) nor do they assess problem-solving or inquiry skills (Krajcik and Blumenfeld, 2006). As long as schools are evaluated on how well their students do on such tests, it will be difficult for them to leave the standard model behind.

One of the key issues moving forward is how to design new kinds of assessment that correspond to the deep knowledge required in today’s knowledge society (Carver, 2006; Means, 2006). Several learning sciences researchers are developing new assessments that focus on deeper conceptual understanding.

In classrooms that make day-to-day use of computer software, installed on each student’s own personal computer, there is an interesting new opportunity for assessment-the assessment could be built into the software itself. After all, the learning sciences has found that effective educational software has to closely track the students’ developing knowledge structures to be effective; since that tracking is being done anyway, it would be a rather straightforward extension to make summary versions of it available to teachers. New learning sciences software is exploring how to track deep learning during the learning process, in some cases inferring student learning from such subtle cues as where the learner moves and clicks the mouse-providing an opportunity for assessment during the learning itself, not in a separate multiple-choice quiz (eg Gobert, Buckley and Dede, 2005).

Five factors impacting the future of learning

As the age of innovation unfolds over the coming decades, and societies, organizations, and educational institutions evolve, the following unresolved challenges must be addressed. How these challenges are resolved will in large part determine which future scenario of learning will emerge.

1. Technology

For decades, educational futurists have been claiming that computers will change schools. The first was in the 1950s, when B.F. Skinner claimed that his “teaching machines” made the teacher “out of date” (1954, 1968, p22). Then, Papert’s 1980 book Mindstorms argued that giving every child a computer would allow students to actively construct their own learning, leaving teachers with an uncertain role: “schools as we know them today will have no place in the future” (p9). The rise of the internet in the 1990s resulted in an increasing belief that ICT would soon transform schools. However, despite decades of rapid growth in the capabilities of ICT, and substantial government funding to install computers and high-speed internet connections into schools, there is almost no evidence that ICT has enhanced learning (Cuban, 2001). Furthermore, research suggests that when ICT are introduced to schools, they are embedded into existing standard model practices, rather than used to drive a fundamental transformation of schooling. For example, many textbook publishers today are convinced that within a few years, paper textbooks will be replaced by laptop computers that store all of a student’s textbooks and curriculum materials. But if every student has a laptop that contains the same textbooks as before, nothing fundamental has changed.

So it is important to make a distinction between ICT that sustains the existing standard model, and ICT that transforms the standard model towards a more learning-sciences based learning environment. Learning scientists are exploring technologies that support the authentic, situated, and collaborative essence of creative learning (see Sawyer, 2006a). One example is the increasing use of inexpensive wireless interactive learning devices (WILD), handheld computers that are networked and capable of communicating with each other. WILD include personal digital assistants (PDAs) such as the Palm Pilot, and also, increasingly, mobile phones. The promise of harnessing computing where every student has his or her own computer, and where they are available everyday, anytime, anywhere for equitable, personal, effective, and engaging learning give WILD a greater transformative potential than desktop computers. As of 2006, more than 10% of US schools provided handhelds to students (Pea and Maldonado, 2006). The popularity of handhelds reflects the desire of schools to make computing integral to the curriculum, rather than only occasionally used in labs. As of 2005, 55% percent of U.S. children between the ages of 8 and 18 owned a handheld videogame player (Pea and Maldonado, 2006). Since that report, a new generation of handheld devices has become available that have internet capabilities, such as the Nintendo DS and the iPhone 3G, and similar devices raise the level of internet sophistication even higher. At present, there is almost no educational software available for these platforms, but the potential is enormous. One promising current effort is the European Union’s m-Learning project (www.m-learning.org). The m-Learning project is aimed at young adults, aged 16-24, who are most at risk of social exclusion, and the project’s goal is to develop new products and services that will deliver learning experiences via inexpensive, portable devices that are accessible to almost everyone, primarily, mobile phones.

The potential is that this technology could support a form of technology use that is embedded in the ongoing situated practice of the learning community. The 2004 FutureLab report Literature Review in Mobile Technologies and Learning (Naismith, Lonsdale, Vavoula and Sharples, 2004) emphasizes the alignment between the affordances of WILD and the key principles emerging from learning sciences research. First, WILD enable learners to actively construct their own knowledge, for example through participatory simulations such as the Virus Game (Collella, 2000), where learners play the role of hosts in the spread of a virus, and their WILD keep track of who they meet and how the virus spreads. Second, WILD support situated activities that are embedded in authentic contexts, such as MOBIlearn (Lonsdale et al, 2003), a major European research project that is focused on context-aware delivery of content and services, using location-sensitive technologies such as GPS. Third, WILD support collaborative learning environments, both because the devices are networked, and also because they are small enough to be used while learners are engaged in face-to-face activities. An example is the MCSCL project in Chile (Zurita and Nussbaum, 2004), which is using hand-held computers to encourage face-to-face collaboration.

In addition to the potential classroom applications, WILD also enable anytime, anywhere learning, because students can interact with learning content outside of the classroom. Educational software companies have the opportunity to provide small pieces of educational content that students can access while they are engaged in a different activity: watching television or waiting for the bus.

The addition of GPS capabilities to these devices provides for another potential opportunity: context and location sensitive learning software. Several projects are exploring educational applications that respond to the wearer’s current location, such as tour guides (Abowd et al, 1997) and location-aware language learning applications that adapt the content presented according to users’ location (Ogata and Yano, 2005), and digitally augmented field trips (Rogers et al, 2004; Williams et al, 2005). Handhelds are becoming particularly widespread in informal learning settings such as science centers and other museums.

Because learners are networked together as they use WILD, it is an example of computer support collaborative learning (CSCL), a burgeoning research area with international conferences every alternate year. The acronym MCSCL is sometimes used to refer to Mobile CSCL. These applications are usually internet-based and often rely on desktop computers as well as wireless devices. Even when based on desktop computers, CSCL applications share many of the same benefits: they enable collaborative, authentic learning that extends beyond the boundaries of the classroom.

The key to avoiding the mistakes of past advocates of learning technology is to realize that computers will never attain their full potential if they are merely add-ons to the existing standard model classroom. Appropriate use of information technology requires a fundamental rethinking of the entire learning environment.

2. Customization

The goals of standard model schools were to ensure standardization – all students were to memorize and master the same core curriculum – and this model has been reasonably effective at accomplishing these goals. Standard model schools were structured, scheduled, and regimented in a fashion that was explicitly designed by analogy with the industrial-age factory (Callahan, 1962), and this structural alignment facilitated the ease of transition from school student to factory worker.

In the standard model, everyone learns the same thing at the same time. Many parallel structures and processes of these schools align to enforce standardization. But learning sciences findings suggest that each student learns best when they are placed in a learning environment that is sensitive to their pre-existing cognitive structures; and learning sciences research has shown that different learners enter the classroom with different structures. Learning sciences research suggests that more effective learning will occur if each learner receives a customized learning experience.

Educational software gives us the opportunity to provide a customized learning experience to each student to a degree not possible when one teacher is responsible for six classrooms of 25 students each. Well-designed software could sense each learner’s unique learning style and developmental level, and tailor the presentation of material appropriately (see Koedinger and Corbett, 2006, for an example). Some students could take longer to master a subject, while others would be faster, because the computer can provide information to each student at his or her own pace. And each student could learn each subject at different rates; for example, learning what we think of today as “5^th grade” reading and “3^rd grade” math at the same time. In age-graded classrooms this would be impossible, but in alternative models of schooling there may be no educational need to age-grade classrooms, no need to hold back the more advanced children or to leave behind those who need more help, and no reason for a child to learn all subjects at the same rate.

In many countries, age-graded classrooms also serve to socialize children, providing opportunities to make friends, to form peer groups, and to participate in team sports. Some of these activities may not seem critical to learning, but there is a broad base of research suggesting that peer learning is uniquely effective. If learning and schooling were no longer age-graded, other institutions would have to emerge to provide these opportunities. Finally, if primary and secondary schooling are no longer age graded, then higher education could no longer expect all incoming students to be the same age, and this would result in dramatic transformations of traditional universities.

3. Diffusion of education

Museums and public libraries might play an increasingly larger role in education. They could receive increased funding to support their evolution into learning resource centers, perhaps even receiving an increasingly large portion of government education funding. They could participate in several ways: for example, by developing curriculum and lesson plans and making these available to students anywhere over the internet, and by providing physical learning environments as they redesign their buildings to support schooling. Science centers have already taken the lead in this area, developing inquiry-based curricula and conducting teacher professional development, but art and history museums may soon follow suit.

The boundary between formal schooling and continuing education will increasingly blur. The milestone of a high school diploma could gradually decrease in importance, as the nature of learning in school begins to look more and more like on-the-job apprenticeship and adult distance education. The $100 computer and the inexpensive handheld allow for learning to take place anywhere, anytime; 16 year olds could work their part-time jobs during the day and take their classes at night, just like adults do now. Many types of knowledge are better learned in workplace environments; this kind of learning will be radically transformed by the availability of anywhere, anytime learning, as new employees take their laptops or handhelds on the job with them, with software specially designed to provide apprenticeship support in the workplace. Professional schools could be radically affected; new forms of portable just-in-time learning could increasingly put their campus-based educational models at risk.

The relationship between the institution of school and the rest of society may need to change, as the internet allows learners to interact with adult professionals outside the school walls, and as classroom activities become increasingly authentic and embedded in real-world practice.

The internet enables learning to take place anywhere. For example, as of 2005, 22 US states had established online virtual schools; during the 2003-2004 school year, the Florida Virtual School became the state’s 73^rd school district, and now receives per-student funding from the state just like any other district. In the 2004-2005 school year, 21,000 students enrolled in at least one of its courses (Borja, 2005).

The term “Web 2.0″ is often used to refer to a shift in internet usage to more active forms of participation, where all users contribute content and play the role of both producer and consumer (as opposed to “Web 1.0″ where experts generated content and users were primarily limited to the role of consumer). Web 2.0 includes wikis, blogging, multiplayer online games, and modding and mash-ups. Many education researchers are experimenting with Second Life, an internet-based virtual world where individuals can create on-screen characters called avatars, and then communicate with each other through their keyboards. Many university instructors have created classrooms in Second Life; at the Open University in the United Kingdom, the Schome project (www.schome.ac.uk) has created online learning communities for both teenagers and adults. This has led some to suggest that education might experience a similar shift to Education 2.0 – a world that supports collaborative learning, active participatory learning, and new forms of inquiry: new forms of engaging with knowledge (TLRP, 2008).

However, there are many challenges posed when Web 2.0 technologies are introduced into schools. The TLRP report Education 2.0? (TLRP, 2008) has noted that Web 2.0 challenges traditional notions of authority, authorship, and integrity; this may be welcomed by some, but resisted by others. The structure of the curriculum could change radically, even to an extreme of learners developing their own curricula. The challenge is to find a way to harness the collaborative and participatory power of Web 2.0, while retaining valued curricular goals and guidance of experts and teachers.

4. Organizational learning

The organizations that thrive will be those that successfully master the challenges of organizational learning and knowledge management. Future schools will face these challenges.

Organizational learning refers to the activities, processes, and structures through which individuals “acquire, share, and combine knowledge through experience with one another” (Argote, Gruenfeld and Naquin, 2001, p370). Organizational learning processes can be explicitly designed with the goal of increasing organizational learning, or they can be emergent and informal. Organizational learning is an emergent property of groups, and cannot be equated with the sum of the individual learning that happens in the members of the organization.

Knowledge management refers to the processes and structures that retain and distribute knowledge in an organization. Without knowledge management, organizational learning can only be of limited effectiveness, because organizational learning occurs at the team level (Edmondson, 2002), and therefore large complex organizations need systems in place to disseminate knowledge among teams.

Knowledge management has proven to be a difficult task. Several software vendors offer products that purport to accomplish knowledge management – databases where knowledge workers are to enter important information about their experiences with projects, customers, or challenges, marked with keywords that would allow later retrieval by anyone in the organization. However, almost all companies that have implemented such systems have found them to be of extremely limited value; in most cases, staff rather quickly stops using the system altogether.

Most schools today are structured as highly bureaucratic and top-down organizational forms. Such organizational forms have proven to be the least effective at successful organizational learning and knowledge management. A challenge moving forward is for schools to revise their organizational forms to enable adaptive and agile learning and knowledge management. Teacher professional development communities are one promising attempt in this direction (Fishman and Davis, 2006).

5. Educational professionals

In one vision of the innovation economy, the teacher becomes a creative worker, jointly constructing knowledge with learners in a creative classroom. Teachers are considered to be creative professionals, and are trained and rewarded accordingly. Sawyer (2004) has argued that creative teaching involves disciplined improvisation: the ability to draw on the routines and practices that are acquired through experience, but to modify them improvisationally to respond to each classroom’s needs at the moment. Disciplined improvisation acknowledges the benefits of frameworks; well-designed curricula are necessary to effectively scaffold constructivist learning. To create an improvisational classroom, the teacher must have a high degree of pedagogical content knowledge-to respond creatively to unexpected student queries, a teacher must have a more profound understanding of the material than if the teacher is simply reciting a preplanned lecture or script (Feiman-Nemser and Buchmann, 1986; Shulman, 1987). An unexpected student query often requires the teacher to think quickly and creatively, accessing material that may not have been studied the night before in preparation for this class; and it requires the teacher to quickly and improvisationally be able to translate their own knowledge of the subject into a form that will communicate with that student’s level of knowledge.

There are, however, some who espouse a very different vision: of a scripted, “teacher-proof” classroom such that just about anyone would be capable of serving as a teacher. In this vision, sometimes known as “direct instruction,” education researchers and curriculum experts develop a highly detailed lesson plan for each class session: so detailed that, in some cases, all of the teacher’s utterances are scripted. In schools that have implemented this vision, teachers are reprimanded if they diverge from the official script that appears in their lesson plan. In such classrooms, the only skill required of a teacher is the ability to read the script, speak clearly, and manage the students to maintain a focused classroom.

This vision of the de-skilled teacher aligns with the credentialist, instructionist paradigm that I described earlier, and learning sciences research suggests that such a curriculum is not capable of generating creative graduates. Consequently, this vision also aligns with the possibility that the economy could become radically deskilled.

Even if such a vision comes to pass in the great majority of schools, there are likely to continue to be creative classroom options available to those who can afford it. The risk is of a social order that reproduces itself through these imbalances in the education system: deskilled classrooms for the majority of citizens, which prepare them only for deskilled labor, and creative classrooms for a privileged elite, who have been tapped to move into those few professions that continue to require creativity.

Related to these two competing visions of the teacher is the possibility that the role of “teacher” could devolve into multiple roles. For example, the teaching profession could become multi-tiered, with master teachers developing curriculum in collaboration with software developers and acting as consultants to schools, and learning centers staffed by a variety of independent contractors whose job no longer involves lesson preparation or grading, but instead involves mostly assisting students as they work at the computer or gather data in the field (Stallard and Cocker, 2001).

The challenges to any transformation of the teaching profession are likely to include resistance from teachers’ professional organizations, unless the transformations are handled with great sensitivity and political skill. A second challenge would be faced by institutions of higher education responsible for preparing these educational professionals; they currently are designed to prepare for a single, unified teaching profession. In most countries, teachers are certified by government bodies, and before educational certification could become multi-tiered, complex political and institutional processes would have to take place.

Possible Future Scenarios

In the face of the above variables, factors, and pressures, a society’s response to the age of innovation could move down a range of different paths. I group my comments into the six scenarios that are outlined in the OECD report What Schools for the Future? (OECD, 2001). I believe these still best represent the possible range of futures.

Scenario 1: Robust bureaucratic school systems

Schools continue much as they are today. They are characterized by strong, centralized bureaucracies, with standardization and uniformity emphasized. Despite all of the forces identified above, in Scenario 1 schools as institutions prove to be extremely resistant to radical change. This could result due to a combination of vested interests, powerful stakeholders, and parents who prefer only gradual change in schools. It could also result from the importance of the non-classroom functions of schools: providing a place for two-career parents to place their children during the day, socialization, sorting and selection, and the credentialing function.

Forces that work against Scenario 1 include the growing power of learners and parents as producers and participants in learning (“Education 2.0″), the impact of ICT in disseminating learning outside the classroom walls, and a potential crisis in the teacher workforce (which, if taken to an extreme, results in Scenario 6).

Scenario 2: Extending the market model

Advocates of a politically conservative approach – those who hold that the free market always provides better and more efficient solutions – will continue to argue that education should be privatized. An open market of free competition, they argue, will allow educational innovations to be tried, and the successful ones will thrive and propagate. The current centralized government model, they argue, is incapable of innovation due to standardization and top-down control.

In Scenario 2, the conservative vision comes to pass, perhaps due to increasing dissatisfaction with public schools. Government funding is distributed directly to parents, who then choose from a range of educational offerings. Privately-run, for-profit learning centers might begin to offer a three-hour intensive workday, structured around tutors and individualized educational software, with each student taking home his or her laptop to complete the remainder of the day at home. In the US, one of the largest for-profit educational franchises is Sylvan Learning Centers; these storefront operations could expand dramatically if given access to government funding. Because curriculum and software would be designed centrally, and the software does the grading automatically, these tutors could actually leave their work at the office – unlike today’s teachers, who stay up late every night and spend all weekend preparing lesson plans and grading. For those parents who need an all-day option for their children due to their work schedule, for-profit charter schools could proliferate, each based on a slightly different curriculum or a slightly different software package. Particularly skilled teachers could develop reputations that would allow them to create their own “start-up schools,” taking 10 or 20 students into their home for some or all of the school day – the best of them providing serious competition for today’s elite private schools, and earning as much as other knowledge workers such as lawyers, doctors, and executives.

The history of innovation suggests that frequent experimentation is necessary for innovation to occur. To enhance innovation, educational systems must develop some way to allow frequent variations to be attempted, and some method for selecting and disseminating the best of these innovations. The innovations must be sustainable over time, and they must be scalable to large numbers of schools and districts. The market is one such mechanism for selection and dissemination; if Scenario 3 is rejected, then another such mechanism must be proposed and implemented.

One risk of allowing competition and innovation in the free market is that the education system could fragment, with some schools offering a creative education (possibly for a small elite) and other schools offering credentialist training in specific, narrowly tailored sets of job-specific skills.

Scenario 3: Schools as core social centers

Schools are largely viewed as successful and are widely respected as playing a central function in society. The level of public support for schools increases, as a broad public recognizes that schools perform a necessary public role. Schools are viewed as centers of a community, and as serving not only the function of educating individuals, but also as serving a collective function of community building and social capital formation. Poor areas receive increased funding to accommodate their relatively greater need.

Schools as core social centers not only serve full-time primary and secondary students, but also play a role in adult and continuing education. Schools become less bureaucratic and more diverse. The boundaries marking one school level from the next become more flexible, as learning is increasingly viewed as a lifelong process. There is greater mixing of ages, and increased youth-adult activities.

Schools work increasingly closely with other community institutions (libraries, museums, social service agencies), viewing themselves as one node in a network. The professional role of teacher evolves to collaborate more closely with other sources of community expertise. Thus the local role of schools becomes much more critical; centralization and uniformity at the national level declines in significance.

Scenario 4: Schools as focused learning organizations

As in Scenario 3, schools enjoy high levels of public trust and increased funding, and equity is an important issue, with poorer schools receiving increased funding to address these disadvantages. Schools reform themselves around a knowledge-society agenda, based in the sort of learning sciences research described earlier in this report. Experimentation and innovation are common, curriculum variations are widespread. More specialized classrooms and schools might emerge (focused for example on the arts, foreign languages and affairs, or technology). Schools retain an important credentialing function, although other forms of credentialing may also emerge; new forms of assessment frequently appear.

Schools become true learning organizations, capable of generating and disseminating innovation. Organizational structures become flatter, with a reduction in hierarchical levels as teams of teachers take on leadership responsibilities. Teachers are viewed as knowledgeable professionals and are more motivated and more highly paid. There is an increasing mobility in and out of teaching and other professions. Compared to Scenario 3, teaching remains a distinct profession with a clear identity, but with more frequent mobility and with more connections to other professionals than in Scenarios 1 or 2. Students often work in small groups, in environments that include not only teachers but other knowledge workers. There may be a wide variety in age grading and ability mixes. ICT is widespread, as are network and communication links outside the schools to other knowledge industries and creative industries.

Scenarios 3 and 4 both display similarities to the future envisioned by the New Horizons for Learning team (www.newhorizons.org), as presented for example in (Dickinson, 2000): schools replaced by community learning centers and radically elaborated public libraries-open 18 hours a day-and early childhood parenting centers.

Scenario 5: Learner networks and the network society

Several trends that I have identified above – the diffusion of education, diverse knowledge sources, and customization – if taken to an extreme could result in a scenario in which schools as we know them become obsolete. (The OECD report refers to Scenarios 5 and 6 as “de-schooling” scenarios.) Today’s large public schools were designed in an industrial era and were based on instructionism, an outmoded model of schooling. Roger Schank (1999) and Seymour Papert (1980) have argued that computer technology is so radically transformative that schools as we know them will have to fade away before the full benefits can be realized. It may be impossible to implement alternative models of learning in the institution that today we know of as school. If today’s schools cannot adapt rapidly enough, parents may increasingly abandon schools and seek other alternatives. The flight from schools would begin with the educated classes, and also with various religious and interest groups. Under pressure from parents, politicians may follow this by reducing funding for schools and increasing funding for other options.

If education diffuses radically, schools may no longer be physical locations where everyone goes to learn; learning could take place at home, on the job, or online. Imagine a nation of online home-based activities organized around small neighborhood learning clubs, all connected through high-bandwidth internet software. There would be no textbooks, few lectures, and no curriculum as we know it today. New forms of credentialing, assessment, and competence measures could proliferate. Software, media, and publishing companies could innovate new forms of curriculum and learning delivery that could accelerate Scenario 5. “Teachers” would operate as independent consultants who work from home most of the time, and occasionally meet with ad-hoc groups of students at a learning club. Each meeting would be radically different in nature, depending on the project-based and self-directed learning that those students were engaged in. In fact, each type of learning session might involve a different learning specialist; new types of learning professionals might emerge – for example, staffing telephone or internet helplines for students, or offering home visits for short tutoring sessions.

Variations of Scenario 5 are commonly presented by education futurists; “Education 2.0″ falls in this category. Scenario 5 supports flexibility, extremely customized learning for each individual, and networked and disseminated learning. One risk, however, is that those at the lowest socioeconomic levels could be left behind in this transformation; a few schools might remain to serve these most disadvantaged students. These may or may not be well-funded institutions, depending on the commitment of society to educating even its poorest citizens.

A second challenge is how Scenario 5 could satisfy the non-classroom functions currently performed by schools: for example, providing a safe place for children while parents work during the day, providing socialization opportunities with peers. Scenario 5 could not come to pass unless other institutions emerged, in parallel with the de-schooling process, to take on these functions.

Scenario 6: Teacher exodus-the “meltdown” scenario

As in Scenario 5, schools are unable to respond to these broad societal shifts, due to institutional inertia. Public respect for schools declines, and funding drops, to the point where schools are no longer able to attract qualified teachers. As today’s teachers retire, and the knowledge society demands increasingly high qualifications for teachers, communities may not be willing to increase funding levels as necessary to attract the teachers needed in the knowledge society.

We are likely to see a wide range of responses to the teacher shortage, from innovative to traditional. One response will be to move to a deskilled teaching profession, with scripted and “teacher-proof” curricula. Other responses will include an increasing use of ICT as an alternative to teachers.

If this scenario comes to pass, educational equity will be a key challenge. For example, several futurists have predicted that automatization will accelerate dramatically so that an increasing number of jobs can be automated (Pink, 2005). This trend could combine with increased globalization such that unskilled jobs would almost all relocate to low-wage countries. The effect on advanced economies would be to create a radically tiered social structure, with a few highly paid creative knowledge workers at the top, and the great majority of the workforce having extremely limited job opportunities (apart from service sector jobs, such as waiting on tables or repairing automobiles, that are resistant to automatization and outsourcing).

In such a society, it would become politically difficult to argue that creative abilities were required of all citizens. In a difficult budgetary and funding environment, it might begin to be perceived as inefficient to invest in a learning sciences-based education for the entire workforce if only a small percentage of workers would eventually need those skills. A tiered educational system could then emerge, with a small cadre of creative and highly paid teachers educating the creative workers of the future, and a much larger cadre of relatively unskilled teachers simply executing scripted curricula.

Final challenges

I believe that some combination of Scenarios 3, 4, and 5 represent the best form of schooling for the innovation age. However, there are substantial societal and institutional forces in place that work against any transformation to such a future. To avoid Scenarios 1, 2, or 6, learning sciences researchers will have to develop four broad categories of materials, to work as a unified whole, while allowing for adaptation and customizability:

Textbooks must be rewritten (or even reconceived as laptop-based software packages), to present knowledge in the developmentally appropriate sequence suggested by the learning sciences, and to present knowledge as a coherent, integrated whole, rather than as a disconnected series of decontextualized facts. This poses substantial challenges for private textbook publishers, and for the school leaders who review and approve textbooks.

Curricular units must be prepared that are suitable for teachers to draw on and adapt to the unique needs of each classroom. These could be developed by private publishers, or a form of open-source community of educators could emerge to allow teachers to share and build on their own curricular innovations (several such communities exist online today; see Fishman and Davis, 2006).

Educational software that is based on learning sciences principles must be made commercially available. This poses substantial challenges for the private companies that develop such software. Exciting new learning applications are emerging from university research laboratories, but few of these are being developed into commercial products – in large part, because other aspects of schools, identified in this report, also need to change before such applications can be successfully implemented.

Assessments must be developed that assess deep knowledge instead of surface knowledge, and to take into account the fact that due to customization, different learners might learn different subject matter (Pellegrino, Chudowsky and Glaser, 2001). These new forms of assessment do not yet exist, and a clear vision of how such tests would be constructed has not yet emerged from learning sciences research. A critical issue for the future is to continue this work. Test construction is complex, involving field tests of reliability and validity for example, and will require learning scientists to work with psychometricians and policy experts (Pellegrino, Chudowsky and Glaser, 2001).

In addition to these scholarly challenges, an even bigger challenge to assessment reform is likely to be political. It will not be easy to convince those government bodies responsible for educational assessment to transition to these fundamentally new assessments-in no small part because parents may resist the use of tests that look very different from the ones they experienced in school. A further political difficulty is that during the transition period to learning-sciences based classrooms and deeper forms of assessment, there is likely to be a period of several years during which different children are likely to excel at the new assessments than at the old. Those parents whose children seem to be disadvantaged by lower scores are likely to actively resist the new assessments.

Conclusion

We are entering the innovation age. In the decades ahead, as the nations of the world respond to the demand for innovation, creativity will be increasingly valued. There are no forces at present, and none potentially on the horizon, that would result in a return to an industrial-age economy; no forces that would reduce the importance of creativity to society and the economy.

However, the innovation age could unfold along a broad range of paths. The most humanistic, liberal view is of a world where all people realize their full creative potential through effective educational institutions and work environments, and find fulfillment through creative work and creative leisure activities. However, a more class-based outcome is also possible – a world in which a small creative elite is capable of generating sufficient innovation to grow the economy, with the remainder of the workforce continuing to engage in scripted, process-managed, uncreative work.

Based on my best understanding of innovation research, I believe that this pessimistic outcome is unlikely – because the most innovative companies are those that foster and demand innovation from all of their employees, rather than a small elite. Decades ago, many industrial-age companies had a research and development team that functioned as a creative elite; all new ideas were expected to come from this team, and the rest of the company was simply expected to execute, to follow instructions with almost no creativity required. In recent decades, this model has proven to be ineffective, and the most innovative companies have shifted to organizational designs that foster creativity throughout the organization.

To maximize innovation and knowledge generation, many societal factors must be in alignment. In closing I emphasize two: first, the broader society must foster knowledge communication and dissemination, through enhanced social networks, transportation infrastructures, and communication technologies. Second, learning must be available to all citizens throughout the lifespan, and this learning must be designed to support creative behaviour. At present, many schools (and corporate learning programmes as well) are based in an cultural model of teaching and learning that I have called the “standard model.” I have argued that the standard model does not result in learning that supports creative behaviour. Fortunately, research emerging from the learning sciences is showing how to design learning environments that result in creative learning.

I have identified a range of challenges that must be overcome before schools and other organizations can successfully redesign learning environments on learning sciences principles. For the future of creativity and innovation, it is critical that societies overcome these challenges and build creative classrooms designed for the innovation age.

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This document has been commissioned as part of the UK Department for Children, Schools and Families’ Beyond Current Horizons project, led by Futurelab. The views expressed do not represent the policy of any Government or organisation.

Continuing mortality improvements at older ages

Mortality rates in the UK are declining at all ages and for both sexes, just as they are in the rest of the developed world. With every year that passes, there is an increase in the proportion of successive birth cohorts that reaches retirement age, and an increase in the likelihood of surviving to enjoy that retirement for several years. Declining mortality at older ages is one of the main drivers of the growth in the relative size of the older population. By 2025 one in five people in the UK population will be aged 65 years or more. By 2050 it will be almost one in four.

Since most deaths now occur in later life, it is the continuing improvement in late life mortality that is contributing most to increasing life expectancy at birth. Over the last 20 years in the UK, male life expectancy at birth has increased by 5.6 years, ie at an average rate of more than three months per year, with most of the gain accruing to men past the age of retirement. Four of those additional life years have been added to life expectancy at the age of 65. Death rates in older men have not only fallen sharply in this time – by almost one half in the 60-69 age group and one third in the 70-79 age group – and from relatively high levels, but the decline in death rates has actually been accelerating, which accounts for the more or less linear increase in life expectancy. The average annual rate of improvement between 2000 and 2005 was twice as high as it was in the late 1980s. Death rates among older women have followed a similar trend, though the gains have been not quite so large.

Is this pattern of accelerating mortality improvements apparent in the data for the oldest-old – the population aged, say, over 80 years – as well as for people in their 60s or 70s? For men aged 80 to 90 years, it seems that it is, but not for men in their 90s, or indeed for women in either the 80-89 age group or the 90-99 age group (Pensions Commission, 2005). However, contrary to the expectations of some analysts writing in the 1980s and 1990s, there is no sign yet of a stagnation in mortality gains among the oldest segment of the population, certainly not in the UK (or Japan or France), nor even of a slowdown in the rate of improvement. Clearly then, there is no evidence in these data for the view that life expectancy in affluent countries is approaching any kind of limit, let alone the limit of 85 years estimated by Fries (1980) and reaffirmed by Carnes and Olshansky (2007).

It is these recent trends in mortality that form the basis of current official forecasts for future life expectancy, and they have been sufficiently striking to prompt the Government Actuary’s Department (GAD) to change its assumptions about the trajectory of future mortality improvements. Where the 2000-based projections assumed that annual improvements in mortality rates would converge toward ½% at each age for both males and females by the year 2032, the latest forecasts reckon that annual rates of improvement will converge to 1% for most age groups, which is equivalent to the average annual rate of improvement for the 20^th century.

Earlier forecasts were further shaped by the assumption of an eventual slowdown in mortality improvements, which has now been dropped. Hence we find that forecasts of future life expectancy have been revised upwards both in the medium term and in the longer term. Over the next twenty years female life expectancy at age 65 is forecast to grow even more quickly than it has done over the last 20 years (3.4 yrs as against 2.6); and there will be only a slight dip in the rate of increase for men over the same period (3.6 years as against 4 years). Thereafter the projected trend in mortality improvements entails a marked slowdown (and convergence) in the rate of increase for both sexes. Between 2028 and 2048 life expectancy at age 65 years will increase by 1.8 years for men and 1.7 years for women.

Variations and inequalities in mortality risk

The gender gap in life expectancy is narrowing

The life expectancy of a 65 year old woman in the UK is now 19.7 years, almost 3 years longer than that of a 65 year old man. It is not surprising, then, that among the oldest age groups in the population (eg 85 years+) women outnumber men by more than two to one, nor that nine out of every ten centenarians in this country are female.

Over the course of the 20^th century, in common with most other developed countries, the gender gap in life expectancy in the UK first widened, and then in the 1970s and 1980s started to narrow (Gjonca et al, 2005). Mortality rates for men are falling faster than mortality rates for women. If these trends continue, which is what GAD expects, the ratio of men to women in the older population will of course increase, and this means that an increasing proportion of older women will have surviving husbands. Japan and Russia are notable exceptions to this pattern (ie the sex gap in life expectancy has increased over the last 20 years). In Japan, the widening gap appears against a background of improving life expectancy for both sexes whereas in the Russian Federation life expectancy has actually declined.

Social inequalities in life expectancy are widening

One of the most notable features of recent trends in mortality in affluent countries is that a pattern of international convergence in life expectancy overlays a pattern of widening within-country variation of age at death, much of which is thought to be explained by socioeconomic differences in mortality risk (Edwards and Tuljapurkar, 2005). In the UK, as in most of Europe (Mackenbach et al, 2003) and the US (Meara et al, 2008) over the last couple of decades, the increase in life expectancy has been accompanied by widening socio-economic inequalities in mortality . Although mortality rates have been decreasing at both ends of the social scale, they have been decreasing much more quickly in the upper socio-economic groups.

Here in the UK, data from the ONS Longitudinal Study show that, in the years between 1972-5 and 2002-5, the gap in life expectancy at age 65 between men in manual and non-manual occupations doubled from 1 to 2 years. The gap between men in the highest and lowest of the Registrar General’s occupational classes now stands at 4.2 years, with unskilled manual workers having more or less the same life expectancy at pensionable age (14 years) as professionals did in 1972-5 (ONS, 2006). The trends for women are the same.

A similar pattern is apparent in analyses of deaths in the British Regional Heart Study (Ramsay et al, 2007), as well as in many studies of trends in geographical inequalities in mortality. Although the risk of premature mortality (< 75 yrs) has declined everywhere in the UK over the last 25 years, the difference between the authorities with the highest and lowest probabilities of surviving beyond 75 has increased (Wells and Gordon 2008). A similar conclusion is reached by Leyland et al (2004), though he uses a lower threshold to define premature mortality (< 65 years). Between 1979 and 1998, premature mortality decreased by 36% in Great Britain as a whole. Over the same period inequalities in the risk of premature mortality increased not only between regions, but also within most regions of the country. The excess premature mortality associated with living, for example, in London increased from 14% to 19%.

Changes in cause-specific mortality

One common factor in analyses of trends in cause-specific mortality over the last half-century, not only in the UK, but in all of the developed world, is the contribution of declining mortality from cardiovascular/circulatory diseases to overall mortality decline. It has been estimated, for example, that reduced CVD mortality contributed more than 5 of the 8.8 years added to life expectancy at birth in the USA since the middle of the 20^th century (Cutler, 2004). In the USA, as in the UK, it is the decline in mortality from heart disease that has contributed most of the decline in CVD mortality – mainly because a much larger proportion of deaths were (and still are) caused by heart disease than by stroke.

In the UK, over the last ten years (1995-2005), the age-standardised mortality rate for CHD fell from 94 to 48 per 100,000; with death rates falling by about one half in both the 55-64 year age group and the 65-74 age group. If these trends were to continue, we could expect to see the end of premature mortality from CHD. Whether or not that will happen over the next few decades is unclear. A recent analysis of trends in CHD mortality in younger adults – they appear to be flattening out – suggests that increases in obesity may be starting to offset the decline in other risk factors among younger cohorts (O’Flaherty et al, 2008).

For the other main cause of death in the UK, cancer, the picture is quite different, and more complicated. Taken as a whole, age-standardised mortality from cancer changed very little in the second half of the 20^th century (Quinn et al, 2001), although more recently, mortality rates have declined substantially (10-15%) among both men and women (Westlake and Cooper, 2008). Cancer incidence, however, declined by only 1% between 1993 and 2004, and it actually increased among women (with breast cancer accounting for much of the increase). For men, the main source of the downward pressure on cancer mortality is the fall in mortality from lung cancer, and this is due to declining incidence. With breast cancer in women and prostate cancer in men, on the other hand, the drop in mortality has occurred in spite of increasing incidence.

Increasing healthy life expectancy

In the early 1970s it was feared that a combination of increasing longevity and the intractability of the major degenerative diseases of later life would lead to an expansion of morbidity (eg Gruenberg, 1977). If gains in life expectancy at older ages were being driven mainly by the increasing capabilities of medicine to postpone death in people with serious illness, then the average person should expect to spend more years living with a heavy burden of disease and disability. What is now clear is that age-related disease is not as intractable as was then supposed. There are established and effective strategies to reduce the risk of onset for many kinds of chronic disease as well as effective interventions to delay the progression of disease and minimise associated disability. There is also growing evidence that the onset of age-related ill health and disability is in fact being postponed to older ages across whole populations. What is being postponed, in other words, is the need for medical intervention to deal with the more serious problems of age-related disease and disability. At least this is what seems to be happening in some developed countries and for some forms of age-related disease and disability.

There are distinct questions to ask here. We can ask, for example, whether or not the number of years that we can expect to spend in a healthy (or active) state is increasing. We can also ask whether it is increasing as fast as life expectancy. Or is it increasing even faster, which would mean that there is a compression of the time spent in serious ill-health or disability at the end of life?

The evidence for ongoing improvements in healthy life expectancy in the UK (ie the first question) is now quite strong. Or at least this is the case for cardiovascular disease, which is, after all, not only the main cause of death in later life but also a major cause of late-life disability. Trend data for the age-specific incidence of disease (eg first coronary attacks or first strokes) confirm that the average age of onset is climbing up (Davies, 2007; Rothwell, 2004). Estimates of the relative contribution of medical care and changing levels of population risk factors to declining mortality from CHD tell the same story, though from a slightly different angle. The kind of evidence that can give us a more rounded picture of health status is, however, more equivocal. Data from the General Household Survey, for example, on self-perceived health suggest that we are keeping our health for longer (although it seems that increases in healthy life expectancy are not keeping pace with improving life expectancy). There is, on the other hand, quite a lot of evidence to suggest that the prevalence of chronic disease and related health problems is increasing in the older population, and this is not just because the older population is itself ageing. A recent analysis of the MRC CFAS dataset found that the prevalence of chronic disease is increasing in successive cohorts of the younger-old (65-69 years), though it is admittedly very difficult to be sure that most of this change cannot be explained by improved detection and earlier engagement with medical care (Jagger et al, 2007).

The evidence on trends in late-life disability is, if anything, even more problematic. Although there are some affluent countries which do show clear evidence of favourable trends in late-life disability (often in spite of an increasing prevalence of self-reported health problems and diseases), the UK is not one them (Lafortune et al, 2007). And since there is no firm evidence for increasing disability-free life expectancy in the UK, there can be no firm evidence to suggest that the functional status of the older population is improving enough to bring about a compression of disability.

Key uncertainties and potential discontinuities in longevity trends

Demographic uncertainty

Demographic forecasters make errors, not because their methods are inadequate to the task in hand, but rather because the future trajectory of mortality is inherently uncertain. We may be confident, and reasonably so, that mortality rates in the older population will continue to decline over the 20 years, but we cannot be so sure of the accuracy of our estimate for the average annual rate of improvement, that it will be 2%, for example, rather than 1.5% or 2.5%. GAD, which for many decades has persistently under-estimated mortality improvements in the older population, captures some of the uncertainty in forecasts of life expectancy through its use of variant projections. Since the likelihood of forecasting error increases with the length of the projection period, the gap between the high and low variant forecasts for life expectancy increases over the course of the century. In the 2006-based projections, there is a 2.6 year gap in 2025 between the upper and lower estimates for life expectancy at birth for men; by 2050 it opens up to 8 years (and for women it increases from 1.6 years to 6.3 years). Although the trend line for the principal projection lies of course between these limits, GAD’s current methodology gives us no mathematical handle on the probability that it will in fact fall within that range. All we can say is that it most probably will (and, of course, that the future is more likely to correspond to the principal projection than to either of the variants).

It seems very unlikely, for example, that life expectancy will start to decline after 2038, which is the boundary set by the low variant forecast (ie it assumes that life expectancy remains constant after that date). But it is not altogether inconceivable that it might start to fall some time between 2025 and 2050, and precisely this outcome has been assigned to a worst-case scenario for the obesity ‘epidemic’ in the USA (Olshanksy et al, 2005). Nor does it take much casting around to find other potential causes of such an outcome, such as a catastrophically bad influenza pandemic. As for the high variant forecast, this corresponds quite closely to a continuation of the more or less linear trend in improvements in life expectancy noted by Oeppen and Vaupel (2002) for a times series of data from so-called ‘best practice’ countries. If, however, we assumed that the trend in life expectancy projected for the UK for the next 20 years were to continue up to 2050 (ie an average annual increase of about 3 months per year), then life expectancy at birth in 2050 would exceed the high variant forecast. Once again this may be an unlikely outcome, but it is not altogether inconceivable.

Optimists and pessimists

We cannot be sure that future changes in mortality rates will be the same as those we have seen in the recent past, but unless we have any reason to think otherwise, our best bet is to assume that they will. This may be a good rule-of-thumb, but when it comes to deciding on its application to the future of human mortality in the 21^st century, it leaves some important basic issues unresolved. In particular, there is the question whether we have good reason to think that future changes in mortality rates will not be the same as those we have seen in the recent past. And this question may in turn be asked in various ways depending on which stretch of the recent past we are considering for extrapolation into the future. Do we have any reason to think that gains in life expectancy in the 21^st century will be less than those seen in the 20^th century? Do we have any reason to think that the pattern of gains in life expectancy seen in the UK over the last 20 years will not continue? More generally, we can ask whether we have any reason to think that the rate of mortality improvements at older ages is more likely to slow down than continue on its present trajectory. The kinds of answers that demographers and experts on human mortality give to these questions may be divided into four broad categories. At the extremes there are two scenarios which ‘foresee’ a fairly radical departure from recent trends, or at least they argue that such a discontinuity is much more likely than most demographic forecasters are inclined to suppose.

The pessimistic scenario assumes that the increasing prevalence of obesity in cohorts that are still relatively young or in middle age will have a very substantial impact on their mortality in later life, large enough in fact to reverse the long-term trend in life expectancy. We are to suppose that the full impact of obesity on mortality will turn out to be not very different from the impact of smoking on mortality. What distinguishes this particular pessimistic scenario from the risk of catastrophes that hit us, as it were, ‘out of the blue’, is the availability of evidence on current trends in obesity as well as estimates of the impact of obesity on mortality, which together enable a projection to be made. The basis for the scenario, in other words, is found in present trends. What makes it an especially pessimistic scenario (rather than a merely realistic assessment of the likely impact of obesity on life expectancy) is (i) the choice of the most pessimistic of the range of current estimates of the relative mortality risk associated with obesity and overweight, and (ii) a likely under-estimate of the effect of countervailing changes in lifestyle, especially the decline in smoking prevalence.

At the other extreme there is what we might call a super-optimistic scenario, which reckons on our ability to develop and apply the means of overcoming whatever limits the process of biological ageing puts to human longevity soon enough to have an impact on the evolution of human longevity in this century. Should this happen, then (so the argument goes) we should expect to see a rapid acceleration in gains in life expectancy, and there is no reason why the average age at death should not exceed the maximum observed human lifespan (approximately 125 years) before the end of the century. What makes this a super-optimistic scenario is that it offers us a reason to think that the future trends in mortality will depart quite radically from historical trends. The gains in mortality that would be required to achieve this scenario exceed anything that could be derived from the extrapolation of current trends.

Even among the majority of demographers who would reject these ‘extreme’ scenarios as highly unlikely, there remain important differences of opinion on the question whether life expectancy in affluent countries is approaching a limit; and if it is, whether this has any relevance for attempts to forecast the short- to medium-term future for mortality. For the sake of simplicity, and following Carnes and Olshansky (2007), they may be divided into realists, who argue that the rate of mortality improvements is more likely to slow down than continue on its present trajectory, and optimists, who forcefully reject the idea that we have any reason to suppose that this will happen in the foreseeable future.

The difference in practical terms between realists and optimists is large. Where Carnes and Olshansky think that combined life expectancy is unlikely to exceed 85 years, Oeppen and Vaupel (2002) puts it at 100 years by the end of the century. The key to this difference lies in differing assessments of the relevance of what is known about the ageing process to the assumptions that demographers make about the future of mortality. Carnes and Olshansky (2007) argue that humans, like other organisms, “are subject to the biological equivalent of a warranty period”. This is not to say that we cannot survive beyond our ‘warranty period’; the point is rather that the probability of death increases sharply the longer we survive beyond it. What the optimists dispute in this is not just the rate at which the probability of dying increases in later life, or the estimate of the ‘warranty period’ for humans, or indeed whether the idea of a warranty period is at all useful. The fundamental division of opinion turns on the question whether the constraints that biological ageing imposes on human longevity are going to become apparent in the mortality data soon enough at least to influence the assumptions of demographic forecasters.

Convergent or divergent trends in differential mortality risk?

Will social inequalities in life expectancy continue to increase?

Uncertainty about what is going to happen to social differentials in mortality risk is presumably at least as great as the uncertainty about overall trends in future mortality. If we suppose that there are practical limits to life expectancy which rich countries like the UK are fast approaching, then we would expect soon to see a slowdown in the rate of increase in the mean age at death and a compression of mortality around the mean (Fries 1980). In effect, most of the future increase in the mean would be achieved by a narrowing of social inequalities in mortality. It is assumed, on this view, that the benefits for life expectancy of good early life nutrition and healthy living have been more or less fully realised by a substantial minority of the population. Future cohorts in similar circumstances may still gain more in this way, but not much. There is, however, still a large gap to be closed between them and the rest.

The problem with this view, however, is that it is not supported by the evidence. To be sure, GAD forecasts a slowdown in the rate of increase in life expectancy between 2025 and 2050, and this may be accompanied by a compression of mortality (and a narrowing of social differentials). As we have already noted, however, current trends in social differentials provide no evidence for this. Quite the contrary. And this is despite a considerable effort on the part of government to do something about it. If we decided to follow, for this particular case, GAD’s standard approach to projection, we would presumably forecast a further widening of social inequalities in mortality. Given the determination of government to reverse this trend, the question we have to ask is this: how confident can we be that government efforts to narrow social inequalities in mortality will be successful before 2025 or 2050? Or should we suppose that they will be no more successful over the next 20 years than they have been over the last 10 or 15?

The future of the gender gap in life expectancy

The gender gap in life expectancy decreases by about 20% in GAD’s principal projection for 2050, and by more than a third in the high variant. Only in the low variant does it actually increase. If we take the high and low variants as the outer limits for likely outcomes, then the gender gap in life expectancy could be anywhere between 2.4 and 4.2 years by 2050. It is worth noting, moreover, that the continuing decrease seen in the principal projection happens in spite of an assumed convergence between male and female rates of mortality improvements: gains in female life expectancy will accelerate as gains for men will slow down (ie without this assumption the convergence would be much greater).

Since male-female life expectancy fails to converge only in the low variant forecast, it is perhaps worth asking how unlikely it is that we will have much greater gains in life expectancy than are forecast in this variant along with a lack of convergence in male and female life expectancy. The point has already been made that GAD’s methodology does not allow us to assign a number to the probability of this kind of outcome. However, as with Olshansky’s pessimistic scenario for the impact of obesity on future trends in life expectancy or Vaupel’s best-bet forecast of linear increases in high-performing countries, such an outcome does not seem so unlikely as to fall outside the limits of serious consideration (wherever they are).

Are we on the verge of an epidemic of frailty?

Just as there are optimists and pessimists about the future of mortality over the next few decades, so also are there optimists and pessimists about the likelihood of achieving a compression of morbidity (or disability) when life expectancy is continuing to increase by more than two months per year. Although current trends in old-age disability in the USA give grounds for optimism, here in the UK they look less favourable (Lafortune, 2007).

Even in the USA, however, it would be unwise for policy-makers to discount the risk of a slowdown in current rates of improvement in the prevalence of disability. Nor is it sufficient that disability rates continue to decline for there to be no expansion of disability (ie the amount of time that the average person spends in a disabled state at the end of life). If future increases in life expectancy outpace future increases in active (or disability-free) life expectancy, there will be an expansion of disability. The prospects for a compression of disability depend, therefore, not only on what happens to disability rates, but also on what happens to life expectancy. An increase in the prevalence of disability may look unlikely on current trends, but there is a risk, for example, that the effects of obesity will be sufficient to reverse them; and there is also the risk that gains in life expectancy at older ages exceed the current ‘best estimate’ of forecasters.

Useful as it is, however, to make this kind of broad distinction between a future compression of disability and a future expansion of disability, there are other possible scenarios for the evolution of the relationship between increasing life expectancy and increasing active life expectancy. It is possible, for example, that increases in active life expectancy will keep pace with increasing life expectancy, so that there will be neither a compression nor an expansion of disability.

It is also important to take proper account of the distinction between more and less severe states of ill-health and disability. If we suppose that current gains in life expectancy are strongly dependent on improvements in the secondary prevention of fatal chronic disease in later life, then although we should expect an expansion of morbidity, this will result from an expansion of the time spent with relatively mild and ‘manageable’ health problems, not from an expansion of time spent in a severely disabled or seriously ill condition.

The original prediction of an imminent compression of morbidity (Fries 1980) was based on the conjunction of two hypotheses: firstly, that the main driver of the current gains in life expectancy at older ages was an underlying improvement in health which has enabled people to remain free of potentially fatal chronic disease for longer; and secondly, that life expectancy was approaching its limit. As we have seen, there is no evidence yet of a slowdown in gains in life expectancy. Even, therefore, if the first hypothesis is right, there is no reason in theory to predict a compression of morbidity in the foreseeable future unless we also predict a slowdown in gains in life expectancy.

Suppose, then, as seems quite likely, that most of the current gains in life expectancy at older ages are due to a combination of improved secondary prevention of fatal chronic disease and underlying improvements in health. Can we be reasonably confident that if this is true, there will be no expansion of (severe) disability? According to Manton et al (1991), and the hypothesis that increasing life expectancy is in a state of ‘dynamic equilibrium’ with morbidity and disability in later life, we can. Not everyone, however, would agree. A good deal turns on the relationship between patterns of delayed onset and progression for different categories of chronic degenerative disease. If age-specific patterns of risk for the major fatal chronic diseases of later life (eg circulatory disease) are changing faster than the patterns of risk for severely disabling but non-fatal conditions, then the prospect of extended survival is likely to expose individuals to an increasing risk of disabling and age-related functional loss.

How longevity trends intersect with developments in

The drivers of mortality decline

“Gains in longevity are the result of a complex array of changes (standards of living, public health, personal hygiene, and medical care), with different factors playing major or minor roles in different time periods” (Wilmoth, 2000). Most analysts would accept that medicine made a relatively small contribution to declining mortality until the second half of the century, or perhaps even as late as the 1970s, after which it started to make a big difference (Bunker, 2001). It seems clear, for example, that the secondary prevention of heart disease through more effective medication and improved surgical techniques has had a substantial impact on the mortality of people with diagnosed heart disease (Jeune, 2007), and they are, after all, a large proportion of the older population. Whether or not medical interventions have contributed more to declining mortality over the last 20 years than social change or lifestyle change is not so clear. Certainly for heart disease there is an impressive body of analysis which argues that improvements in medical care account for less than half the decline in mortality in recent decades (Unal et al, 2004), though a rather different view of the impact of medical intervention emerges from some recent analyses of the contribution of pharmaceutical innovation to mortality decline (Lichtenberg, 2007).

What is at issue in these different estimates is the balance between the various components in the array of forces driving down mortality in the recent past, and even if we were to suppose this issue settled, we would still have to consider how this balance might change in the foreseeable future. There are two broad questions we might ask here. Firstly, how much life expectancy can we expect to gain in rich societies without the ever more intensive application of expensive medical interventions? Secondly, should we expect over the next few decades an increase in the life expectancy gains made as a result of the widespread application of biomedical innovation (and if so, how)?

Social change and changing lifestyles

The question of how much life expectancy we can expect to gain in rich societies without the intensive application of new medical technologies has been tackled in various ways. One approach involves an assessment of the impact of the increasing diffusion of what Carey (2003) calls ‘healthful living’ on mortality. Although Carey himself argues that social and lifestyle change probably has a rather small and diminishing contribution to make to future longevity gains, there are others who take quite a different view. The effects of the continuing recession of the 20^th century smoking epidemic may be the most obvious candidate for this kind of exercise, but there are of course other factors besides smoking which have a measurable impact on mortality risk. It has been estimated, for example, that a modest reduction in risk factor levels for CHD in the general population could reduce CHD deaths in the UK by nearly one half within a policy-relevant time frame (Kelly and Capewell, 2004). An alternative approach would be to estimate the effects on population life expectancy of the elimination or narrowing of social inequalities in mortality. What would happen, for example, to population life expectancy if standardised mortality ratios for the lowest income groups were the same as those for the highest (Manton et al, 1990)? More generally, we could assess the impact of narrowing the gap in life expectancy by eg 50% or 75%.

The role of smoking

Smoking is the single largest cause of preventable deaths in the UK (Davy, 2007), accounting for approximately one in six of all adult deaths in England in 1998-2002 (Health Development Agency, 2004). Since the gap in life expectancy at birth between the average non-smoker and the lifelong smoker is estimated at about 10 years (Doll et al, 2004), it not surprising that smoking should be widely regarded as the largest single determinant of the substantial variations in mortality that are found (i) between men and women (see eg Pampel, 2003), (ii) between different socioeconomic groups (see eg Law and Morris, 1998), and (iii) between different geographical areas (see eg Mackenbach et al, 2008). It is hard to exaggerate the importance attached by many demographers and epidemiologists to smoking behaviour in explaining changing patterns of mortality in the developed world in the second half of the 20^th century.

Smoking patterns that appear early in life of a cohort have very large effects on mortality several decades later. In many countries the spread of smoking in cohorts born at the beginning of the 20^th century acted as a substantial drag on the mortality declines that might have been expected from post-war improvements in living standards and health care (Janssen et al, 2007). As the smoking epidemic recedes, we should therefore similarly expect an acceleration of mortality declines in places where the proportion of smokers in cohorts reaching later life continues to fall. There are good reasons, therefore, to think that the continuing decline in smoking prevalence is likely to be one of the main drivers of gains in life expectancy in the developed world over the next 50 years.

Human and physiological capital

There are two other potentially important sources of continuing gains in life expectancy which are largely (but not entirely) independent of innovation in biomedical technology; firstly education, and secondly what economist Robert Fogel (2003) has called the accumulation of ‘physiological capital’.

The idea that improvements in the general level of education in society is a important driver of increasing life expectancy has its origins, partly in the well-established link between socioeconomic status and differential mortality risk, and partly in the idea that higher levels of education are associated with an increased ability to negotiate the challenges and hazards of modern life in a highly urbanised and technologically-oriented society (ie more ‘know-how’). What is gained from more education is not just a higher standard of living. Better educated individuals are more in control of their lives, which means inter alia that they are more in control of the various factors in the social and material environment which influence their own health status (Cutler et al, 2006).

The idea that the accumulation of ‘physiological capital’ early in life has large benefits for late-life health and mortality builds on the now familiar idea that nutrition in utero and in early childhood has a substantial and long-lasting impact on health via their influence on the formation of essential physical structures in the developing organism (Barker, 1995). As a result of improved nutrition in early life, more recent cohorts in the developed world are not only better able to resist infectious disease than their parents and grandparents, but also benefit from a delay in the onset of the chronic diseases that cause ill-health and death later in life. One of the key pieces of evidence to which Fogel appeals in developing these views is trend data on birth weights and adult heights. Essentially we are getting taller – which is a good marker for the improved development of internal organ systems – and there is, he thinks, a demonstrable link between adult height and mortality risk (see eg Langenberg et al, 2005). The fact there is no evidence of any deceleration in this particular trend, certainly in Europe, suggests furthermore that we should expect no weakening in the force of this source of mortality reductions (Fogel and Costa, 1997). At the very least, we might look forward to a narrowing of socioeconomic differences in adult height, and given the link between adult height and mortality risk, this would lead us to expect a narrowing of social inequalities in life expectancy.

Innovation in medicine and biotechnology

Most deaths in old age are caused by cancer, heart disease and stroke. Individualised interventions which aim to delay or halt the progression of these life-threatening diseases account for much of the medical care that is now provided in our society, and an enormous amount of research effort is devoted to developing more effective interventions. Innovations in new fields such as pharmacogenomics and nanotechnology clearly have the potential to provide some of the additional power that is needed to maintain current momentum in what Carey (2003) calls ‘disease prevention and cure’ as a driver of mortality improvements in later life. The magnitude of the gains in life expectancy that may be achieved by such developments should not be over-estimated, however. If we suppose that more effective treatment were to reduce cancer mortality as dramatically over the next two decades as mortality from heart disease has fallen over the last 20 years (ie by about 50%), this would add not much more than a couple of years to life expectancy at birth.

Can we expect to find therapeutic innovation anywhere other than in the development of technologies which offer the prospect of improvements in disease prevention and cure? Carey (2003) himself answers this question by identifying two quite distinct potential drivers of future improvements in mortality: regenerative medicine; and age-retardation. The implication of the distinction is that the development of these technologies would represent an important ’step-change’ in the capabilities of biomedicine to extend healthy lifespans. How likely is it that gains in life expectancy can be maintained on their current trajectory without such a step-change? Olshansky and Carnes (2007), for example, take the view that we should expect a slowdown in mortality improvements unless there is a radical breakthrough in our ability to control the process of biological ageing. They doubt whether Oeppen and Vaupel’s optimistic forecasts for the future of life expectancy in this century can be realised simply by the wider diffusion of healthy living and improved disease prevention and cure.

Since the aim of regenerative medicine is to develop therapies which will restore lost, damaged or ageing cells and tissues in the human body, it seems clear that it has the potential to make a significant contribution to future increases in life expectancy at older ages. As ever in such cases, it is important to distinguish between outputs that might reasonably be expected in the short term, and the more speculative long term promise. The hope that stem cell therapy might be used, for example, to repair damaged heart tissue or to ‘cure’ diabetes lies in the longer term future (DHHS, 2006).

‘Age-retardation’, as it is now generally understood, would represent a step farther even than the ability to repair ageing or damaged tissue and cells in various body systems. Effective age-retarding interventions would stand to regenerative medicine rather as prevention stands to cure. Where regenerative medicine aims to remedy age-related decline in cell and tissue function by repair or replacement, age-retarding interventions would aim to prevent or slow down the processes that underlie that age-related decline in function (President’s Commission on Bioethics, 2003). Once we assume that such interventions are feasible, there is no reason why life expectancy should not eventually exceed the current maximum observed lifespan, and it is this conclusion which has prompted discussion of their social and ethical implications.

Range of potential futures these trends might point to from present to 2025 and 2050.

Greater or smaller gains in life expectancy

What are the main scenarios for longevity apart from the range of trajectories for life expectancy that is bounded by the high and low variant forecasts made by GAD? If we follow Oeppen and Vaupel (2002) in thinking that it is feasible that there should be a more or less linear increase in life expectancy in best-practice countries for most of this century, then it is important to add this optimistic scenario to the range of possible futures for longevity. By the same token, though this does depend on contested assessments of the likely impact of the so-called obesity epidemic on mortality, it seems excessively complacent to discount altogether the risk of a pessimistic scenario in which life expectancy actually starts to fall as younger (and more obese) cohorts start reaching later life, say from 2030 onwards.

A rather different approach to the construction of possible futures for life expectancy in the UK was adopted by the Wanless review on the future of NHS spending (Wanless, 2002). The key variables in this case were (i) the public’s engagement with their own health (ii) the achievement of public health targets, and (iii) health service productivity. Solid progress in these respects would produce life expectancy gains in line with what was then GAD’s high variant forecast. Slow uptake would lead to gains in life expectancy that correspond to GAD’s principal forecast. The fully engaged scenario, however, is associated with mortality improvements beyond what is achieved even in the high variant forecast. The interest of this set of scenarios lies partly, therefore, in the fact that one of the projected outcomes falls outside the boundaries set by GAD’s high and low variants, and partly in the way that movements in mortality trends are connected with opportunities for policy action by government.

Variability in mortality risk

Quite distinct from the question of the magnitude of the gains in life expectancy that might be achieved between now and 2050 is the question of variability in mortality risk. What will happen to (i) the gender gap in life expectancy, and (ii) socioeconomic disparities in life expectancy?

In the GAD variant forecasts male-female life expectancy fails to converge only when life expectancy gains stagnate. In view of this fact, it would seem desirable at least to consider a scenario which combined moderate gains in life expectancy with an increase in the gender gap in life expectancy. In other words, life expectancy would continue to increase for both men and women, but there would no significant increase (or perhaps even a decrease) in the ratio of men to women in the oldest-old population.

The GAD variant forecasts have nothing to say about future trends in socioeconomic disparities in life expectancy. The present government target for reducing inequalities in life expectancy at birth runs to 2010 (a 10% reduction between 2003 and 2010 in the life expectancy gap between local authorities). Whether or not it is likely that our society will achieve proportionately ambitious targets for 2025 and 2050 is open to question. These are nonetheless the benchmark scenarios against which governments should presumably measure their long-term success in reducing socioeconomic disparities in life expectancy. The worst-case scenario is that the relative difference in mortality rates between high and low socioeconomic groups will continue to increase.

More or less disability and ill-health in later life

There are two ways of constructing scenarios for the future of disability and ill-health in the older population. If we want simply to clarify the range of possible outcomes for the interaction between changing life expectancy and changing active life expectancy, we should think in terms of the expansion or compression of disability and ill-health as worst- and best-case scenarios. The most commonly discussed intermediate scenario foresees some increase in the time spent with mild (and relatively manageable) health problems and a stable or decreasing amount of time spent in a severely disabled state.

The approach adopted by most projections for the future of disability and ill-health in the older population is different from this. The scenarios generated by these projections involve an estimate of the numbers of severely disabled or dependent older people in the population based on combinations of alternative trajectories for (i) trends in life expectancy and (ii) trends in age-specific prevalence rates for disability and dependency. This is the kind of approach taken by the PSSRU model for projecting future expenditure on long-term care (eg PSSRU, 2004), and the recent OECD projections on the future of old-age disability (Lafortune, 2007). We can ask, for example, what happens if age-specific prevalence rates:

• remain unchanged and life expectancy grows more quickly than GAD’s principal projection (this is the most common worst-case scenario)
• follow current trends (which generates a positive scenario if rates have been decreasing as they have done in the USA over the last 10 or 20 years)
• decrease in line with optimistic expectations about improving health (eg at an average rate of 1% per year).

A more sophisticated approach to generating the same kind of outcome is used in the scenarios prepared by Jagger et al (2006) for the Wanless review of social care. They outline three basic scenarios:

• a no change scenario which assumes that the age-specific prevalence of disabling chronic disease will remain unchanged. This is not to say that preventive efforts will be ineffective. They will be effective, but only enough to offset the negative impact of obesity on the health and functional status of cohorts that are now still relatively young.. The incidence of dependency will stay the same and mortality rates will decline in line with GAD principal projections.
• a poorer health scenario assumes that current trends in obesity will continue (which means an increase in prevalence of about 2% per annum). This problem will be compounded by the ageing of large ethnic minority populations, which will add to the prevalence of CHD and stroke. Preventive strategies will only partially offset these trends.
• an improving health scenario, which is not that different from the fully engaged scenario for life expectancy. There will be a decline in smoking prevalence and obesity as individuals take their own health more seriously. Health services will be responsive to demand with high rates of technology uptake for disease prevention and excellent rates of diffusion of treatment. Mortality will decline more quickly than in the GAD principal projection.

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Over the last 20 years the chances of a 65 year-old women reaching the age of 80 have improved from 61% to 71%. Although the odds for a 65 year old man are not so good, they are still better than evens (59%), and much better than they were 20 years ago (41%).

This is not true for all developing world. Some countries, such as the USA and Netherlands, have experienced relative stagnation in mortality improvement, especially among women (Mesle and Vallin).

In 1981, the gap in life expectancy at birth was 6 years. In 2006 it was 4.3 years, which is relatively low for a rich country at the beginning of the 21^st century.

The relative gap in death rates between upper and lower socio-economic groups has grown more in northern Europe (inc. the Nordic countries) than in the south.

Although analysis of mortality by ‘underlying cause’ suggests that stroke mortality in the UK has been declining more slowly than CHD mortality in recent years – indicative perhaps of a slowdown in the well-recognised long-term secular decline in stroke mortality – Goldacre et al (2008) have argued that a revision of these estimates may be in order (at least for the UK), since mortality based on underlying cause alone misses about one-quarter of all stroke-related deaths.

Combined life expectancy at birth would reach 100 years before the end of the century.

Though we should not underestimate the difficulties and disagreements involved in determining what the ‘present’ trajectory is.

This is not to say that the data on recent trends might not indicate that there has in fact been a compression of disability over, say, the last 20 years; and this trend may provide the basis for a ‘best-bet’ projection for the future.

When this argument was first developed, dementia was classified as a non-fatal degenerative disease. It now appears as a cause of death on death certificates. Although this change weakens the force of the distinction between fatal and non-fatal degenerative disease, the essential point remains the same.

This compares with the estimate of 6-7 years of life lost at age 40 for obese non-smokers in the Framingham cohort (Peeters et al, 2003)

Olshansky et al (1990) estimated that the elimination of mortality from cancer would add 3.2 years to life expectancy at birth in the USA.

Though presumably it might take quite some time to have this kind of population-wide effect.

This document has been commissioned as part of the UK Department for Children, Schools and Families’ Beyond Current Horizons project, led by Futurelab. The views expressed do not represent the policy of any Government or organisation.

As a first step to establishing the nature and significance of the R&D, knowledge, innovation triangle, this section outlines some definitions of key formal elements of the triangle, before extending the discussion to more informal, but, probably, equally important components.

Elements of the formal triangle

Research and experimental development (R&D) are formally defined as “… creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications.” (OECD, 2002, p.30)  The general feeling, however, is that this definition is very narrow and of little relevance to the inventive activities of most small firms or many parts of the service sector (Gallaher et al, 2006), as well as failing to capture all the creative investments of large organisations.

The United States Patent Office states that an invention includes “… any art or process (way of doing or making things), machine, manufacture, design, or composition of matter, or any new and useful improvement thereof”. European patents are granted for “… inventions that are new, involve an inventive step, and are susceptible of industrial application.”

The EC (2005a, p31) define innovation as “Technological product and process (TPP) innovations comprise implemented technologically new products and processes and significant technological improvements in products and processes.”  CRIC (2005, p. 5) defines innovation as “…the successful exploitation of new ideas. That is, the development and commercial exploitation of a new idea for a product or process that contributes to wealth creation and profitability.”

Elements of the informal triangle

The formal triangle is well defined, largely for tax and legal purposes (eg R&D tax breaks and protection of intellectual property), but this makes it much narrower than is ideal for the purposes of the present discussion.  The concept needs to be widened to attempt to include all aspects of creativity amongst the management and workforce that is reflected in creative products and new ways of doing things.

The so-called “creative sectors” themselves, which span 13 different industries (DCMS, 2002, Annex A), give some indication of areas of creative activity that lie in the service rather than the manufacturing sector, some of which have no significant link with technology per se or traditional forms of R&D.  Examples of such industries include advertising, architecture, music and the visual and performing arts, and computer games, software and electronic publishing.  Few of such activities would be linked with patenting, but are associated with other forms of intellectual property rights such as copyrights and trademarks.  As the Work Foundation’s (2007, p16) report indicates

“The creation of ideas, images, symbols, design and cultural expression on this scale would alone be enough for the sector to warrant attention; such vitality needs to be honoured and nurtured.”

However, creativity is far from limited to the creative industries, it can happen in any sector of the economy and at any point in the production, distribution and use of goods and services.  Individual workers may have ideas for improving the production process, ideas may move up and down the supply chain, final consumers may find new uses for an existing product.  The sum of the often incremental improvements may nevertheless prove significant.

3.      The central role of the R&D, knowledge, innovation triangle

The centrality of R&D and knowledge creation and use is set out clearly by Romer,

“Ultimately, all increases in standards of living can be traced to discoveries of more valuable arrangements for the things in the earth’s crust and atmosphere … No amount of savings and investment, no policy of macroeconomic fine-tuning, no set of tax and spending incentives can generate sustained economic growth unless it is accompanied by the countless large and small discoveries that are required to create more value from a fixed set of natural resources.” (Romer, 1993, p345).

It is now widely accepted that the creation, dissemination, and application of knowledge have become a major engine of economic expansion (Shapiro et al, 2007, p15). Innovation drives economic growth because,

“Through innovation processes leading to the creation of new knowledge and its application in new or better products, services, processes, and modes of organisation, or application of existing knowledge and/or technologies to new contexts.” (ibid., p10)

Innovation, knowledge, and technology are such powerful drivers of economic growth because unlike capital and labour, they do not suffer from diminishing returns (ibid., p11). In other words, the creation of knowledge and technological innovation can actually increase the return to further knowledge and innovation, thus creating a powerful growth mechanism (this is discussed in detail in Section 5 below).

Innovative efforts are on the rise as a share of economic activity (OECD, 2007, p6).  Investment in knowledge has grown more rapidly than investment in machinery and equipment since the mid-1990s in most OECD countries, and has surpassed the latter in a few countries such as Finland and the United States.  Most sectors and industries are currently experiencing what the OECD calls a “Schumpeterian renaissance”, in which innovation is the crucial source of effective competition, of economic growth, and of the transformation of society (Shapiro et al, p15).

The creative industries themselves are hugely important, playing an increasingly significant role in economic life.  In the UK, this set of industries account for 7.3% of the economy’s output, which is comparable in magnitude to the financial services sector (Work Foundation, 2007, p16).  The thirteen creative industries directly employ a total of 1 million individuals, although around another 800,000 work in creative occupations, and

“The livelihood of a growing proportion of British citizens will depend upon the sector maintaining its trajectory of growth.” (ibid.)

Higher level, technological innovations

Formal, more radical innovation relies heavily on the creation of basic knowledge, through both education and science (OECD, 2007, p18).  Scientific progress has become a direct driver of the innovation process, for instance

“Technical progress has accelerated in areas where innovation is directly rooted in science (eg biotechnology, information technology, new materials) and firms’ demand for links to the science base has increased.” (OECD, 2000, p4)

There is also “… a strong relationship between expenditures in R&D and innovation output measured by US patents granted”. (Bosch et al, 2005, p19)

Creating, developing and diffusing new products and processes requires strong science and technology (S&T) skills as well as many non-research soft and entrepreneurial skills (OECD, 2007). There is an increasing emphasis on policy issues related to the availability of highly skilled labour, in particular highly skilled human resources in S&T. Strong S&T skills facilitate the uptake and use of new technologies which drives innovation throughout the economy (Bosworth, 1996). This places a premium on both the “quantity” as well as the quality of highly skilled labour in the economy.

Lower level innovation and diffusion

It is too easy to focus on higher level at the expense of lower level innovation.  Popper and Wagner (2002, p7) argue that “… relatively small innovations and developments of new technology may lead to results almost beyond our imagining, as we have witnessed only in the last decade with the advent of the internet and the world-wide web. Relatively small investments in knowledge creation may lead to large dividends in more familiar form such as enhanced productivity, more sustainable economic activity, and richer, healthier, and more fulfilling lives.” (op cit., pp7-8)

It has long been recognised that lower level innovation and the adoption of new technologies already in use elsewhere are more crucially dependent on the skills and competencies of the workforce (eg Solo, 1966; Amsden, 1989).  In the context of economic development, Solo (1966) argues that the presence of formally educated scientific and technical elites is a necessary but not sufficient condition for development, which can only begin when the skills of the middle mass of “mechanics and technicians” reaches a sufficient threshold.  Similarly, in the case of Korea, Amsden (1989, p9) argues that, while “Salaried engineers are a key figure in late industrialization because they are the gate keepers of foreign technology transfers”, nevertheless “… Korea was a successful learner partly because it invested heavily in education” (ibid., p23).

This link between education, innovation and diffusion has been taken up extensively in the literature.  OECD (2007, p18) argues that a well-performing and broadly accessible education system facilitates the adoption and diffusion of innovation and that human capital is a key factor in the adoption of new technologies and the introduction of innovative practices.

Evidence for this argument lies scattered throughout the international comparative case study work of the NIESR.  For example, Mason and Wagner (2002, p93) argue that the greater skills of the German workforce – particularly intermediate skills – help to keep production moving smoothly and this frees up time for strategic incremental process improvements. The NIESR case studies provide many other instances of the role played by skills, particularly intermediate skills.

4.      Areas where improvement is necessary

Overall skills position

The UK uses five levels to measure literacy and numeracy skills, Level 1 literacy and Entry Level 3 numeracy are the standards necessary to function at work and society in general.  In 2003, 16% of the working-age population in England (over five million people) lacked Level 1 literacy skills and 21% (6.8 million people) lacked Entry Level 3 numeracy skills (OECD 2005). International surveys have found the UK lies in the bottom half of the OECD in terms of the number of people that lack these basic skills.

The proportion of adults in the UK with low skills has decreased slightly in recent years from 35% of the adult population in 2003 to 33% in 2005 (OECD, 2005).  However, UK adults with low skills still form a relatively large percentage of the population by international standards.  Out of thirty countries compared by the OECD in 2005, sixteen countries had a lower proportion of adults with low skills than the UK. The top performing countries, such as the USA, Canada, Japan and Germany had less than half the proportion of adults with low skills compared to the UK.

The UK saw little change in the percentage of adults holding intermediate skills between 2003 and 2005 – forming 27% of the total. The proportion of adults in the UK with intermediate skills, however, remains relatively low, and below the average for the thirty OECD countries.

The amount of adults possessing high skills in the UK increased from 28% of the adult population in 2003 to 30% in 2005.  The UK has a larger proportion of adults with high skills than nineteen of the OECD countries, but lies considerably behind the top performing countries such as the USA, Japan and Canada, with at least 40% of their adults possessing high skills.

The skills level of UK workers can be measured by looking at the national qualifications framework (NQF), which distinguishes six levels of qualification obtained, ranging from no qualifications, through NQF1 to NQF5, where NQF5 is the highest level of qualification.   In the UK there is a major difference in the qualifications of those people living in the least and most deprived areas of the country.  For instance, nearly 10.6% of the employed population in the least deprived areas has obtained a qualification of NQF5, whereas just 3.4% of employed workers in the most deprived areas have obtained this qualification.  The proportion of those with NQF4 falls from 32.3% in the least deprived areas to just 16.1% in the most deprived areas.  The proportion of employed workers with NQF3 also falls with the level of deprivation.  There are compensating increases in amongst those with no qualifications (from 3.7% to 14.6%), NQF1 (from 14.1% to 23.1) and NQF2 (from 19.3% to 24.4%).

The supply of top-level managers in the UK argued to be very competitive, as evidenced by the high international ratings of UK management schools and the quality of the students they attract (Porter and Ketels, 2003). The UK has relatively high levels of professional management (as opposed to the majority of owner-managers) and attracts the best managers from around the world. Modern executive compensation techniques are used more widely in the UK than elsewhere, except in the USA.  It is generally believed that problems in managerial skills are mainly concentrated at lower and middle management levels.

Overview of the UK’s innovation position

The UK’s relative performance in innovation can be assessed by looking at the following factors: strength of the science and engineering base (the number of publications and citations per head of population); business enterprise R&D (BERD) and gross expenditure on R&D (GERD), both as a percentage of GDP; intellectual property (eg the number of patents and trademarks granted); networks and collaborations (eg percentage of innovation-active firms reporting research cooperation with other organizations); and innovative products (eg share of firms’ turnover attributed to new or significantly improved products) (DTI, 2006, p20).

The UK has a strong science and engineering base. The UK leads its competitors (eg France, Germany and the US) both in terms of the number of papers and the number of citations per head (ibid., p23). Only the US leads the UK in terms of its overall share of world citations (ibid., p23). The UK research base performs relatively strongly right across the subject spectrum, with some variation. The UK is strong in clinical, preclinical health-related, environmental and biological sciences, but not quite so good in mathematics, engineering and physical sciences (ibid., p23).

The UK lags behind its competitors on R&D spending. In 2004, the UK’s BERD/GDP was about 1.2%, compared to 1.9% for the US, 1.8% for Germany and 1.4% for France (ibid., p26). The UK also performs less well in terms of GERD/GDP, which was below the EU25 average in 2003 (EC, 2005b, pp21-22), at about 1.9% in 2003, while that of France was 2.2%, Germany 2.5% and the US 2.7% (DTI, 2006, p26).

Data from the US Patent and Trademark Office (USPTO) shows that Germany and the US have a significantly greater number of patents per million of population than the UK, while the UK and France have a similar number of patents per head (ibid., p29). The large difference with the USA might, in principle, be due to the fact that US firms are more likely to register this with the USPTO than non-US firms.  Nevertheless, USPTO data are broadly consistent with other measures of patenting performance, such as triadic patents (ie patents for the same invention registered in the US, EU and Japan), which correct for this bias.

It has been argued that a greater percentage of UK innovation-active firms use alternative methods of protection to patenting than other European firms (consistent with the importance of the “creative sectors” in the UK, where forms of IP other than patents were important – see Section 2 above). UK firms are more likely to use trademarks (UK firms dominate the top 10 in the UK Trade Mark scoreboard according to HM Treasury et al, 2005), lead-time advantage, secrecy, complexity of design, and registration of design patterns and copyright. The Report suggests that these differences are partly the result of differences in industrial structure across countries.

They suggest that UK firms achieve improvements in their market position through means that are under-recorded in traditional innovation indicators.  If true, these assertions raise questions about why the UK is going a different route than its main competitors and, if not true, the evidence suggests that the UK is considerably under-performing vis-a-vis its main competitors.

The share of turnover in UK businesses accounted for by new or significantly improved products was second only to German firms in the EU15 (Lucking, 2004, p15). The UK leads all the countries covered by the CIS in terms of the proportion of turnover that is due to new or improved products amongst product innovators. Of UK product innovators, 41% of their turnover appears to be generated from new or improved products.  These results seem somewhat out of line with the other innovation evidence reported above.

5.      Market imperfections and government intervention

Historically, support for government intervention in education, training and R&D came from the fact that taxes on earnings drive a wedge between the private and social returns.  As the individual only receives earnings net of taxes, they under-invest in education from society’s viewpoint.  The same argument can be applied to training, whether this raises the individual’s wage or the firm’s profits, and to R&D, which raises the firm’s future profits.  Both wages and profits are taxed, which leads to a private under-investment from society’s point of view.

More recently, the justification for government intervention has shifted, based upon growing evidence that there may be increasing returns to investments in knowledge at the macro level.  This occurs because the knowledge generated by one firm can be recombined with other knowledge by other firms (Smith, 2002).  As each firm does not take into account the benefits to other firms, the level of private investment in knowledge is less than the socially optimal level.

R&D spillovers

The R&D literature has widely explored the existence of spillover effects in which any one firm may benefit from the R&D carried out by other firms, for example, in the same sector (Bosworth, 2006, pp194-197).  Of course, defining the relevant pool of R&D from which a particular firm benefits is an empirical question, which has been extensively tested using either R&D or patent measures of the pool based upon the technological distance of one firm from that of others.  Technological distance can be based on similarities or differences in the international patent classes within which firms operate.  The pool exists because each firm is unable to appropriate all of the benefits arising from their R&D and innovation activities.  Some of the scientific and technological information cannot be protected through secrecy or intellectual property rights, leaks out and is of value to other firms.  Griliches (1992, ppS30-31) notes that

“The more difficult to measure and the possibly more interesting and pervasive aspect of R&D externalities is the impact of the discovered ideas or compounds on the productivity of the research of others.” (Griliches, 1992, ppS30-31).

Even in the case of strong patents, appropriation is incomplete. For one thing, “disclosure” of information is part of the “price” the inventor must pay to obtain patent monopoly rights over the idea.

The result is that the return to the stock of R&D knowledge is higher at the aggregate than the individual firm level (Griliches, 1992).  This implies that firms that take decisions based upon their own private calculus invest in R&D at a level below that which is socially optimum.  In other words, the firm only invests up to the point where the private return to the next £1 of R&D is also £1.  This calculation does not account for the fact that the firm would benefit from a greater industry- or economy-wide investment in R&D – according to the spillover hypothesis, if there is an overall expansion in R&D, all firms benefit.

The associated empirical literature links firm performance (eg total factor productivity or market value) to own-R&D and some measure of the R&D pool that the firm benefits from.  The results thereby provide information about both the private and the social rates of return to R&D.  According to Griliches (1992, ppS43-44)

“… there has been a significant number of reasonably well done studies all pointing in the same direction: R&D spillovers are present, their magnitude may be quite large, and social rates of return remain significantly above private rates. … R&D returns account for half of the growth in output per man and about three quarters of the measured TFP growth, most of the explanatory power coming from the spillover component … “.

Education and human capital spillovers

Similarly, a reason for government intervention in education is the existence of externalities and spillovers, even if these are much more difficult to quantify than in the case of R&D.  The argument that there are externalities from education – human capital spillovers – has a long history, which dates back at least to Marshall (1890).  The work by Blaug (1968, p243), for example, outlines nine different types of economic and non-economic spillovers that arise because of improvements in education.  Indeed, there is a significant literature on positive educational spillovers on social activities (Wolfe and Zuvekas, 2000).

In the main, attempts to isolate human capital spillovers have largely focussed on the effects of the average level of education in different locations on the earnings of otherwise similar individuals in those locations (eg Rauch, 1993; Acemoglu and Angrist, 2000; Ciccone and Peri, 2006; Moretti, 2004a).  Some of these locational studies are quite sophisticated.  Moretti (2004b), for example, uses longitudinal, plant level data (which help to eliminate some of the issues of selectivity and endogeneity).  In addition, this paper explores the role of “economic distance” in determining the strength of spillovers, showing that

“… spillovers decline with economic distance … aggregate human capital in the high-tech sector of the city matters more for high-tech plants than aggregate human capital in the low-tech sector of the city; and aggregate human capital in the low-tech sector matters more for low-tech plants than aggregate human capital in high-tech plants.” (ibid., p657)

The local area spillover effects outlined above are somewhat different from those envisaged by Battu et al (2004).  Here the productivity increasing “employment related” spillovers (Blaug, 1968, p244) occur from the more to the less educated amongst employees in the same workplace.  Based on a statistical analysis of the Workplace Employment Relations Survey, Battu et al (2004) report the existence of substantial and significant educational spillovers in the workplace, which are largely independent of the individual worker’s own educational level.

Endogenous growth – the “new growth theories”

Most goods and services, such as capital and labour are characterised by:

• rivalry – that only one person can make use of them at a given point in time;
• excludability – that one person (eg the owner) can prevent other individuals using them.

Knowledge is a non-rival good and, insofar as it is not wholly appropriable – in other words, insofar as there are knowledge spillovers – it is also non-excludable.

The result is that, while there may be diminishing returns to investing in knowledge at the individual level (eg each additional unit of knowledge adds less to income than the previous unit of knowledge), there can be increasing returns to investment in knowledge at national level (as not only the individual making the investment benefits, but so do other individuals and groups within the economy).

Thus, according to Cortright (2001, p4),

“The centerpiece of New Growth Theory is the role knowledge plays in making growth possible.  Knowledge includes everything we know about the world, from the basic laws of physics, to the blueprint for a microprocessor, to how to sew a shirt or paint a portrait. Our definition should be very broad including not just the high tech, but also the seemingly routine.”

Free markets fail to produce adequate amounts of knowledge.  In essence, there is a “free rider” problem.  If there is no way to exclude others from benefitting from the knowledge an individual produces, there is no effective way of making them contribute towards paying for its production.  To put it slightly differently, there is no way the producer of knowledge can capture revenues that reflect all of the benefits other individuals receive from knowledge and, as a consequence, they under-invest in knowledge from a societal perspective.

6.      Implications for education and training

The UK’s future economic performance is dependent on the generation and exploitation of new ideas that will provide a lead over competitors (Bosworth, 2008).  This requires, at the very least, the successful combination of:

• people with the skills to recognise, produce and exploit ideas (e.g. management, leadership, entrepreneurship, technical know-how, a creative and innovative population)
• an infrastructure capable of supplying the skills and knowledge to generate new ideas and support their exploitation (eg education and training systems, R&D capacity), and,
• a system capable of making appropriate connections between the supply of and demand for ideas (such as establishing mutually beneficial partnerships between industry and the further/higher education sectors, support for entrepreneurs and new businesses).

The literature highlights several important links between education, R&D and innovation.  These include the need for high level science and technology skills, necessary for the more high profile forms of R&D and innovation.  However, they also include the skills of the general workforce, which both free management time for innovation and allow innovation to take place.  Increases in education and skills allow more innovation options – not just cost reducing, but also quality increasing.  In addition, increases in education and skills lower the degree of risk in activities such as R&D and the introduction of new products and processes.

Historically, the skills focus in the context of innovation has largely been on graduate level jobs in management, engineering, and science.  In England, for example, the Lambert Review (2003) concentrates on the university sector and the extent to which it can and should act as a catalyst for change in industry and the Sainsbury Review (2007) looks at the role of science in enabling British companies to move away from low-cost and towards high-value goods, services and industries.  While these top level skills are crucial to future success, they are not, in themselves, enough. They are necessary but not sufficient.

As the report by CRIC (2005) argues, a much greater emphasis needs to be given to the skills of the overall workforce in order to ensure that a higher rate and greater pervasiveness of innovation materialises.  In addition, it needs to be recognised that innovation is not just driven by large-scale investments in the production of new products and services or the introduction of new processes, which will largely be the results of decisions by senior staff within an organisation, but it will also be the result of more piecemeal, incremental changes suggested by other members of the workforce that nevertheless have a significant cumulative impact on performance.

The present paper has reported on the huge inequality in the distribution of education, knowledge and skills across individuals.  This works its way into where individuals are located and the degree of deprivation they suffer, as well as the direct link between economic inactivity and the lack of skills.  Education and training remain focussed on the younger members of society and are much less important amongst older individuals, even though society recognises the need for lifelong learning and is currently in the process of raising the retirement ages of both females and males.  Smith (1776) argues the point in the following way,

“In the progress of the division of labour, the employment of the far greater part of those who live by labour, that is, of the great body of the peoples, comes to be confined to a very few simple operations, frequently to one or two. But the understandings of the greater part of men are necessarily toned by their ordinary employments. The man whose whole life is spent in performing a few simple operations, of which the effects are perhaps always the same, or very nearly the same, has no occasion to exert his understanding or to exercise his invention in finding out expedients for removing difficulties which never occur. He naturally loses therefore, the habit of such exertion and generally becomes as stupid and ignorant as it is possible for a human creature to become. The torpor of his mind renders him not only incapable of relishing or bearing a part in any rational conversation, but of conceiving any generous, noble or tender sentiment, and consequently of forming any just judgement concerning many even of the ordinary duties of private life.” … “His dexterity at his own particular trade seems, in this manner, to be acquired at the expense of his intellectual, social and martial virtues. But in every improved and civilised society this is the state into which the labouring poor, that is, the great body of the people, must necessarily fall unless government takes some pains to prevent it.”

Policy has also tended to be supply side oriented with an emphasis on the role of publicly funded institutions.  However, as DIUS (2007) has recently recognised that the policy remit needs to be broader and to give more prominence to the demand-side, in particular, to encourage investment in R&D in this country, improve the science base, support innovation within businesses, provide skills at all levels to make people more innovative (eg the establishment of National Academies at a sectoral level), encourage innovation in public services and use of public procurement to foster innovation, and assist locations become more innovative through the establishment of innovation partnerships.

While the HM Treasury (2000) report identifies a range of factors that result in poor productivity performance, including skills, these tend to be treated as being independent of one another. In practice, they are all inter-related and, in particular, the willingness to invest, adopt best practice, undertake R&D and to innovate are all dependent on the skills of management and employees.  The assertion in HM Treasury (2005) that the UK is strong in areas of innovation that are not reflected in traditional technological indicators requires urgent further research.  If this is wrong, some of the levels and trends (eg R&D/GDP) are very worrying; if it is correct, there is a need to know why the UK is different and what the implications are for the competitive position of the UK economy.

References

Acemoglu, D. and Angrist, J.D. (2000) How Large are Human-capital Externalities? Evidence from Compulsory Schooling Laws. NBER Macroeconomics Annual. Vol. 15. Cambridge, MIT Press, pp.9-59.

Battu, H., Belfield, C.R. and Sloane, P.J. (2004) Human Capital Spillovers in the Workplace: Evidence for the Service Sector in Britain. International Journal of Manpower, 25 (1), pp.123-138.

Blaug, M. (1968) The Rate of Return on Investment in Education. In: Blaug, M. (ed) Economics of Education. London, Penguin, pp.215-259. First published 1965.

Bosch, M., Lederman, D. and Maloney, W.F. (2005) Patenting and Research and Development: a Global View. World Bank Policy Research Working Paper 3739. Washington. October.

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Book Five, Chapter 1, Part 3, Article II.

This document has been commissioned as part of the UK Department for Children, Schools and Families’ Beyond Current Horizons project, led by Futurelab. The views expressed do not represent the policy of any Government or organisation.