Integrating an Aging Student Population / D. Orr 25 CSSHE SCÉES Canadian Journal of Higher Education Revue canadienne d’enseignement supérieur Volume 40, No. 3, 2010, pages 25 - 42 Integrating an aging student population into higher education – challenges for evidence-based policy in Europe Dominic Orr HIS-Institute for Research on Higher Education ABSTRACT Both demographic developments and the need for highly skilled workers have led to renewed efforts to widen access to higher education in Europe. This means looking beyond the traditional clientele of university education in terms of routes into higher education, age, and centrality of studies. Attracting and catering to this more comprehensive group entails rethinking study programs and study environment for a more heterogeneous student body. So where are we now on these issues and where can we expect to be in the next decade? This is a question being raised within the framework of the Europewide Bologna Process for higher education reform. On the basis of data sets being used for analysis within this reform program, a comparison of the situation in selected European countries will be presented. It will be shown that some countries are better placed to deal with the growing number of adult learners than others. RÉSUMÉ Tant l’évolution démographique que le besoin en travailleurs hautement qualifiés ont mené à un regain d’efforts pour accroître l’accès à l’enseignement supérieur en Europe. Cela signifie qu’il faut voir au-delà de la clientèle traditionnelle des études supérieures en termes de parcours d’études postsecondaires, d’âge et de centralité des études. Attirer, puis servir ce groupe plus polyvalent exige de repenser les programmes et le milieu d’études pour répondre aux besoins d’une population étudiante plus hétérogène. Où en sommes-nous aujourd’hui quant à ces questions et quel chemin pouvonsnous espérer avoir parcouru d’ici dix ans? Nous posons la question dans le cadre du processus de Bologne pour une réforme de l’enseignement supérieur, appliqué à l’échelle européenne. À partir d’ensembles de données employées CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 26 pour effectuer des analyses à l’intérieur de cette réforme, nous comparerons la situation dans divers pays européens sélectionnés. Nous démontrerons ainsi que certains pays sont mieux organisés que d’autres pour accommoder une population croissante d’apprenants adultes. INTRODUCTION Higher education is subject to a lot of change and reform at present. This is especially true for European higher education dealing with growth in numbers (and relative percentage) of students, changes to governance structures (Kehm & Lanzendorf, 2006), changes to structures and modes of study (Witte, 2006), and increased private financing, especially through tuition fees (Eurydice, 2009, p.143). Amid all this, another change is occurring – to the student population. In many cases, both policy and practice still focus on the stereotypical students within a certain age bracket, of a certain educational background, and with certain interests (Miclea, 2008, p.70). Those who do not fit into this corset are termed non-traditional. This latter heterogeneous group is not really new to higher education. However, it might be argued that the characterisation of this group as “an invisible majority” (McNair, 2002) still held true in most policy settings in Europe until recently, despite the formal existence of lifelong learning agendas. One main reason for this might be that it is hard to recognise this group without detailed survey data on educational biographies and relative differences in socio-economic backgrounds. On the basis of just such a data set covering 23 European countries, it will be argued here that simply looking at the age of students provides a useful proxy for recognising non-traditional students. This variable, in turn, has the advantage of being a standard statistic found in university administration and national statistics alike; it is easy to collate, to reproduce, and to connect to information in other data sets. Age can be seen as an independent variable when we look at certain aspects of university participation (Baxter & Hatt, 1999). However, it is naturally a proxy for both events in a person’s life, in general, and in their educational career, specifically. In his study on social capital, Bourdieu explicates, for example, the relationship of age to income, occupation, and educational chances (1984, p.105). Indeed, in the mid 1980s, Bean and Metzner proposed defining so-called non-traditional students largely on the basis of their age and whether they study part-time (1985). A strong argument for focusing on age also emerges from projections on both demographic and labour market developments, which show that it is exactly here – in the age profile of students – that we can expect the most visible change to the student population in the coming decade. This article will introduce the agenda on non-traditional students in Europe and the particular relevance of changes to the economic and demographic landscape in Europe. It will then briefly describe the current data situation for large cross-country comparisons before moving on to utilising the available data for a comparative analysis of the situation of adult learners in Europe. In this, it will look at age profile, alternative routes into higher education, and study framework conditions. It will close with a discussion of the results and their pertinence for policy development at both a national level and within the Bologna Process. CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 27 NEW INTEREST IN NON-TRADITIONAL STUDENTS IN EUROPEAN HIGHER EDUCATION The percentage of 25- to 64-year-olds with tertiary education grew considerably in the last decade, specifically, from 20% to 27% between 1998 and 2007 for OECD countries and from 18% to 24% in the EU-19. This growth was paralleled by a decrease in the number of 25- to 64-year-olds who have not attained an upper secondary certificate (OECD, 2009, p.41). In many cases, higher education systems can now be typified as having made the transition from elite to mass higher education according to Kouckŷ’s modification of Trow’s definition, based not simply on entry rates, but on graduate rates (Kouckŷ, 2010). At the same time, there are signs that this growth will not be enough to satisfy the demands of the labour market in the future. The European institute for vocational training, CEDEFOP, predicts that low-skill sectors of European economies will shrink significantly in the next ten years and that growth will occur particularly in high-skill sectors. This change will stem from the need for higher skill levels in many occupational areas and from the expected development toward three-quarters of jobs being in the service industries by 2020. On the basis of such predictions, the analysis also looks at the expected job openings between 2008 and 2020, which is a particularly relevant statistic for the evaluation of strategies for education and training systems within Europe. For jobs requiring higher qualifications (ISCED 5-6), an increased demand is expected of close to 25 million jobs making a total requirement of 73 million jobs; for the medium qualifications (ISCED 3-4) an increased demand is projected of 13 million jobs and a total requirement of nearly 115 million jobs; and in the low qualification sector a decrease of over 13 million jobs and a total requirement of around 43 million jobs between 2006 and 2020 (CEDEFOP, 2008, p.13).1 In the UK, a recent skills report under the chairmanship of Lord Leitch set the goal for higher education attainment in the total working population at 40% for 2020, up from 29% in 2005. In order to reach this quota, the Leitch review sees it necessary to look beyond the 18- to 30-year-old population (2006, p. 21) and even to provide access to higher education via workplace delivery (p. 140). A further exogenous development which will impact on higher education in the future is the demographic downturn, which will already be quite visible by the year 2020. The latest weighted EU-27 average shows that two-thirds of all European students are under 25 years old and 85% are under 29 years old. Looking at the projections for the demography of European populations until 2020 we can see that this section of the population, typically the mainstay of European higher education, is expected to decline – in some cases dramatically. Figure 1 looks at a Eurostat predication of the percentage of young people of typical university age – 18 to 24 years old – for a selection of European countries. The data show a common pattern despite the differences: Europe can expect a drop of approximately 12% in this typical age group (from 44 to 39 million), while the total population will increase marginally by 4% (from 495 to 513 million). Some countries will be hit quite dramatically by this decline, for example, Slovakia (-33%; from 596 to 399 thousand). In the UK, the drop will be smaller (-7%; from 5.8 to 5.4 million), but the number of people in the total population will also increase by 7% (from 61 to 66 million), reflecting the need to upgrade the skills of older people. CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 28 Percentage change from 2008 to 2020 15 % 0% -15 % European Union (27 countries) Czech Republic Germany -30 % Estonia Slovakia United Kingdom -45% Year 2008 to 2020 Figure 1. Demographic decline of the typical student age group between 2008 and 2020 for Europe (EU-27) and selected countries. Source: Based on Europop2008, convergence scenario from Eurostat. The consequences of this prognosis for higher education are that the percentage of the population obtaining higher qualifications should be increased by recruiting more of the typical age group into higher education, but also by recruiting a more heterogeneous group of students who are older and have more diverse social and educational backgrounds. It is indeed remarkable that recent business theories see open societies as having an economic advantage over their competitors as they provide the best way of exploiting talent to the full, and talent is the major economic resource for sustainable societies (Florida, 2005, p.91f.). This challenge has been most clearly taken up as a policy directive by the Bologna Process. The latest documents recognise this growth in participant numbers, but now turn their focus to the question of who is getting into higher education. The 47 ministers responsible for higher education concur that one of their main goals for 2020 is to ensure the “maximisation of talent” by looking at what they term the “social dimension” of higher education (Bologna-Communiqué, 2009). This is an interesting juncture, as two separate agendas appear to be merging within the Bologna Process. On the one hand, there is the social justice argument that the social dimension is about assuring equity – about an equality of opportunities (ibid). On the other, the social dimension is being seen as a human capital argument about maximising talent and its application – a mechanism with which to assure sufficient participation in higher education to satisfy labour market demand. Indeed at the last Ministers’ conference, there was, within the framework of Bologna, a notable consensus of opinion between the ministers from such diverse countries as Portugal, Estonia, France, and Armenia. The Armenian minister defined the social dimension as a key standard of European higher education, which would be central to his country’s national reforms. The French state secretary went on to argue that the social dimension could be seen as Europe’s competitive advantage in the contested landscape of global higher education (source: personal attendance at Bologna Ministerial Anniversary Conference 2010). It appears, therefore, that debates on non-traditional students and improving students’ study conCJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 29 ditions have now entered mainstream discussion, instead of largely being seen as a social democratic argument. This has given rise to the call for more comparative data to enable evidence-based policy development. DATA AVAILABILITY Two international comparative reports, in which the author was involved, have looked carefully at the European student landscape and can provide insight into these issues. The first is the Eurostudent final report, entitled Social and Economic Conditions of Student Life in Europe, published in September 2008 (Eurostudent 2008). Its data set collates comparable data from national surveys of students on the social and economic conditions of their studies. The most recent report comes from the third round of this study, which is carried out on a three-year cycle. Eurostudent conventions specify that a representative sample of all students at ISCED 5A level (academic degree) should be drawn, irrespective of the type of institution of higher education, excluding foreign mobile students. The latter group is excluded because it is assumed that their social and economic framework conditions and their cultural and financial backgrounds would be too diverse for the study and that they should be covered in a separate project. Eurostudent has adopted a decentralized approach to data collection. The aim is to obtain high quality results through a harmonized list of variables and indicators, together with their related definitions. Definition of indicators requires the use of a common questionnaire. Output is harmonized, for the most part, by the Data Delivery Module, the interface for data transfer from national production to central assembly, which constitutes the mould into which all data are poured. Countries, therefore, do not provide the international coordinators with raw micro data, but with calculated aggregate indicators for 63 subtopics. The full set of Eurostudent data covers the topics of demographics, including social background; access routes; study programs; accommodation, funding, and living costs; time use and employment during studies; and temporary mobility during studies. In sum, the Eurostudent data set provides a strong source of data on important aspects of student life in Europe within a comparative framework (Clancy, 2010, p.93). Recognition of the uniqueness of this data set has made the Eurostudent project the official data collector in the Bologna Process, along with the European agencies, Eurostat and Eurydice (Bologna-Communiqué 2009). In April 2009, the European ministers responsible for higher education endorsed a joint report from Eurostat and Eurostudent entitled The Bologna Process in Higher Education in Europe: Key indicators on the social dimension and mobility (Eurostat/ Eurostudent, 2009). This report was specially commissioned for the Bologna Process and uses a collection of data sources to look at the landscape of the European higher education area, which encompassed 46 countries at the time. The data sets from Eurostat, the European agency for official statistics, are largely based on administrative data and, therefore, have the advantage of covering all students, and not a select sample. In most cases, the statistics have been collated in the same way over many years and are considered reliable. Furthermore, data collection occurs every year so that the data are current and developments can be compared over time. On the other hand, the data cover administrative units (such as institutional types and fields of study) but lack depth concerning characteristics of students (beyond age and sex) and their living CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 30 conditions. The data sets are enriched by special household surveys such as the labour force survey. These provide more depth. Their value, however, is limited because they have not been developed to cover the student body specifically. Because of the data collectors’ efforts to combine and complement data from their various sources, the data situation in Europe can be characterised generally as positive (Adelman, 2009). In the current phase of the Bologna Process, Eurostat and Eurostudent have been asked to work together with Eurydice on a report on the implementation of the Bologna reforms in Europe, which will be published in 2012. Eurydice collects and analyzes information on regulations, structures, and policies. It uses special questionnaires sent to the Eurydice units in each country in order to collate additional information. The resulting data covers structures and procedures, but gives little insight into the implementation of these structures at ground level. The deficiencies in the available data sets in Europe are largely to do with the systematic approaches taken by the data collectors and are unlikely to change much in the future. However, with the aid of this data it is possible to provide high level reports, which show tendencies and trends. The reports can then be taken as starting points for further, more in-depth research. This assessment applies to the data which will be presented in the following sections. The article will show some examples of the diverse situation in Europe. It will compare different countries which each attract students with very different profiles in order to highlight differences and similarities. The data used will not cover all 23 Eurostudent participants or all 46 Bologna member countries (for this the reader can refer to the full publications). The analysis will largely focus on countries which show the most interesting deviations, extended in some cases with averages for the European region (EU-27), where possible. STUDENTS’ AGE General age for the majority of students is 18 to 24. Figure 2 now presents data for selected countries. The data show that there are large differences in the age profile of students and that some countries seem particularly successful at training older students. France, the Czech Republic, and Slovakia may be taken as countries that focus largely on young students; their percentages of students under 25 are higher than the EU-27 weighted average. In France only 9% of all students are aged 30 years or older. This is in stark contrast to Sweden and Finland, where between one third and one quarter of students are 30 or older. At the same time, the data for the UK and USA (and perhaps Slovakia) show two quite distinct student groups – those over 30 and those under 24 years of age. Germany, Finland, and Switzerland are examples of countries where the 25-29 age bracket is predominant with between one quarter and one third of all students. This can be taken as an indication of later starts to studies and longer course durations. Looking at the trend data in Table 1, we see that a marginal but clear change has occurred for the EU weighted average: the percentage of students aged 24 or under has decreased by three percentage points between 2000 and 2008. This development has been accompanied by an increase of three percentage points for the age group of 30 and over (that is a decrease of 4% and an increase of 20%, respectively). Germany is the only European country shown in this data set which contradicts this trend. Here CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 31 Share ofof students by age group, 2008 Share students by age group, 2008 9 14 22 20 16 13 18 19 18 22 17 15 25 11 34 16 11 16 20 14 24 32 26 22 80 70 France Czech Republic 67 United Kingdom 67 66 Slovakia EU-27 65 64 Estonia 15-24 United States 25-29 62 Spain 58 54 Switzerland Germany 49 44 Finland Sweden 30 or over Figure 2. Age profile of students (ISCED 5A) for Europe and selected countries, 2008. Source: Eurostat databank, social, and population statistics. Countries ranked by percentage of youngest students. the younger age group has increased, while the older age group has decreased. This can be explained by the effects of study structure and administrative reforms (inter alia, the introduction of bachelor’s courses), which aim to encourage, and seem to achieve, shorter lengths of study. Table 1 Percentage of students between 15 and 24 (ISCED 5A) for Europe and selected countries, 2000–2008 Country/region 2000 2003 2006 2008 EU-27 69 67 66 66 Czech Republic 82 75 71 70 Estonia 74 66 64 65 Finland 55 53 51 49 France 82 79 79 80 Germany 45 49 53 54 Slovakia 86 82 71 67 Spain 73 68 64 62 Sweden 47 43 44 44 – 58 58 58 United Kingdom 68 67 65 67 United States 64 60 65 64 Switzerland Source: Eurostat databank, social and population statistics. No data for Switzerland 2000. CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 32 In order to separate developments in lengths of study from changes to entry age, it is useful to turn to the age profiles of new entrants, although the data here is less comprehensive (for example no weighted average for Europe): see Table 2. The country ranking by youngest students remains largely the same. This chart highlights the fact that Spain and Germany (no data for France) have the highest percentage of entrants under 25 years old, whilst Sweden, Slovakia, Switzerland, and Finland have the lowest. With the exception of Slovakia, these are all countries well known during the last decade for their focus on life-long learning opportunities. In the case of Slovakia, this development could be a sign of the country reacting to the imminent demographic downturn (see Figure 1, above). Table 2 Percentage of higher education entrants between 15 and 24 (ISCED 5A) for Europe and selected countries, 2000–2008 Country/region 2000 2003 2006 Czech Republic 90 73 82 79 Estonia – – 84 83 Finland 75 77 73 76 France – 92 – – 84 84 86 86 Germany 2008 Slovakia 92 87 76 74 Spain 90 89 86 88 Sweden 63 62 68 67 – 73 73 75 79 80 79 81 – 84 80 79 Switzerland United Kingdom United States Source: Eurostat databank, social and population statistics. No data for EU-27; no data for specific years as indicated. ALTERNATIVE ROUTES TO HIGHER EDUCATION According to the OECD publication Education at a Glance, on average, over twothirds of the 25- to 64-year-olds in industrialised countries (70% OECD, 71% EU-19) (OECD 2009, p. 38) have at least achieved upper secondary education and are, therefore, theoretically qualified to enter higher education. However, we know that the percentage of a population entering higher education is lower than this. Of particular importance to widening participation efforts is to prevent dead-end routes within educational systems, whereby a person’s decision against an academic route could obstruct or at least hinder a later decision for an academic route. With the need to upgrade skills for the labour market, initiatives to widen participation in higher education are receiving special attention in a number of countries. The Eurostudent data set, in contrast to other data sources, shows results that do not reflect the extent of initiatives taken by countries, but instead quantify the actual percentage of students who state that they have entered higher education via an alternative or non-traditional route. CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 33 This exercise within the project requires a few explanatory notes, because the organization of routes into higher education depends on the general organization of the national education system and the basic assumptions of what constitutes a sufficient qualification for higher education. Eurostudent has established a common definition, which can be used for cross-country comparisons. It is typified as narrow, since it does not consider all alternatives. Narrow definition of non-traditional routes to higher education: Access to higher education through the validation of prior learning and work experience – with or without a higher education entrance examination. Applying this definition to the final Eurostudent report allows data to be reviewed in light of context information. Careful examination of the results and a very limited (including five countries) comparison will be presented here – but the differences are remarkable nevertheless (Orr & Riechers, 2010). The results show that around 6% of Swedish students enter via this type of route, 4% of Spanish, and 3% of English/Welsh students: in Germany and France initiatives are evident, but are only taken up by a small percentage of students: see Table 3. Table 3 Percentage of students who entered higher education via alternative routes – non-traditional, narrow definition, selected countries, 2005–2007 Country/region England/Wales France Percentage of all students 3 >1 Germany 1 Spain 4 Sweden 6 Source: New calculations based on EUROSTUDENT III. Percentages rounded to the nearest 1. Date of national survey used for EUROSTUDENT varies by country. The accompanying research, which we carried out in order to review the data, enabled us to identify key measures in each of the countries shown in the chart. Sweden places an emphasis on access schemes in order to encourage non-traditional students. One clear measure in Sweden is the 25:4 scheme, which focuses on older students. In order to be eligible for this initiative, students must be at least 25 years old and have a minimum of four years of work experience. Special efforts are made to recognise real competencies (reell kompetens) which may have been obtained in non-formal learning settings such as the workplace. The onus for accreditation is placed on the higher education institutions themselves. In Spain, applicants without admission qualifications can enter higher education via a special entrance examination. This entrance examination (prueba especifica) is only open to those 25 years old or older. The examination is regulated nationally, but it is organized by the institutions for higher education. A further initiative has just been introduced for people 45 years old or older. In the UK, there is an emphasis on providing alternative routes via vocational qualifications and adult education, involving almost one quarter of all students. The strong institutional differentiation between the universities in the UK regarding mis- CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 34 sions has led to certain universities specialising in the recruitment of non-traditional students. This is supported by higher government grants. In Germany, the small percentage of students nationally again hides special initiatives being taken by individual universities. In particular, the Humboldt University has a number of out-reach programs. Further, some of the universities in eastern Germany are commencing initiatives to recruit older students as a reaction to a sharp decrease in birth rates at the beginning of the 1990s. The West German states of North-Rhine Westphalia and Lower Saxony introduced state-wide initiatives in spring 2010. In order to participate, a person must have at least three years work experience. France has one very prominent initiative called la validation des acquis de l’expérience (VAE). Applicants must submit a complete portfolio of their achievements and at least three years work experience. In 2007, less than one percent of first year students entered higher education via this route. In general, we can conclude that the numbers of students taking such alternative routes into higher education remain relatively small and are largely based on individual initiatives of universities, which are more or less supported by national governments. However, the high prominence of this issue – reflected, for example, in the most recent Bologna Communiqué (2009, p. 3) – indicates that an expansion of such initiatives can be expected in the future. These initiatives will lead to a greater percentage of older students entering university. Once higher education institutions have successfully recruited older students, perhaps via non-traditional routes into higher education, there is an expectation that this will lead to different requirements of the study process, in particular, requirements taking into consideration the different lifestyle of these students. In the next section, we will apply the variable age to various framework conditions of studying. STUDY FRAMEWORK CONDITIONS Some of the Eurostudent data on student living conditions can be differentiated by age and this produces some interesting results for consideration within the context of providing an appropriate study framework for older students. The significance of age for the amount of time a student spends in paid employment can be seen in Figure 3. This chart shows remarkable similarities between countries in the hours per week during the term that students dedicate to paid employment for the younger age bracket. In all countries, apart from England/Wales and Estonia, just over ten hours are spent on paid work (age brackets dictated by Eurostudent data collection). Furthermore, in none of the countries shown do students between the ages of 21 and 24 work more hours than their older counterparts. The situation is more diverse for the older students, who often work between 20 and 40 hours. These differences are likely explained by details hidden when the data was pooled into one age bracket of 28 years and older. The numbers at the base of each column show the differences in hours worked by age group. At the lowest level, we can see that older students in England/Wales and Estonia spend approximately one third more hours in paid employment than younger students (for Estonia 38 versus 28 hours per week). In the Czech Republic and Slovakia the amount of hours is more than three times higher (3.4 and 3.3 times, respectively). CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 40 38 37 35 33 30 30 paid employment, hours per week 35 28 26 25 22 20 19 20 20 15 13 11 10 10 10 10 11 5 0 1.7 Sweden 2.0 Germany 2.0 Switzerland 2.0 Finland 1.4 England/Wales 3.3 Slovakia 3.4 Czech Republic 1.4 Estonia Aged 21-24 28 and over Figure 3. Hours per week during term time dedicated to paid employment by age, selected countries. Source: EUROSTUDENT III. Countries ranked by hours per week worked by students aged 28 and over. Number given above the country labels is the difference in hours per week between older and younger students. The Eurostudent data set (not shown here) allows for the same comparison by income earned through working, and displays the same tendency. In fact, older students earn at least twice the income working as younger students. Working students in Sweden aged 21 to 24 earn €300 per month through employment during study periods and those aged 28 or over earn €750. The difference in Germany is between €240 for the younger age group and €720 for the older age group and in Finland between €420 and €1380. This can be attributed to both the necessity and the wish to earn a monthly income working. Older students may feel the need to maintain previous income levels. At the same time, common sources of income for students, namely parental support and state funding, are only available to older students in a limited way (Eurostudent 2008, p. 93) and must be compensated for. The necessity, expectation, or wish to work while studying will have consequences for the personal organization of study time. On the basis of the Eurostudent data set, it is possible to calculate the percentage of students who spend less than 21 hours a week on study-related activities, including taught classes and personal study time. Students who spend fewer than 21 hours a week studying are referred to within the project framework as de facto part-time students. They account for from as little as of 5% of the student population in Portugal to over 40% in Estonia. It should be noted that this data on study habits does not mirror official administrative data, as it is the result of statements made by students on how they organize their study week. This has the advantage of being independent of differing administrative contexts of enrolment. CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 36 In order to investigate the relationship between hours of work and hours of study, the Eurostudent data on de facto part-time students can be cross-referenced with data on the students who work. Since some students work only a few hours per week alongside their studies, only the percentage that spends more than five hours per week in paid employment during term-time is included. Figure 4 includes all countries for which Eurostudent data is available (18 countries – see Note 2 for abbreviations). Using the median values for both dimensions produces four sections and a relatively clear split between bottom left, with low percentage of working students studying de facto part-time (for example Turkey, TR) and top right, with a high percentage of same (for example Estonia, EE). These results would suggest a clear link between increased hours of work and decreased hours of study. Indeed, the positions of those countries included in Figure 3 follow broadly the same pattern in Figure 4 – Sweden, Germany, and Switzerland in the bottom left-hand section and the Czech Republic, Slovakia, and Estonia in the top right-hand section. Share of students with paid job in term with more than 5 hours per week (in%) 80 70 60 50 40 SE IT 30 20 10 0 0 10 20 30 40 50 Share of students studying 21 hours or less (in%) 60 70 80 Figure 4. Percentage of students studying de facto part-time against percentage of students working during term time. Source: EUROSTUDENT III. Lines on the X and Y axis are determined by the median values (X=18, Y=44) CJHE / RCES Volume 40, No. 3, 2010 37 Integrating an Aging Student Population / D. Orr 100 90 80 74 70 70 62 60 48 50 51 40 40 34 38 29 30 27 20 10 38 31 25 18 16 18 4 2 4 2 8.3 Germany 9.2 Czech Republic 11 7 11 6 13 12 0 5.9 Switzerland 3.9 Estonia 15-29 years 3.7 EU-27 6.0 3.8 United Slovakia Kingdom all students 30 or older 2.0 Finland 1.7 Sweden Figure 5. Percentage of students studying part-time (administrative definition) by age, selected countries. Source: Eurostat/Eurostudent. Countries ranked by percentage of part-time students. Number given above the country labels is the difference in percentage between older and younger students. Keeping this analysis in mind, we might make the following recommendations about the required study conditions in some of the countries we have looked at. In the Czech Republic, Slovakia, and Estonia the older age group spends a significant number of hours in paid employment during their studies (more than 30 hours – Figure 3). These countries have relatively high numbers of students who study de facto part-time (more than one quarter – Figure 4). Since these are likely to be the older students, it is now interesting to turn to the administrative statistics on part-time students and to focus on what percentage of students is enrolled in a program officially seen as part-time. The need for flexible alternatives for older students would be high for the Czech Republic, Slovakia, and Estonia and, in contrast, lower in Sweden, Germany, and Switzerland. Figure 5 shows data taken from the Eurostat/Eurostudent publication and highlights percentages of students defined officially as studying part-time by age. Results vary by country, with Germany and the Czech Republic showing very low levels of part-time students (4%), and Slovakia, Finland, and Sweden very high levels (36%, 38%, and 51%, respectively). In terms of older students, in Slovakia, 97% of students aged 30 years or over are enrolled in programs officially defined as part-time. The percentage of older students in part-time studies is also high in Finland, Sweden, and the United Kingdom, where between two-thirds and three-quarters of the older students are enrolled in part-time programs. These countries were highlighted in Figures 1 and 2 as countries where a high percentage of enrolled students belong to the older age bracket. We can, therefore, assume that these countries have made special efforts to accommodate older students, accepting the argument that these students need a more flexible program of study than the younger age groups. CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 38 Remarkably, there is significant difference in enrolment in part-time studies by age in every country, with the greatest differences in those countries with the lower enrolment rate in part-time studies (left-hand side of the chart). The only exception to this is the United Kingdom, which might be related to the two distinct age groups studying university courses (compare Figure 2). In the case of the Czech Republic, the percentage of older students enrolled in part-time studies is 9.2 times higher than the percentage of younger students, although less than one in five students aged 30 or over is enrolled in such courses. With reference to Figure 3, this result could give cause for concern, since here we see that students with paid employment in this older age bracket dedicate 37 hours per week to their work. They will therefore find it a significant challenge to organize their full-time studies around such a schedule. This struggle to cope can be clearly seen in the Eurostudent data on how Czech students organize their time by the amount of work they undertake in term-time – see Figure 6. Students who work 15 hours or more during in term time spend 12 hours at taught lessons and 12 hours on personal study time, a total of 10 hours less on studyrelated activities in comparison to those students who do not have a job. The picture is very similar for Slovak students, but many of them will be enrolled in part-time programs. In other words, they are enrolled in programs offering flexibility between intensity and course duration. DISCUSSION AND OUTLOOK In this article we have focused on older students under the assumption that this group is likely to become a major segment of higher education in the future. European higher education statistics were taken to facilitate a comparison between European higher education systems regarding the size of the respective adult student population, how such students organize their studies around paid employment, and whether flexible study programs are available to them. In particular, a comparison between the Czech Republic and Slovakia shows how two countries with similar demographics (Figure 1) are coping with the challenge of providing appropriate study conditions. The final comparison showed working students coping with the challenge of balancing studies and work in the same way in both countries (Figure 6). However, it showed that only Slovakia offers a significant percentage of its students official part-time courses (Figure 5), although many of its students are studying de facto part-time (Figure 4). This may explain Slovak higher education’s apparent success in recruiting older students (Figure 2). This kind of analysis can help policy-makers at both national and European levels to evaluate their policies. In this, the particular advantage of focusing the first analysis on age as a variable means that various data sources can be combined. However, this kind of analysis can only provide the starting block for more in-depth studies at regional and institutional levels. At the same time, there is an interest within the Bologna Process in extending this work to cover an even wider region. At the recent ministerial conference in Budapest and Vienna to celebrate the ten-year anniversary of the Bologna Process, ministerial representatives from other higher education areas were invited to take part in a Bologna Policy Forum. Representatives from, among others, Australia, Canada, China, Egypt, Japan, and the USA took part. All participants recognised the existence of comCJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 39 58 a. Czech Republic 47 42 37 36 3 15 34 3 17 14 9 14 15 12 18 17 19 18 12 0 hours of work 1-5 hours of work 6-10 hours of work 11-15 hours of work paid jobs personal study time taught studies 15 hours of work or more 54 b. Slovakia 38 30 37 33 8 13 28 3 13 12 14 9 10 15 15 16 15 11 0 hours of work 1-5 hours of work 6-10 hours of work 11-15 hours of work 15 hours of work or more Figure 6. Allocation of weekly time budget across study-related activities and paid work in the Czech Republic and Slovakia – Hours per week by hours worked. Source: EUROSTUDENT III, National Profiles Czech Republic and Slovakia. mon problems and the benefit of exchanging ideas on how to solve them (Bologna Policy Forum Statement, 2010). Many representatives of these countries also appeared interested in the data collection initiatives within the Bologna Process. Whilst both Unesco and the OECD have standard comparative publications, it should be emphasized that the combination of information sources used in the Bologna data collection is unique (Adelman, 2009). It is unfortunate that currently only UOE data can be provided from outside the European Higher Education Area (EHEA) for comparative purposes. A wider exchange of ideas and experiences with the new student groups would be facilitated if such data as collected by Eurydice and Eurostudent could be provided by other countries as well. The decentralised approach taken by the data collectors means that they are open to the adoption of new data sets, from countries such as Canada and the USA, which have a similar thematic scope. CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 40 One interesting aspect of the EHEA for higher education in North America is the high involvement of national governmental bodies in the formulation of policy to support newly recognised student groups like older students. The Bologna data collection feeds into the debates of ministers at the Bologna meetings, but also at national levels, on what should be done. It has been agreed amongst the ministers that the social dimension, which looks at participation and success by student characteristics such as age, will be a key focus of developments until 2020. Observers from across the Atlantic are likely to be interested in seeing which initiatives are taken to achieve this objective and how collected data is used to support this intergovernmental process. If they can also provide appropriate data, Canada and the USA would have the opportunity to compare and contrast their experiences. REFERENCES Adelman, C. (2009). The spaces between numbers: Getting international data on higher education straight. Washington: Institute for Higher Education Policy. Baxter, A., & Hatt, S. (1999). Old and young mature students: Painting a fuller picture. Journal of Access and Credit Studies,,1(2), 137-148. Bean, J. P., & Metzner, B. S. (1985). A conceptual model of non-traditional undergraduate student attrition. Review of Educational Research, 55(4), 485–540. Bologna Communiqué = Leuven/Louvain-la-Neuve Communiqué. (2009). The Bologna Process 2020: The European higher education area in the new decade (Communiqué of the Conference of European Ministers Responsible for Higher Education, Leuven and Louvain-la-Neuve, 28–29 April 2009). Retrieved from http://www.ond. vlaanderen.be/hogeronderwijs/bologna/conference/documents/Leuven_Louvain-laNeuve_Communiqu%C3%A9_April_2009.pdf Bologna Policy Forum Statement. (2010). Retrieved from http://www.ond.vlaanderen.be/hogeronderwijs/bologna/forum2010/Vienna_BPF_Statement.pdf Bourdieu, P. (1984). Distinction: A social critique of the judgement of taste. London: Routledge. CEDEFOP. (2008). Skill Needs in Europe: Focus on 2020. Thessaloniki: CEDEFOP. Clancy, P. (2010). Measuring access and equity from a comparative perspective. In H. Eggins (Ed.), Access and equity: Comparative perspectives (pp.69–102). Boston: Sense Publishers. European Commission. (2009). New skills for new jobs: Anticipating and matching labour market and skills needs. Luxembourg: European Commission. Eurostat, Eurostudent. (2009). The Bologna Process in higher education in Europe. Luxembourg: Eurostat. Eurostudent. (2008). Social and economic conditions of student life in Europe [EUROSTUDENT III Final Report]. Bielefeld: W. Bertlesmann. Eurydice. (2009). Key data on education. Brussels: Eurydice. Florida, R. (2005). Cities and the creative class. New York: Routledge. CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 41 Leitch (2006). Prosperity for all in the global economy: World class skills. London: HMSO. Kehm, B., & Lanzendorf, U. (2006, ds.). Reforming university governance: Changing conditions for research in four European countries. Berlin: Lemmens. Kouckŷ, J. (2010). Who gets a degree? Access to tertiary education in Europe 1950–2009. Prague: Charles University. McNair, S. (2002). The invisible majority: Adults learners in English higher education. Higher Education Quarterly, 52(2), 162–178. Miclea, M. (2008). Demographics and higher education: Mediating variables, institutional responses and public policies. In L. Vl sceanu & L. Grünberg, (Eds.), Demographics and higher education in Europe: Institutional perspectives (pp. 63–77). Bucharest: Unesco-Cepes. OECD. (2009). Education at a Glance. Paris: OECD Orr, D., & Riechers, M. (2010). Organisation des Hochschulzugangs in sieben europäischen Ländern: Eine vergleichende Betrachtung [Organization of higher education access routes in seven European countries: A comparative view]. Hanover: HIS:Forum Hochschule. Witte, J. (2006). Change of degrees and degrees of change: Comparing adaptations of European higher education systems in the context of the Bologna Process. Enschede: CHEPS. CONTACT INFORMATION Dominic Orr Senior Researcher and Project Leader of EUROSTUDENT HIS-Institute for Research on Higher Education Goseriede 9 30159 Hannover Germany Email: [email protected] Telephone: +49 511 1220 372 Dr. Dominic Orr is currently the international project leader for EUROSTUDENT IV and was recently co-editor of the Eurostat/EUROSTUDENT publication “The Bologna Process in Higher Education in Europe”. He works as a senior researcher at the German higher education policy institute HIS-Institute for Research on Higher Education, in Hanover. His specialist areas of interest are comparative studies on higher education, funding and quality assurance, and social dimensions of European higher education reform. His undergraduate studies were completed at Southbank University in London and he graduated from the Technical University Dresden with a doctorate in comparative education. CJHE / RCES Volume 40, No. 3, 2010 Integrating an Aging Student Population / D. Orr 42 NOTES 1. 2. A recent publication of the European Commission, published in the light of the financial crisis in Europe emphasises that these changes will still occur despite the current developments and advises countries to invest in training and education sectors in order to fulfil this future demand and create sustainable economies (European Commission, 2009). In Figure 4, countries are referred to by their standard abbreviation. These are: AT: Austria; BG: Bulgaria; CH: Switzerland; CZ: Czech Republic; DE: Germany; EE: Estonia; ES: Spain; FI: Finland; FR: France; IE: Ireland; IT: Italy; NL: Netherlands; NO: Norway; PT: Portugal; RO: Romania; SE: Sweden; SI: Slovenia; SK: Slovak Republic; TR: Turkey. CJHE / RCES Volume 40, No. 3, 2010