1. 1 Experiences with the Adult Education Survey in Norway and cross-country comparisons of AES data

2. Basic information about the Norwegian AES Cross-country comparisons based on AES data –Selected findings from our preliminary analyses  Possibilities and limitations  Suggestions for further analyses

3. Timetable AES in Norway May – mid August 2007: –Fieldwork July- December 2007: –Processing, validation, calibration of final weights December 2007 (minor corrections later on in April 2008): –Microdata and control tables to Eurostat January 2008: –Online dissemination of first national results www.ssb.no/en/volwww.ssb.no/en/vol October 2008: –Short web-article based on tables from New Cronos www.ssb.no/vis/magasinet/analyse/art-2008-11-12-01.html October 2009: –”Adult learning in Norway and other European countries” Article in Statistics Norway’s biannual ”Utdanning SA”, a publication with statistical analyses in the field of education

4. Data collection Mode –CATI:  All respondents: 73,6 %  Participants in FED: 56,1 %  Participants in FED or NFE: 63,9 % –CAPI:  All respondents: 26,4 %  Participants in FED: 43,9 %  Participants in FED or NFE: 36,1 % Response rate –Net sample whole survey: 3330 –Net sample Eurostat part of survey (age 25-64): 3018 –Response rate (unweighted): 67,7 %

5. Questionnaire Modules not covered: –Attitudes, Social participation, Information about learning possibilities –Cultural participation (only BOOKHOME included) Variables not covered: –EDUAB,ISCDAB2 –EXIST2J –ISCEDFATH1D, ISCEDMOTH1D (Can be retrieved from registers) –ISCOFATH1D, ISCOMOTH1D (Can be retrieved from registers) –NFEPROV (A version from previous national surveys was used) –ICTSKILLS, ICTLEVELS –FRLGSKIL

6. Comparing the level of adult learning across countries Possible measures found in the AES –Participation rates in formal, non-formal and informal learning –Average number of learning activities per person/participant –Average number of hours in formal and non-formal education and training per person/participant  Unfortunately, only instruction hours are included in the AES –Homework/self-study is often the most time-consuming part, especially in formal education Advantageous to include several measures in the analysis

11. Patterns of adult learning in sub-groups of the population Educational attainment Gender Age Employment and characteristics of main job Link patterns of participation in different parts of the population to issues of motivation and perceived obstacles to adult learning Sample size varies considerably between countries –May place rather tight constraints on the level of detail in sub-population breakdowns  E.g. limited number of unemployed in the Norwegian AES data set

14. Understanding the ”Matthew- pattern” in adult learning Adults with limited formal education are over-represented amongst non- employed The impact of incentives, and the challenge of motivation: –The wage returns to workplace training are lower for those with less than secondary education (Bassanini et al. 2005: 150) –Employers also often get a higher return from training employees with tertiary education (Døving et al. 2006:159) –Previous encounters with education and training shape our ”learner identity”, in positive or negative ways (Antikainen 2006)  Benefits of a general versus stratified initial education system? –On average, adults with less education may face fewer demands for training in their daily working life – harder to see the needs/benefits of education and training?

15. Understanding the ”Matthew- pattern” in adult learning AES provides data on: –Motivation (details only for NFE activities) –Attitudes to adult learning (not included in all countries) –Obstacles to adult learning (no separation between formal/non- formal activities) –Willingness to participate (more) in education and training. Learning begets learning? Interesting to look at how motivational patterns and obstacles vary by educational attainment

19. Age differences in the main reasons why adults didn’t participate in education or training even though they wanted to participate

20. Gender and adult learning - moving beyond overall male and female participation rates AES provides opportunities to take into consideration: –Employment patterns –Household composition  Impact of having younger children –Fields of education and training –Motivation and obstacles –Etc.

21. Gender differences in the main reasons why adults didn’t participate in education or training even though they wanted to participate

27. Results from logit-analysis on participation in non-formal training amongst employed. Probability of participation, estimates for constructed individuals. Per cent SwedenNorwayGermanyGreat Britain Reference60,939,941,939,2 Woman67,842,041,049,2 ISCED 2 or below53,432,721,432,8 ISCED 5+671,247,450,341,8 25-34 years59,242,344,541,6 50-64 years53,235,135,040,3 ISCO1-3. Managers, professionals, technicians and associate professionals88,964,367,950,9 ISCO4-5. Clerks and sales77,458,956,146,3 ISCO6-7. Skilled agricultural and fishery workers, craft and related trades workers69,950,840,341,8 1-10 empl.49,931,037,230,5 50+ empl.68,044,047,342,3 Part-time57,439,836,227,3 Reference is: Male with ISCED 3+4 education, 35-49 years, ISCO8-9 (Plant and machine operators and assemblers and elementary occupations), employed full-time in a firm with 11-49 employees. Source: Adult Education Survey

28. Thank you for your attention