# Predicting the probabilities of participation in formal adult education in Hungary

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1 Péter Róbert Predicting the probabilities of participation in formal adult education in Hungary SP2 National Report Status: Version

6 Table 3. Descriptive statistics and the structure of the attitudes Attitude items Descriptive statistics* Principal component analysis** Mean Standard Communalities Factor 1+ Factor 2+ deviation (extraction) If you want to be successful at work you need to keep improving your knowledge and skills Employers should be responsible for the training of their employees The skills you need to do a job can t be learned in the classroom Education and training can help you manage your daily life better Learning new things is fun Learning gives you more self-confidence Individuals should be prepared to pay something for their adult learning * Note: Means and standard deviation refer to the five-point agreement scales (1=fully agree; 5=totally disagree). Thus, lower values mean higher agreement. ** Note: Principal component analysis of the 7 items led to 2 factors. Factor 1 has an Eigenvalue of and explains 35.2% of the total variance after rotation. Factor 2 has an Eigenvalue of and explains 16.0% of the total variance after rotation. Variance explained is 51.2 in total. Varimax rotation was applied. + Note: Factor loadings come from the rotated factor solution and values below 0.4 are not shown. 6

8 Table 4. Participation in formal adult education by attitudes toward adult education (column %) Attitude items The respondent participated in formal adult education* did not participate in formal adult education Total fully agree totally disagree fully agree totally disagree fully agree Totally disagree If you want to be successful at work you need to keep 77.7 (+) improving your knowledge and skills Employers should be responsible for the training of 47.6 (+) their employees The skills you need to do a job can t be learned in the 47.3 (+) 4.8 (+) classroom Education and training can help you manage your 61.2 (+) daily life better Learning new things is fun 41.5 (+) 1.6 (-) Learning gives you more self-confidence 68.3 (+) Individuals should be prepared to pay something for their adult learning 30.2 (+) *Note: Bold: significantly deviates form the total percentage; (+) = overrepresentation, (-) = under-representation 8

11 third sociological model is the full with both the educational and the sociological predictors of participation in formal adult education in Hungary. Table 6. Estimates from logistic regression models on the odds of participating in adult education (Unstandardized coefficients) Explanatory variables Model 1 Demogr. Model 2a Sociology Model 2b Sociology Model 2c Sociology Model 3 Attitude Model 4 Full Woman 0.636*** Aged between 25 and *** 1.845*** between 36 and *** 1.576*** over Lives in high populated area in medium populated area in low populated area - - Has child aged below ** ** aged between aged between ** aged between ISCED56 level of schooling 0934* ISCED34 level of schooling 0912* 0.946** 0.880* ISCED12 level of schooling Left school 5 years ago 3.395*** 3.370*** 2.202*** 6-10 years ago 3.004*** 3.055*** 2.054*** years ago 1.969*** 2.099*** 1.279*** more than 20 years ago Fully integrated in the LF 0.874*** ** Integrated in the LF 1.425*** Weakly integrated in the LF 2.321*** Self-employed *** ** Unemployed *** ** Works in manual job *** *** ** Att: improve skills for success *** * Att: employers responsibility Att: can t be learned in class Att: manage daily life better ** * Att: learning is fun Att: more self-confidence * Att: should pay for learning Constant *** *** *** *** *** ** Nagelkerke R square Initial -2 log likelihood* Final -2 log likelihood Decline in -2 log likelihood *** *** *** *** *** *** Degree of freedom * Note: The model contains only the constant Significance: *** p< 0.001; ** p<0.01; *p<0.05; +p<0.1 11

12 Model2a shows that Hungarians with higher level of schooling (ISCED 3-4 or the diploma holders ISCED 5-6) participate in formal adult education with larger probability in contrast to the early school dropouts (ISCED 1 and 2). Similarly to the age effects in the demographic model, the period effects are also substantial in Model 2a. The odds of participating in adult education are getting significantly smaller as more time elapsed since one has left school. In sum, Model 2a explains 19% of the variance of returning to school, this is a bit higher than in Model 1. The decline in the -2 log likelihood value is also more substantial with only 5 independent variables (degree of freedom) in comparison to 9 in Model 1. Generally Model 2b with the occupational features performs worse than Model 2a with the educational ones. The model explains only 6% with 6 predictors. However, the pattern in the effect of the occupational variables is interesting. Integration into the labour market matters in the sense that those employees who are less integrated seem to participate in adult education with higher probability (the effect sizes are growing). Nevertheless, the direction of the causal relationship is not straightforward. It is possible that these employees invest into education because they want to get better integrated. However, it is also possible that the lower degree of integration allow them to study; this is the way how they can find time to participate in adult education. 4 A further important result from Model2b is the significant negative effect for those who work in manual job, revealing that working in these occupations (ISCO job title begins with 6, 7, 8, 9) is a strong obstacle in Hungary. Model 2c shows that level of schooling and labour market and occupational indicators are strongly connected to each other. The impact of education is more moderate in this model and the pattern of labour market integration changes when it is controlled for education. In fact, unemployment and self-employment turn out to decrease the chances of returning to formal adult education. The negative impact of working in manual job is smaller but remains highly significant. Model 3 looks at the role of attitudes. All 7 items are included in the model because the bivariate investigation of relationship between the factor structure and the participation in adult education did not show significant difference for Factor 2. This model has only a small explanatory power of 5% and the decline in -2 log likelihood is significant but moderate as well. Basically, having favourable attitudes toward learning has a positive impact on the odds of participating in formal adult education. (Note, that negative sign of the estimates means here positive effect as full agreement with the statements that skills are needed for work success, or for managing life better, or learning increases self-confidence, was coded as 1 and totally disagreement was coded as 5.) The complete multivariate analysis is performed in Model 4. Apparently, the demographic, the sociological and the attitudinal characteristics are not independent form each other but they have stronger or weaker correlations. This fact influences how the explanatory variables work as they control for each other and the model shows the most influential effects. For the demographics, this is age; neither gender nor region matter anymore. Only having small child aged below 3 remains a significant obstacle of studying. For the sociological features, the role of the time since one has left school remains a strong predictor of participation in formal adult 4 This second assumption would hold better for part-time work than for temporary contract. In Hungary, parttime employment is scarce. Furthermore, employers may support less those workers who they employ only with a temporary contract. These considerations would lead to a bit bigger chance for the previous interpretation of the casual relationship: lower degree of labour market integration is the cause and participation in adult learning is the outcome and not vice versa. 12

15 Table 7. Selected estimates for the significant interaction terms between the indicators influencing participation in adult education (Unstandardized coefficients) Explanatory variables and interaction terms* Estimates Main effects Woman Aged between 25 and between 36 and over 45 - Lives in high populated area 2.480* in medium populated area in low populated area - Has child aged below aged between ** ISCED56 level of schooling ISCED34 level of schooling ISCED12 level of schooling - Left school 5 years ago 9.158*** 6-10 years ago 9.003*** years ago 6.807** more than 20 years ago - Fully integrated in the LF 4.950* Integrated in the LF 8.932** Self-employed Unemployed Attitude: improvement of skills needed for success at work ** Attitude: learning is fun Attitude: learning gives more self-confidence 0.579* Interaction terms Woman aged between * Has child aged below 3 and left school 1-5 years ago ** Has child aged below 3 and left school 6-10 years ago ** Has child aged between 6 and 13 and left school 6-10 years ago * Has child aged between 6 and 13 and left school years ago *** Having ISCED 5-6 level of schooling and living in high populated area *** Having ISCED 3-4 level of schooling and living in high populated area * Fully integrated in the LF and living in high populated area ** Fully integrated in the LF and left school 1-5 years ago ** Fully integrated in the LF and left school 6-10 years ago ** Fully integrated in the LF and left school years ago * Integrated in the LF and left school 1-5 years ago ** Integrated in the LF and left school 6-10 years ago ** Integrated in the LF and left school years ago * Self-employed and left school 1-5 years ago * Self-employed and left school 6-10 years ago * Self-employed and left school years ago Unemployed and left school 1-5 years ago * Unemployed and left school 6-10 years ago * Unemployed and left school years ago Living in high populated area and agreeing that learning is fun 0.581** Living in medium populated area and agreeing that learning is fun 0.410* Fully integrated in the LF and agrees with improvement of skills is needed for success 1.566** Unemployed and agrees with improvement of skills is needed for success Fully integrated in the LF and agrees with learning gives more self-confidence ** Integrated in the LF and agrees with learning gives more self-confidence * Unemployed and agrees with learning gives more self-confidence Constant *** 15

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