Trends, Investment-Patterns and Coherences of Job-Related Participation in Adult Education and Training from 2007 to 2010

Author(s):

Sarah Widany(presenting / submitting)Johannes Christ(presenting)

Conference:

ECER 2015

Network:

02. Vocational Education and Training (VETNET)

Format:

Paper

Session Information

02 SES 05 B, Competence in VET: Transitions in Perspectives

Paper Session

Time:

2015-09-09

11:00-12:30

Room:

324. [Main]

Chair:

Margaret Eleanor Malloch

Discussant:

Trine Deichman-Sørensen

Contribution

Within the Lisbon Agenda of the European Union financing of lifelong learning is regarded as key factor to enhance participation in adult education and training (AET) (Commission of the European Communities 2003). The financing structure in the field of AET is characterized by public and private spending and various financing models are discussed in order to provide a sufficient level of participation and to avoid underinvestment (e.g. Falch & Oosterbeek 2011). Cross-country comparisons show that participation rates vary considerably between western industrialized countries and so do the proportions of public and private spending. These variations can be related to inter alia structural differences in the educational system and other institutional factors (Brunello 2001, Bassanini et al. 2005) as well as to varying degrees of public support in overcoming barriers to participation in AET (Rubenson & Desjardins 2009). However, three major financial sources are prevalent in all countries: companies investing in their employees learning activities; individuals who pay for the participation in AET; and different ways of public funding. In Germany, companies and employees are the main financing source for job related training in the employed workforce; the first bearing a higher proportion of the direct costs than the latter. Public funding has a minor part (Kuckulenz 2007).

In line with human capital theory, different sources of funding imply different anticipated returns of investment and thus different logics of investment (e.g. Becker 1980). This theoretical assumption is further supported and developed in theories of segmented labour markets, in which learning on the job or participation in further education are regarded as a principal element of internal labour markets within large companies and the civil service, thus providing beneficial opportunity structures for AET. Whereas, in occupational labour markets it is the employees themselves who provide for AET. On the external labour market for a lack of returns, neither employers nor their employees have incentives to invest in AET (e.g. Doeringer & Piore 1971).

Differentiating segments of AET according to the source of financing, analyses show participation patterns that correspond to the theoretical assumptions above. Participation in company-sponsored AET is by far the largest segment. Participation is more likely for employees in the public sector or in large firms and altogether depends foremost on characteristics related to the company and employment context. Whereas the likelihood to participate in individual financed AET is predicted best by individual characteristics such as the educational level, age and sex amongst others (Schömann 2013:105, Brunello et al. 2007). Furthermore, sources of financing can overlap. In this segment of co-financed AET, both employers and employees invest in participation either monetarily or in the form of time (during/outside working hours). In this case, company-related and individual influencing factors concurrently shape participation patterns. Corresponding to segmentation theories the mobility of participation between different segments is rather low: If individuals participate in more than one learning activity, in the great majority the accumulation of participation takes place within one segment (Kaufmann/Widany 2013). In addition to varying patterns of selectivity regarding participation, the three segments also vary according to certain characteristics, e.g. aim, scope, costs.

The paper investigates the selectivity of participation in job-related AET, taking into account different segments according to the source of financing. A longitudinal perspective will gain additional insight as the accumulation of single participations can be observed in the course of time. Thereby, it is of special interest if the accumulation is persistent within one segment of further education as suggested by segmentation theory. Furthermore, if transitions between different segments occur, it will be investigated how these participations can be related against the backdrop of the employment context.

Method

The analysis is based on survey data of the German project "Further Training as a Part of Lifelong Learning" (WeLL: Berufliche Weiterbildung als Bestandteil Lebenslangen Lernens), a panel study with a particular focus on further vocational training. WeLL is a linked employer-employee data set including information on several companies in Germany that can be linked to longitudinal information on the associated employees in four annually repeated waves from 2007 until 2010. The data set’s sampling frame basically followed two steps: In a first step a stratified sample of 149 companies in Germany was drawn with criteria of company size and industrial sector. In a second step individuals employed in these companies were randomly selected and surveyed within the four waves. The scientific use files used for the analysis covers 6,404 employees within the first wave in 2007, 4,894 in 2008, 4,930 in 2009 and 3,781 in 2010 (Bender et al. 2008; Huber & Schmucker 2012). A valid solution for analyzing varying participation patterns in AET is the operationalization of AET in three different segments according to the source of financing: company-sponsored, individual financed and co-financed AET (as shown above). Because of its longitudinal design and a large collection of training information as well as a variety of employee’s characteristics and the conditions of employment WeLL is a promising data set for analyzing participation patterns concerning the stability of segment-specific participation on the individual level and transitions between different segments of participation in particular. First, descriptive statistics will show participation rates, trends and developments as well as different features, e.g. costs, volume and aims of participation in the different segments. Segment-specific selectivity is analyzed controlling the impact of several socio-demographic and job-related predictor variables (e.g. age, educational level, sex, industrial sector, company size) in multivariate models. The longitudinal design of the data set enables the identification of factors promoting or preventing stable participation rates within one segment or across different segments. The selection of the predictor variables refers to theoretical considerations and existing empirical research findings as shown above.

Expected Outcomes

First, we expect to reproduce the segment-specific participation patterns and characteristics of AET (see above) as stated in previous research and thereby strengthen the need for a differentiated approach within the analysis of participation in AET. Against the backdrop of the financial crisis, the economic development in the reference period is relatively dynamic. However, we expect minor changes in participation rates and characteristics over the course of time and a rather high stability in selectivity and intraindividual participation patterns. This assumption is based on a relatively weak link between participation in AET and economic trends like unemployment or GDP-rates in recent years and an overall high stability of selectivity in participation patterns (see e.g. Seifried/Berger 2011, Grund/Martin 2012, Widany 2014). Albeit, on the individual level opportunity structures for participation will vary over the course of time occasionally. Thus, the accumulation of adults’ learning activities is realized by different means of financing. Transitions between different segments of financing can be related to changes in the employment context, especially career mobility. Furthermore, transitions can be related to different characteristics of the learning activity, such as certification, initiative or intentions connected to the learning activity.

References

Bassanini, Andrea; Booth, Alison; Brunello, Giorgio; Paola, Maria De; Leuven, Edwin (2005): Workplace Training in Europe. IZA Discussion Paper No. 1640. Institute for the Study of Labor (Bonn). Available online at http://ftp.iza.org/dp1640.pdf. Becker, Gary S. (1980): Human capital. 2nd revised edition. [S.l.]: Univ Of Chicago Press. Bender, Stefan; Fertig, Michael; Görlitz, Katja (2008): WeLL - unique linked employer employee data on further training in Germany. Essen: RWI (Ruhr economic papers, 67). Brunello, Giorgio (2001): On the complementarity between education and training in Europe (IZA Discussion paper series, No. 309). Available online at http://www.econstor.eu/bitstream/10419/21164/1/dp309.pdf. Brunello, G.; Garibaldi, P.; Wasmer, E. (2007): Education and Training in Europe. Oxford: Oxford Univ. Press. Commission of the European Communities (2003): Investing efficiently in education and training: an imperative for Europe. Brussel (COM(2002) 779 final). Available online at http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2002:0779:FIN:EN:PDF. Doeringer, Peter; Piore, Michael J. (1971): Internal labor markets and manpower analysis. Lexington: Lexington Books. Falch, Torberg; Oosterbeek, Hessel (2011): Financing lifelong learning: (EENEE Analytical Report No. 10). Available online at http://www.eenee.de/portal/page/portal/EENEEContent/_IMPORT_TELECENTRUM/DOCS/EENEE_AR10.pdf. Grund, Christian; Martin, Johannes (2012): Determinants of further training – evidence for Germany. In The International Journal of Human Resource Management 23 (17), pp. 3536–3558. DOI: 10.1080/09585192.2011.654347. Huber, Martina; Schmucker, Alexandra (2012): Panel "WeLL". Arbeitnehmerbefragung für das Projekt "Berufliche Weiterbildung als Bestandteil Lebenslangen Lernens". Nürnberg (FDZ-Datenreport. Dokumentation zu Arbeitsmarktdaten, 03/2012). Available online at http://doku.iab.de/fdz/reporte/2012/DR_03-12.pdf Kaufmann, Katrin; Widany, Sarah (2013): Berufliche Weiterbildung – Gelegenheits- und Teilnahmestrukturen. In Zeitschrift für Erziehungswissenschaft 16 (1), pp. 29–54. DOI: 10.1007/s11618-013-0338-8. Kuckulenz, A. (2007): Studies on Continuing Vocational Training in Germany: An Empirical Assessment. Heidelberg: Physica-Verlag. Rubenson, K.; Desjardins, R. (2009): The Impact of Welfare State Regimes on Barriers to Participation in Adult Education: A Bounded Agency Model. In Adult Education Quarterly 59 (3), pp. 187–207. DOI: 10.1177/0741713609331548. Schömann, Klaus (2013): Labour market transitions and dynamics of transitions in Germany. In A. Jobert, C. Marry, H. Rainbird, L. Tanguy (Eds.): Education and Work in Great Britain, Germany and Italy: Taylor & Francis, pp. 93–111. Seifried, Jürgen; Berger, Stefanie (2011): Determinanten der Weiterbildungsbeteiligung. In Zeitschrift für Berufs- und Wirtschaftspädagogik 107 (1), pp. 138–152. Widany, Sarah (2014): Weiterbildungsbeteiligung im Trend. Die Teilnahme von Akademiker_innen an beruflicher Weiterbildung im Zeitverlauf - 1991 bis 2010. Frankfurt am Main: Peter Lang.

Author Information

Sarah Widany (presenting / submitting)

Freie Universität Berlin

Further Education and Educational Management

Berlin

Johannes Christ (presenting)