10 SES 07 E, Research on Teacher Induction and Early Career Teachers
The vocational education and training (VETNET) system in Germany faces several challenges. A first problem is that we do not have enough skilled workers in training occupations. There are bottlenecks in various industries, especially in the industrial-technical sector as well as in the nursing and health care professions (Bundesagentur für Arbeit, 2017). One way of tackling this shortage is to integrate persons with few opportunities on the labor market, e.g. refugees or low-skilled students. However, up to now, it is difficult for people with a migration background or a lower secondary school leaving certificate (German Hauptschulabschluss) to obtain an apprenticeship (Blaß & Himmelrath, 2016). We therefore need, on the one hand, more trainees in the dual training model and, on the other hand, a vocational system with teachers who can deal with diverse persons.
A second problem is the lack of teachers at vocational schools that will become even worse in the future. In Berlin, for example, 44 % of the teacher demand will not be covered in 2023 (Senatsverwaltung für Bildung, Jugend und Wissenschaft, 2016). So, we need not only more apprentices, but also more teachers at vocational schools to counteract the shortage of skilled workers.
But there is a third problem: Too few persons decide to become vocational school teachers, especially in industrial-technical and person-oriented disciplines (Lange & Sülflow, 2017). Universities therefore urgently need to attract more student teachers and guide them successfully through their studies. This can be achieved, among other things, by a target-group-specific approach and recruitment strategies as well as needs-oriented counseling in the phase of choosing a course of study or reorienting one’s studies. To this end, it is important to learn more about the people who decide to become vocational school teachers and what their motives are (Driesel-Lange, Morgenstern, & Keune, 2017). However, research on preservice teachers’ career motivation has so far concentrated mainly on the teaching profession in the general education system (among others Retelsdorf & Möller, 2012; Richardson & Watt, 2014; Rothland, 2014).
The current study deals with the third problem and examines the career motivation of students who want to become vocational school teachers. A previous study showed that preservice vocational school teachers mostly decide because of intrinsic motives – like preservice general school teachers (Rothland, 2014) – but utility (i.e. financially security or time for family, friends, and hobbies) as an extrinsic motive is also a relevant reason for choosing this profession (Micknaß, Ohlemann, Pfetsch, & Ittel, in press). It is still unclear how the individual motive facets are related to each other. Therefore, the current study investigates which different types of career motivation there are and how we can describe these types (based on individual variables, teacher competencies, and decision security).
In the winter semester 2017/18, we surveyed 314 preservice teachers for vocational schools by questionnaire in the German university locations Berlin (n = 50), Osnabrück (n = 152), and Hannover (n = 112). The questionnaire contains the following: (1) individual and study-related information; (2) career choice motives measured with the standardized Motivation for Choosing Teacher Education Questionnaire (FEMOLA; Pohlmann & Möller, 2010); (3) teacher competencies surveyed with four scales expertise, education, diagnostics and media didactics out of the Instrument for Recording Vocational Self-Concepts of Preservice Teachers (ERBSE-L; Retelsdorf, Bauer, Gebauer, Kauper, & Möller, 2015); and (4) the decision security in career choice (Rühl, Förster, Strauß, Kaspar, & König, 2016). The individual and study-related information we surveyed were age, gender, academic progress (which means bachelor’s or master’s degree), occupational field of study (industrial-technical subjects, nutrition/food science/ecotrophology or nursing/health science), and prior pedagogical experience by checking none, one, or several of eight possible pedagogical activities (i.e. babysitting or tutoring). FEMOLA consists of the six scales educational interest, subject-specific interest, ability beliefs as intrinsic motives, and utility, social influences and the low level of difficulty of the course of study as extrinsic motives. The career choice motives, teacher competencies, and decision security were answered on a four-point Likert scale ranging from 1 = ‘does not apply at all’ to 4 = ‘applies exactly’. All scales have a good or very good internal consistency. In the first step, we performed a series of latent profile analysis (LPA) to identify groups with the same characteristics in the career choice motivation (based on the FEMOLA scales). In the second step, we examined the identified groups with regard to their individual and study-related information, teacher competencies and decision security. We performed analysis of variance (MANOVA/ANOVA) for metrical variables and Cramer’s V test for categorical variables (Field, 2018). LPA were performed using Mplus version 8, all other analyses were computed with SPSS 25.0.
Using the decision criteria outlined in Nylund, Asparouhov, and Muthén (2007), the results of the latent profile analysis show the best solution with five profiles (SABIC = 2782.68; BLRT = -1360.10, p = .00). The average latent class probabilities for the most likely latent class are over all five profiles .81 or higher. The two groups with the highest means in the intrinsic motives educational interest, subject-specific interest and ability beliefs we called ‘the intrinsic’ (n = 49) and ‘the intrinsic-extrinsic’ (n = 65). While the first group has the lowest means in the extrinsic motives, the other one has comparatively high means in the extrinsic motives utility and social influences. The biggest group (n = 133) we describe as ‘the moderate intrinsic’, because their highest means are in intrinsic motives, but all below the means of the intrinsic and the intrinsic-extrinsic. Utility is also a decisive motive for the moderate intrinsic. The fourth group has the highest mean in the motive utility, and much higher than intrinsic motives; so, we called this group ‘the pragmatic’ (n = 38). The fifth group is the only with comparably low educational interest. Subject-specific interest and utility are their two highest rated motives. Social influences and low level of difficulty of the course of study are not relevant for their decision. So, we called this group ‘the subject-specific pragmatic’ (n = 29). These five groups differ significantly in their age, teacher competencies and decision security in career choice. In gender, study progress, and occupational field we found no significant differences. The subject-specific pragmatic has the lowest decision security why we considered them a possible risk group for dropping out of studies. Further results and practical implications for the recruitment and counseling of students will be presented and discussed.
Blaß, K. & Himmelrath, A. (2016). Berufsschulen auf dem Abstellgleis. Wie wir unser Ausbildungssystem retten können. Hamburg: edition Körber-Stiftung. Bundesagentur für Arbeit. (2017). Fachkräfteengpassanalyse (Berichte: Blickpunkt Arbeitsmarkt). Nürnberg. Driesel-Lange, K., Morgenstern, I. & Keune, M. (2017). Wer wird Lehrer/in am Berufskolleg? Die Unterstützung von Professionalisierungsprozessen angehender Lehrpersonen für die Berufsbildung. In M. Becker, C. Dittmann, J. Gillen, S. Hiestand & R. Meyer (Hrsg.), Einheit und Differenz in den gewerblich-technischen Wissenschaften. Berufspädagogik, Fachdidaktiken und Fachwissenschaften (S. 368–387). Berlin: LIT. Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th edition). Los Angeles: Sage. Lange, S. & Sülflow, A. (2017). Aktuelle Entwicklungen der Studierendenzahlen in beruflichen Lehramtsstudiengängen: Verlieren wir zu viele Studierende im Übergang vom Bachelor- in das Masterstudium? Die berufsbildende Schule, 69 (2), 65–71. Micknaß, A., Ohlemann, S., Pfetsch, J. & Ittel, A. (in press). Berufswahlmotive von Studierenden des beruflichen Lehramts. In F. Gramlinger, C. Iller, A. Ostendorf, K. Schmid & G. Tafner (Hrsg.), Bildung = Berufsbildung?! Konferenzpublikation der 6. BBBFK 5.-6.7.2018 in Steyr. Bielefeld: wbv. Nylund, K. L., Asparouhov, T. & Muthén, B. O. (2007). Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study. Structural Equation Modeling, 14 (4), 535–569. Pohlmann, B. & Möller, J. (2010). Fragebogen zur Erfassung der Motivation für die Wahl des Lehramtsstudiums (FEMOLA). Zeitschrift für Pädagogische Psychologie, 24 (1), 73–84. Retelsdorf, J., Bauer, J., Gebauer, S. K., Kauper, T. & Möller, J. (2015). Erfassung berufsbezogener Selbstkonzepte angehender Lehrkräfte (ERBSE-L). Zusammenstellung sozialwissenschaftlicher Items und Skalen. Retelsdorf, J. & Möller, J. (2012). Grundschule oder Gymnasium? Zur Motivation ein Lehramt zu studieren. Zeitschrift für Pädagogische Psychologie, 26 (1), 5–17. Richardson, P. W. & Watt, H. M.G. (2014). Why People choose teaching as a career. An expectancy-value approach to understanding teacher motivation. In P. W. Richardson, S. A. Karabenick & H. M.G. Watt (Eds.), Teacher Motivation. Theory and Practice (pp. 3–19). Hoboken: Routledge. Rothland, M. (2014). Warum entscheiden sich Studierende für den Lehrerberuf? In E. Terhart, H. Bennewitz & M. Rothland (Hrsg.), Handbuch der Forschung zum Lehrerberuf (S. 349–385). Münster: Waxmann. Rühl, A.-M., Förster, S., Strauß, S., Kaspar, K. & König, J. (2016). Zukunftsstrategie Lehrer*innenbildung Köln (ZuS): Heterogenität und Inklusion gestalten. Teilprojekt Qualitätssicherung. Hochschulweites Bildungsmonitoring. Befragung von Lehramtsstudierenden. Skalendokumentation (Allgemeiner Teil). 1. Messzeitpunkt. Universität zu Köln. Senatsverwaltung für Bildung, Jugend und Wissenschaft. (2016). Bericht zur mittelfristigen Lehrkräftebedarfsplanung. 90. Sitzung des Hauptausschusses vom 6.11.2015.
The programme is updated regularly (each day in the morning)
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.