How Educational Background Is Shaping (Types Of) Higher Education Dropout
Author(s):
Sören Isleib (presenting / submitting)
Conference:
ECER 2017
Network:
14. Communities, Families and Schooling in Educational Research
Format:
Paper (Copy for Joint Session)

Session Information

14 SES 01 B JS, Higher Education, Family Influence and Dropout

Joint Paper Session NW 14 and NW 22

Time:
2017-08-22
13:15-14:45
Room:
K5.14
Chair:
Loizos Symeou

Contribution

The paper analyses the influence of parental educational background on study dropouts in the German higher education system. Education is not only a fault line within generations but also between generations. A characteristic finding for the German educational system is that educational success in school is depending on the parental educational background of students. There are some findings (Isleib/Heublein, 2016) which indicate a similar situation for higher education dropouts. Also we know that the situation and decisions prior to study as well as the concrete study decision are strongly influenced by educational background (Boudon 1974; Quast et al., 2014; Schindler 2014). Children whose parents hold an academic degree have an increased chance to enter the higher education system (Quast et al., 2014; Schindler 2014). The effect of educational background is thereby assumed to be mediated by these decisions, especially the type of school attended prior to study. But there is still a lack of research dealing with the effect of educational background on the concrete dropout decision and how it shapes different types of dropout. The question of the submitted paper is: Which are the risk factors of a higher education dropout depending on the educational background?  

The work is framed by a theoretical and interdisciplinary model of the higher education dropout process which derived from social-integrative, psychological, rational choice and habitual explanations of dropouts (Barry/Okun, 2011; Neuville et al., 2007; Robbins et al., 2004; Thomas, 2002; Tinto, 1975, 2006; for an overview see Cabrera et al., 2006; Sarcletti/Müller, 2011) developed at German DZHW. The focus of the analysis is directed on educational decisions prior to study, the transition to study with the factors study motives and information level as well as the study phase with the factors social integration, learning habits, perception of study conditions and the personal situation during the study such as work during study, financial situation and children. Educational background is measured by the (highest) parental professional qualification level. Two groups of educational background were built: Students/graduates with parents who hold no academic degree and students/graduates with at least one parent with an academic degree. The aim of the paper is to identify reasons for a higher education dropout in each of the both groups to show different risk factors in relation to the parental educational background.

 

 

Method

The used data stems from a German nationwide representative study also conducted by DZHW which addresses both dropouts and graduates (n=3.684, missings listwise excluded). Three logistic regression models with average marginal effects (AME, Mood, 2010) will be estimated. The first model shows the overall effect of parental educational background on higher education dropout. Model 2 (low educational background, n=1.844) and 3 (high educational background, n=1.840) estimate AME in each group of parental educational level.

Expected Outcomes

Results show that educational background is a risk factor for a higher education dropout which is indeed mediated by educational pathways prior to study (Model 1). Other strong factors for an increased dropout probability are extrinsic study motives, a low social integration, a negative perception of the study conditions, financial insecurity and having children. The models 2 and 3 show if the effects only occur (in terms of significance) in one group of parental education or are shaped by significant effects in both groups. Vocational education prior to study is only a risk factor for a dropout in the non-academic group of educational background (Model 2). Focusing the study motives an extrinsic study decision also is increasing the dropout probability only in this group as well as a low dedicated type of learning. Having children has the strongest effect on higher education dropout in the non-academic group. Intrinsic study motives only show an (negative) effect on dropping out in the group with a high educational background (Model 3). As a conclusion a profound study decision, a high commitment to learning and good study conditions might lead to a higher study success, especially when there is no academic family background. The first two factors are open for individual behavior and can be influenced by the students themselves, whereas study conditions need to be focused by higher education institutions. Also studying with children might be not a risk factor for dropping of study if there are more possibilities of a very flexible organization of the study. The fact that the effect of having children only occurs in the non-academic group (Model 2) indicates that there is a correlation with the familial financial support and the financial situation during the study.

References

Barry, C.., & Okun, M. (2011). Application of investment theory to predicting maintenance of the intent to stay among freshmen. Journal of College Student Retention 13: 87-107. Cabrera, L., Bethencourt, J., Pérez, P., & González Afonso, M. (2006). The problem of university dropout. RELIEVE 12: 171-203. Isleib, S. & Heublein, U. (2016). Ursachen des Studienabbruchs und Anforderungen an die Prävention. Empirische Pädagogik, 30 (3), 513-530. Neuville, S., Frenay, M., Schmitz, J., Boudrenghien, G., Noël, B., & Wertz, V. (2007). Tinto’s theoretical perspective and expectancy-value paradigm: A confrontation to explain freshmen’s academic achievement. Psychologica Belgica 47: 31-50. Quast, H., Scheller, P. & Lörz, M. (2014). Bildungsentscheidungen im nachschulischen Verlauf. Dritte Befragung der Studienberechtigten 2008 viereinhalb Jahre nach Schulabschluss. Forum Hochschule 9/2014. Hannover: DZHW. Robbins, S., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130: 261-288. Sarcletti, A., & Müller, S. (2011). Zum Stand der Studienabbruchforschung. Theoretische Perspektiven, zentrale Ergebnisse und methodische Anforderungen an künftige Studien. Zeitschrift für Bildungsforschung 1: 235-248. Schindler, S. (2014). Wege zur Studienberechtigung - Wege ins Studium? Eine Analyse sozialer Inklusions- und Ablenkungsprozesse. Wiesbaden: Springer VS. Thomas, L. (2002). Student retention in higher education. The role of institutional habitus. Journal of Educational Policy 17(4): 423-442. Tinto, V. (1975). Dropout from Higher Education. A theoretical synthesis of recent research. Review of Eductional Research 45: 89-125. Tinto, V. (2006). Research and practice of student retention: What next? Journal of College Student Retention 8: 1-19.

Author Information

Sören Isleib (presenting / submitting)
German Centre for Higher Education Research and Science Studies (DZHW), Germany

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