Session Information
Paper Session
Contribution
The investigation of students’ pathways at the university is closely related to the topic of dropout and success in higher education.
There are several possible theoretical explanations for social differences in educational attainment that is correlated with the students’ pathways at the university. According to the rational action theory approach (Boudon 1974), family background has primary and secondary effects on education choice. Reproduction of cultural capital (Bourdieu 1973; Bourdieu and Passeron 1977; Becker 1975) forms the primary impact. Secondary effect occurs during the educational decision-making process: students and parents rationally calculate the balance of cost and the benefit of different education paths and choose the most advantageous track. Since students with lower social status have to travel a longer distance towards higher education from their origin, they calculate with a higher cost, so they have different results in their investment-returns calculations.
Goldthorpe and Breen (1997) developed Boudon's rational action theory approach. According to it, during educational decision-making the final goal of students is not the absolute-measured education level but to avoid social downgrading. Since absolute measured goals of different classes are dissimilar, universal scheme of balancing costs and benefits leads to a different result depending on social origin. The higher education relevance of this approach is that in case of an eventual failure, tertiary educated parents’ children are more inclined to stay in higher education for a longer period of time and attempt different study pathways in order to achieve their final goal of university degree.
The expansion of higher education, flexible forms of training and the pull/push out effect of the labor market often lead to a fragmented, non-linear student life paths (Hagedorn 2004; Lee and Buckthorpe 2008; Hovdhaugen et al 2015).Analysis of university study outcomes (successful completion, retention or drop out) can lead to significantly different results in individual-level and course-based analyses. E.g. in course-based analyses students who leave their starting course and continue their studies in another track are considered to be dropped out, while from the point of view of individual level they are continuing their higher education.
Most of the previous analyses of student pathways are not individual but course-based, that may shelter successful non-linear study tracks. (Tinto 1993; Hagedorn 2004, Robinson 2004; Kuh et al., 2006, Tumen et al 2008; Reason 2009; Thomas, L., and E. Hovdhaugen. 2014; Tight 2020; Pusztai 2015; Hovdhaugen et al 2015; Helland and Hovdhaugen 2022; Aina et al 2022)
The aim of our research is to discover the patterns of individual student study pathways, as well as to explore the influencing factors of study pathways.
Our main hypothesis is that although a significant proportion of the students drop out of the program they originally started, but they eventually obtain a higher education through a different (detour) route. According to our hypothesis, majority of students who follow the fragmented but finally successful student path have higher-status family background. Students from lower-status families typically either take a linear student path to a lower-value program or drop out within a relatively short period of time.
While our analysis is based on data of a single country, the added value of national-level data construction allows us to examine a more universal research question concerning the general mechanism of influencing factors on student pathways. That has a great relevance concerning the social and institutional dimension of higher education success and failure in Europe.
Method
Our longitudinal analysis of students’ pathways is based on aggregated data of the Hungarian official database of the Higher Education Information System (HEIS) in the period of 2013-2022, joined together with some family background information of students based on background questionnaire of National Assessment of Basic Competencies (NABC) The Higher Education Information System (HEIS) is an official electronic register of students. All higher educational events that happened to the students during their higher education studies are recorded in it. It also includes institutional information of student’s university. Since Hungarian students have individual student ID, on the basis of the HEIS database it is possible to follow up detailed higher education history of students. Of course for data protection reasons a researcher cannot access detailed individual student data, but it was possible to retrieve aggregated variables based on which it was possible to reliably analyze the students' individual level pathways in Hungarian higher education, controlled by family background. For the present analysis students who entered ISCED5 or ISCED6 or undivided long-term courses of Hungarian higher education for the first time in the 2013/14 academic year form starting population of 45171 students. We followed the students’ pathways (student events) of this basic population in a semester breakdown until the end of the second semester of the 2021/2022 academic year. Our analysis was based on two aggregate basic indicators of student pathways: The “Individual Student Success Indicator” shows whether the student has obtained a (some level of) higher education degree and whether additional (higher) education is expected. The “Student Pathway Summary Indicator” shows the summary of student pathway patterns starting from the first entry into higher education to the end of examined time interval. It contains 5 categories of (1) Straight path 1: Successfully completed the initial course within the “normal” time +2 semesters; (2) Straight path 2: Successfully completed initial course beyond the “normal” time +2 semesters; (3) Successful pathfinders: Did not successfully complete the initial training, but obtained some other higher education degree; (4) Pathfinders at risk: Did not successfully completed any study, but higher education is still in progress (5) Dropouts: left higher education without a degree. Besides the descriptive analyses of correlation between these two basic variables and characteristics of initial higher education course with family background and personal characteristics, multinomial logistic regression models were applied for disclosing causal effects.
Expected Outcomes
The aim of our research was to discover the patterns of individual student study pathways in Hungarian higher education, as well as to explore the influencing factors of study pathways (especially the effect of family background and the specifics of the initial training). The longitudinal analysis of students’ pathways was based on aggregated data of the official database of the Higher Education Information System (HEIS) in the period of 2013-2022. We paid special attention to the patterns of fragmented, non-linear student life paths. Our theoretical approach was based on the rational action theory. This analysis confirmed our main hypothesis: 39% of students who were considered to be dropped out according to the course-based statistics did not actually drop out of higher education just switched to another track. Majority of them (28%) have successfully completed some (other) higher education course while and 10,5% have not graduated (yet), but are still enrolled in higher education as students. This fact draws attention to the importance of analyzing the individual student's life path during examination of students’ success in higher education. Among those leaving their first training, the ratio of successful passers and dropouts is around average. Therefore, if someone modifies his/her study path (drops out of his/her first course), it does not increase the probability of dropping out at the individual level, and only minimally increases the probability that he will be stuck in higher education for a very long time without a successful outcome. Our analysis also confirmed our hypothesis concerning effect of family background on students’ pathways in higher education: majority of students who follow the fragmented but finally successful student path have higher-status family background. This results partially confirmed Goldthorpe and Breen (1997) rational action theory approach as well.
References
Aina et al (2022): The determinants of university dropout: A review of the socio-economic literature. Socio-Economic Planning Sciences Volume 79, February 2022 Becker, G. S. (1975): Human Capital: A theoretical and empirical analysis with special reference to education. New York, Columbia University. Boudon, R. (1974): Education, opportunity and social inequality. New York, Wiley. Bourdieu, P. (1973): Cultural reproduction and social reproduction. In Brown, R. K. (ed.): Knowledge, education and cultural change. London, Tavistock. Bourdieu, P. – Passeron, J.-C. (1977): Reproduction in education, society and culture. Beverly Hills, Sage. Breen, R., & Goldthorpe, J. H. (1997). Explaining educational differentials: Towards a formal rational action theory. Rationality and society, 9(3), 275-305. Hagedorn, L. S. (2004): How to define retention: A New Look at an Old Problem: http://files.eric.ed.gov/fulltext/ED493674.pdf. Helland, H., and Hovdhaugen, E. (2022): Degree completion in short professional courses: does family background matter?, Journal of Further and Higher Education, 46:5, 680-694, Hovdhaugen, E. et al (2015): Dropout and completion in higher education in Europe: Annex 1: Literature review. European Union. https://publications.europa.eu/hu/publication-detail/-/publication/965f5f38-0dd0-11e6-ba9a-01aa75ed71a1/language-en Kuh, G. D. et al (2006): What Matters to Student Success: A Review of the Literature. http://nces.ed.gov/npec/pdf/kuh_team_report.pdf. Lee, C., and Buckthorpe, S. (2008): Robust Performance Indicators for Non‐completion in Higher Education. In Quality in Higher Education 14 (1): 67–77. Pusztai, G. (2015): Pathways to Success in Higher Education. Rethinking the Social Capital Theory in the Light of Institutional Diversity. Frankfurt am Main, Berlin, Bern, Bruxelles, New York, Oxford, Wien, 2015. 278 pp., Reason, R. D. (2009): Student Variables that Predict Retention: Recent Research and New Developments. In NASPA Journal 46 (3), pp. 482–501. Robinson, R. (2004): Pathways to completion: Patterns of progression through a university degree. Higher Education (2004) 47: 1. pp 1–20 Thomas, L., and E. Hovdhaugen. (2014): Complexities and Challenges of Researching Student Completion and Non-completion of HE Programmes in Europe: A Comparative Analysis between England and Norway.” European Journal of Education 49 (4): 457–470. Tight, M. (2020): Student Retention and Engagement in Higher Education.” Journal of Further and Higher Education 44 (5): 689–704. Tinto, V. (1975): Dropout from Higher Education: A Synthesis of Recent Research.” Review of Educational Research 45 (1): 89–125. Tinto, V. (1993): Leaving College: Rethinking the Causes and Cures of Student Attrition. 2nd ed. Chicago: University of Chicago Press. Tumen, S. et al (2008): Student pathways at the university: patterns and predictors of completion, Studies in Higher Education, 33:3, 233-252
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