Section A: Dropout focus of research
A.1 Which overall dropout aspect are in focus in the research?
Causes of dropout
Causes of dropout. The authors write: "Our main focus concerns the effects of in-class rank, based on the stu- dent’s pre-university qualifications, on their dropout probability." (p. 253).
A.2 If the study adresses causes: Which causes are adressed?
Socioeconomic causes
Socioeconomic causes as operalionalized by different social class-categories.
Sexrole/gender
Gender.
Insufficient prior competence
- Type of school (base: local education authority), ), - Prior qualifications (i.e. type of prior qualifications (A- levels etc.), number of A-levels, A-level score, A-level in mathematics).
Unsuccessful integration of new student in university life
Accommodation (base: university accommodation).
Other causes (please specify)
Besides the in-class heterogeneity/coefficient of variation concerning A-level scores in each class and each stu-
dents' individual A-level score (averaged across the sub- jects taken) and each students' A-level rank, other co- variates and control variables inlcuded in the final anal- yses are: - Gender, - Age, - Non-UK fee student, - Ac- commodation (base: university accommodation), - Part- time student, - On a 4 year programme, - Social class, - Type of prior school (base: local education authority), - Pre-university qualifications (e.g. A-levels, Highers, De- gree already), - The number of A-levels taken, - A-level in maths. Also, in a supplementary analysis the interaction effect between each students' A-level rank and the rank of the student's university is included to test hypothesis number three.
A.3 If the study addresses dropout reduc- ing measures: Which measures are evalu- ated?
Not applicable. This study does not address dropout reduc- ing measures.
A.4 If the study addresses dropout reduc- ing measures: Which effects are re-
searched?
Not applicable. This study does not address dropout reduc- ing measures.
A.5 If the study addresses what happens to dropouts after leaving university: Give details on the further paths of the drop- outs
Not applicable. This study does not address what happens to dropouts after leaving university.
A.6 Abstract
Please type in an abstract2768140
Arulampalam, W., Naylor, R. A. & Smith, J. P. (2005).
Effects of in-class variation and student rank on the probability of withdrawal: cross-section and time-series analysis for UK university students. Economics of Educa- tion Review, 24, 251–262.
From individual-level data for nine entire cohorts of un- dergraduate students in UK universities, binomial logit regression analyses of the probability that an individual will drop out of university during their first-year are con- ducted. The authors examine the 1984–85 to 1992–93 cohorts of students enrolling full-time for a 3 or 4-year course. They focus on the sensitivity of the probability of withdrawal to the individual’s prior qualifications relative to those of the other students in their university course. It is shown not only that weaker students are more likely to withdraw, but also that the extent of variation in prior qualifications within the student’s university degree course also exerts an influence on the individual’s proba- bility of withdrawal. It is also found that withdrawal
behaviour varies across universities according to a measure of average university student quality.
Assessed Weight of Evidence: High.
8 Appendix 3: Characteristics of the studies available for the synthesis
Country of conduct Number of
studies
UK 11
Germany 7
The Netherlands 7
Italy 4
Denmark, Spain 3
Finland, Norway 2
Austria, Belgium, France, Sweden 1
Table 8.1 Country of conduct
N=43, since one systematic review is not included in the table.
Publication type Number of
documents
Journal article 36
Report 5
Working paper 5
Book 3
Chapter in a dissertation 2
Table 8.2 Publication type
N = 51. There are 44 primary documents and 7 secondary documents.
Curriculum area(s) investigated Number of studies All/close to all (e.g. entire cohorts of high school graduates,
or an entire university) 27
Medicine 5
Business Studies and Economics 3
Science 2
Educational Science 1
Information and communication technology (ICT) 1
Law 1
Psychology 1
Social sciences 1
Table 8.3 Curriculum area(s) investigated
N= 42, since this table only includes those studies which address the review question ‘why do such dropout phenomena occur at universities?’.
Educational level Number of
studies
Degree completion 21
One or more specific semesters 12
Course completion 4
Completed a university degree (independent of degree enrolled in) 3
Other/not stated 3
Table 8.4 Educational level at which dropout is investigated N=43, since one systematic review is not included in the table.
Level of analysis Number of studies
System of higher education 21
University 9
Faculty 8
Department/course of study 5
Table 8.5 Analytical level at which dropout is investigated N=43, since one systematic review is not included in the table.
Review question addressed Number of
studies
‘Why do such dropout phenomena occur at universities?’ 42
‘What can be done by the universities to prevent or reduce such dropout
phenomena? 3
Table 8.6 Review question addressed
N=44. There are 45 answers since one study (Qualter et al., 2009) was found to address both review question.
Possible determinants of dropout investigated Number of studies
Socioeconomic causes 26
Insufficient prior competence 25
Gender 23
Unsuccessful integration of new student in university life 13
Inadequate learning processes at university 12
Wrong choice of studies/flaws in the information or guidance system 10
Ethnicity 8
Psychosocial conditions 7
Other causes (please specify) 29
Table 8.7 Possible determinants of dropout investigated
N = 42, since 42 studies were found to investigate possible determinants of dropout.
There are 153 answers since all studies address more determinants of dropout.
Since the studies often enquire on more variables within each of the categories in the table, the list can- not be used for calculating the number of specific variables used in the studies to investigate the possi-
ble determinants of dropout.
Overall study design Number of
studies
Cross-sectional study 28
Secondary data analysis 8
Experiment with non-random allocation to groups 4
Cohort study 3
Random experiment with random allocation to groups 1
Views study 1
Table 8.8 Overall study design
N=43, since one systematic review is not included in the table.
There are 45 answers, as two studies have been coded as having applied more than one study design.
Study timing Number of studies
Cross-sectional 24
Prospective 15
Retrospective 7
Table 8.9 Study timing
N=43, since one systematic review is not included in the table.
There are 45 answers, as two studies have been coded as having applied more than one study design.
Data collection Number of
studies
Self-completion questionnaire 24
University administrative student level data 23 Secondary data (publicly available statistics or individ-
ual level register data) 11
One-to-one interview 6
Curriculum-based assessments 2
Examinations 2
Clinical test 1
Focus group interview 1
Observation 1
Other documentation 1
Table 8.10 Data collection
N = 44. There are 72 answers, as more studies make use of more than one data source.
Achieved sample size Number of studi- es
50-250 5
250-500 2
500-1,000 5
1,000-10,000 18
10,000-50,000 3
50,000-100,000 5
100,000 or more 2
Other sample unit 1
Not stated/unclear 3
Table 8.11 Achieved sample sizes
N = 43, since one systematic review is not included in the table.
There are 44 answers, as one study investigates two samples.
The term ‘Other sample unit’ refers to one study (Soo, 2009) which oper- ates with a sample of ‘study-year-subjects’. The term ‘Not stated/Unclear’
covers studies that are too poorly reported to either explicitly or implicitly determine the sample size.
Main method of data analysis Number of
studies
Multivariate analysis 37
Bivariate correlations and descriptive statistics 6 Table 8.12 Main method of data analysis
N = 43, since one systematic review is not included in the table.
High Medium Low 11. Weight of evidence A: Taking account of all quality assessment issues,
can the study findings be trusted in answering the study question(s)? 21 22 1 12. Weight of evidence B: Appropriateness of research design and analysis
for addressing the question, or sub-questions, of this specific systematic review
21 21 2
13. Weight of evidence C: Relevance of particular focus of the study (includ- ing conceptual focus, context, sample and measures) for addressing the question, or sub-questions, of this specific systematic review.
21 22 1
14. Weight of evidence D: Overall weight of evidence 19 25 0
Table 8.13 Weight of evidence N = 44 for each row.
9 References for the studies available for the synthesis
Listed below are all references to the 44 studies available for the synthesis, that is, studies which in the research mapping were assigned an overall weight of evidence of medium or high.
ITT2772931: Albrecht, A., & Nordmeier, V. (2001). Ursachen des Studienabbruchs in Physik. Eine explorative Studie. Die hochschule, 2.
ITT2758729: Araque, F., Róldan, C., & Salguero, A. (2009). Factors influencing university drop out rates. Computers & Education, 53, 563–574.
ITT2763854: Argentin, G., & Triventi, M. (2011). Social inequality in higher education and labour market in a period of institutional reforms: Italy, 1992–2007. Higher Education, 61(3), 309–323.
¤ITT2777620: Arulampalam, W., Naylor, R.A., & Smith, J. P. (2004a). A hazard model of the proba- bility of medical school drop-out in the UK. Journal of the Royal Statistical Society: Series A, 167(1), 157–178.
ITT2761966 (secondary reference to ITT2777620): Arulampalam, W., Naylor, R.A., & Smith, J. P.
(2001). A hazard model of the probability of medical school dropout in the United Kingdom. IZA Discussion Paper, 133.
ITT2768140: Arulampalam, W., Naylor, R. A., & Smith, J. P. (2005). Effects of in-class variation and student rank on the probability of withdrawal: cross-section and time-series analysis for UK uni- versity students. Economics of Education Review, 24, 251–262.
ITT2770586: Arulampalam, W., Naylor, R. A., & Smith, J. P. (2007). Dropping out of medical school in the UK: Explaining the changes over ten years. Medical Education, 41, 385–394.
ITT2761965 (secondary reference to ITT2770586): Arulampalam, W., Naylor, R. A., & Smith, J. P.
(2004b). Factors affecting the probability of first-year medical student dropout in the UK: A logistic analysis for the entry cohorts of 1980-1992. Warwick Economic Research Papers, 618.
ITT2777714: Baars, G. J. A., Stegers-Jager, K. M., Stijnen, T., & Splijnter, T. A. W. (2009a). A model to predict student failure in the first year medical curriculum. In: Baars, G. J. A. (ed.) Factors relat- ed to student achievement in medical school. Hague: Lemma.
ITT2777715 (secondary reference to ITT2777714): Baars, G. J. A., Stegers-Jager, K. M., Stijnen, T., &
Splijnter, T. A. W. (2009b). Exploratory study to improve a model to predict student failure in the first-year medical curriculum. In: Baars, G. J. A. (ed.) Factors related to student achievement in medical school. Hague: Lemma.
ITT2770591: Belloc, F., Maruotti, A., & Petrella, L. (2009). University drop-out: an Italian experi- ence. Higher Education, 60(2), 127–138.
ITT2770592 Bennett, R. (2003). Determinants of Undergraduate Student Drop Out Rates in a Uni- versity Business Studies Department. Journal of Further and Higher Education, 27(2), 123-141.
ITT2771809: Bodin, R. M & Millet, M. (2011). L'université, un éspace de regulation: L'abandon dans les 1ers cycle à l'aune de la socialisation universitaire. Sociologie, 3(2), 225-242.
ITT2762040: Di Pietro, G. (2004). The determinants of university dropout in Italy: A bivariate probit model with sample selection. Applied Economics Letters, 11, 187-191.
ITT2758885: Di Pietro, G., & Cutillo, A. (2008). Degree flexibility and university drop-out: The Ital- ian experience. Economics of Education Review, 27(5), 546-555.
ITT2758942: Garcés, A., & Sánchez-Barba, L. F. (2011). An alternative educational approach for an Inorganic Chemistry laboratory course in Industrial and Chemical Engineering. Chemistry Education Research and Practice, 12(1), 101-113.
ITT2758964: Glaesser, J. (2006). Dropping out of further education: A fresh start? Findings from a German longitudinal study. Journal of Vocational Education and Training, 58(1), 83–97.
ITT2762072: Glocker, D. (2011). The effect of student aid on the duration of study. Economics of Education Review, 30, 177–190.
ITT2758994: Hailikari, T. K., & Nevgi, A. (2010). How to Diagnose At-risk Students in Chemistry: The case of prior knowledge assessment. International Journal of Science Education, 32 (15), 2079–
2095.
ITT2772961: Heublein, U., Hutzsch, C., Schreiber, J., Sommer, D., & Besuch, G. (2010). Ursachen des Studienabrruchs in Bachelor- und in herkömmlichen Studiengängen: Ergebnisse einer Bun- desweiten Befragung von Exmatrikulierten des Studienjahres 2007/2008. HIS: Forum Hochschule, 2. Berlin: HIS GmbH.
ITT2772964: Heublein, U., Spangenberg, H., & Sommer, D. (2003). Ursachen des Studienabbruchs:
Analyse 2002. Hochschulplanung, 163. Hannover: HIS GmbH.
ITT2772958 (secondary reference to ITT2772964): Heublein, U. (2003). Ursachen des Studienab- bruchs: Motive für Studienabbrecher. Leibzig: HIS GmbH.
ITT2762308: Hoff, J., & Demirtas, M. (2009). Frafald blandt etniske minoritetsstuderende på uni- versitetsuddannelserne i Danmark. København: Forlaget Politiske Studier.
¤ITT2770888: Hovdhaugen, E., & Aamodt, P. O. (2009). Learning environment: Relevant or not to students' decision to leave university? Quality in Higher Education, 15(2), 177-789.
¤ITT2770886 (secondary reference to ¤ITT2770888): Hovdhaugen, E. (2009). Transfer and dropout:
Different forms of student departure in Norway. Studies in Higher Education, 34(1), 1-17.
ITT2770887: Hovdhaugen, E. (2011). Do structured study programmes lead to lower rates of drop- out and student transfer from university? Irish Educational Studies, 30(2), 237-251.
¤ITT2762111: Johnes, G., & McNabb, R. (2004). Never Give Up the Good Times: Student Attrition in the UK. Oxford Bulletin of Economics and Statistics, 66(1), 23-47.
ITT2767942: Kinnunen, P., & Malmi, L. (2008). CS Minors in a CS1 Course. ICER '08 Proceedings of the Fourth international Workshop on Computing Education Research, September 6-7, 2008: Syd- ney, Australia, 79-90.
ITT2772971: Kolland, F. (2002). Studienabbruch: Zwischen Kontinuität und Krise. Eine empirische Untersuchung an Ôsterreichs Universitäten. Braumüller.
ITT2773010: Larsen, U. (2000). Frafald og studiemiljø. Århus: Studenterrådet ved Aarhus Universi- tet.
ITT2770663: Lassibille, G., & Gómez, L. N. (2008). Why do higher education students drop out?
Evidence from Spain. Education Economics, 16(1), 89-105.
¤ITT2763715 (secondary reference to ITT2770663): Lassibille, G., & Gómez, L. N. (2009). Tracking Students' Progress through the Spanish University School Sector. Higher Education, 58, 821–839.
ITT2759144: Loyens, S. M. M., Rikers, R. M. J. P., & Schmidt, H. G. (2007). The impact of students' conceptions of constructivist assumptions on academic achievement and drop-out. Studies in Higher Education, 32(5), 581-602.
ITT2770677: May, S., & Bousted, M. (2004). Investigation of student retention through an analysis of the first-year experience of students at Kingston University. Widening participation and lifelong learning, 6(2), 42-48.
ITT2759206: Nelson, A. (2008). Looking into one’s own practice: A Swedish study on gender in ed- ucational sciences. Journal of Further and Higher Education, 32(2), 139–149.
ITT2770687: O'Neill, L. D., Hartvigsen, J., Wallstedt, B., Korsholm, L., & Eika, B. (2011). Medical school dropout - testing at admission versus selection by highest grades as predictors. Medical Education, 45, 1111-1120.
ITT2770688: O'Neill, L. D., Wallstedt, B., Eika, B., & Hartvigsen, J. (2011). Factors associated with dropout in medical education: a literature review. Medical Education, 45, 440-454.
ITT2762175: Oosterbeek, H., & van Ewijk, R. (2010). Gender Peer Effects in University: Evidence from a Randomized Experiment. Tinbergen Institute Discussion Paper. TI 2010-113/3.
ITT2762178: Ortiz, E. A., & Dehon, C. (2011). The Roads to Success: Analyzing Dropout and Degree Completion at University. Brussels: ECARES Working paper.
ITT2773000: Pohlenz, P., Seyfried, M., & Tinsner, K. (2007). Studienabbruch: Ursachen, Probleme, Begründungen. VDM Verlag Dr. Müller.
ITT2773001 (secondary reference to ITT2773000): Pohlenz, P., & Tinsner, K. (2004). Bes-
timmungsgrößen des Studienabbruchs: eine empirische Untersuchung zu Ursachen und Verant- wortlichkeiten. Potsdamer Beiträge zur Lehrevaluation|1.
ITT2770695: Qualter, P., Whiteley, H., Morleya, A., & Dudiak, H. (2009). The role of Emotional In- telligence in the decision to persist with academic studies in HE. Research in Post-Compulsory Edu- cation, 14 (3), 219–231.
ITT2771760: Smith, J., & Naylor, R. (2001b). Dropping out of university: A statistical analysis of the probability of withdrawal for UK university students. Journal of the Royal Statistical Society: Series A, 164(2), 389-405.
ITT2786263: Smith, J., & Naylor, R. (2001a). Determinants of degree performance in UK universi- ties: a statistical analysis of the 1993 student cohort. Oxford Bulletin of Economics and Statistics, 63(1), 29-60.
ITT2762212: Soo, K. T. (2009). Estimating the Production Function of University Students. Lancas- ter University Management School Working Paper, 2009/018.
ITT2763560: Suhre, C. J. M., Jansen, E. W. A., & Harskamp, E. G. (2007). Impact of degree program satisfaction on the persistence of college students. Higher Education, 54, 207–226.
ITT2770722: Urlings-Strop, L. C., Stijnen, T., Themmen, A. P. N., & Splinter, T. A. W. (2009). Selec- tion of medical students: a controlled experiment. Medical Education, 43, 175-183.
ITT2770600: Van Bragt, C. A. C., Bakx, A. W. E. A, Bergen, T. C. M., & Croon, M. A. (2011b). Why students withdraw or continue their educational careers: A closer look at differences in study ap- proaches and personal reasons. Journal of Vocational Education & Training, 63(2), 217-233.
ITT2763933: Van Bragt, C. A. C., Bakx, A. W. E. A., Bergen, T. C. M., & Croon, M. A. (2011a). Looking for students' personal characteristics predicting study outcome. Higher Education, 61(1), 59-75.
ITT2762237: Vignoles, A. F., & Powdthavee, N. (2009). The Socioeconomic Gap in University Drop- outs. The B.E. Journal of Economic Analysis & Policy, 9(1), 1-15.
ITT2771298: Zwick, M. (2009). Stuttgarter Abbrecherstudie 2009. Zufriedenheit mit dem Studium und Abbruchneigung bei Studierenden des BA-Studiengangs Sozialwissenschaften an der Universi- tät Stuttgart. Stuttgarter Beiträge zur Risiko- und Nachhaltigkeitsforschung, 14, 1-55.
10 Abstracts for the studies available for the synthesis
Listed below are all references including abstract to the 44 studies available for the synthesis, that is, studies which in the research mapping were assigned an overall weight of evidence of medium or high.
Albrecht, A., & Nordmeier, V. (2001). Ursachen des Studienabbruchs in Physik. Eine explorative Studie. Die hochschule, 2.
ITT 2772931
This article describes a study exploring causes of withdrawal of first-year university students within the subject 'Mono-Bachelor Physik' at two universities in Germany. Also, the aim is to look at the motives given for withdrawal as well as the future career plans of the withdrawn students. The study takes its point of departure in a theoretically developed model of study success. Data are obtained from three questionnaires given to the still active students as well as (with additional relevant questions) to withdrawn students. The researchers find the following factors to signifi- cantly influence the decision to withdraw: University entry qualifications operationalised as HZB- Note is the next most important predictor of study success. Not having received an approval for ones desired study is negatively related to study success (positively related to withdrawal), where- as subject interest, information about study demands, guidance and support (which is the most important predictor of study success) as well as difficulties with having to unite study and family are all positively related to study success. Assessed Weight of Evidence: Medium.
Araque, F., Róldan, C., & Salguero, A. (2009). Factors influencing university drop out rates. Com- puters & Education, 53, 563–574.
ITT 2758729
This paper develops personalised models for different university degrees to obtain the risk of each student abandoning his/her degree, and analyses the profile for undergraduates that abandon their degree. In this study three faculties located in Granada, South of Spain, were involved. In Software Engineering three university degrees with 10,844 students, in Humanities 19 university degrees with 39,241 students and in Economic Sciences five university degrees with 25,745 stu- dents were considered. Data, corresponding to the period 1992 onwards, are used to obtain a model of logistic regression for each faculty which represents them satisfactorily. These models and the framework data show that certain variables appear repeatedly in the explanation of the dropout in all of the faculties. Among these are start age, the father’s and mother’s studies, aca- demic performance, success, average mark in the degree and the access form and in some cases also, the number of rounds needed to pass. Students with weak educational strategies and with- out persistence to achieve their aims in life have low academic performance and low success rates