TY - JOUR
T1 - Dropping out of master’s degrees
T2 - objective predictors and subjective reasons
AU - Rotem, Nir
AU - Yair, Gad
AU - Shustak, Elad
N1 - Publisher Copyright:
© 2020 HERDSA.
PY - 2021
Y1 - 2021
N2 - While student attrition constitutes a major institutional concern at the undergraduate level, this topic is overlooked at the master’s level. Dropout rates have been documented, but no solid predictive models are to be found. Likewise, little is known about students’ decision to terminate their studies. With growing enrolment numbers in postgraduate programmes, this blind spot should be addressed. The multi-method research presented here, combining student administrative data from The Hebrew University of Jerusalem with a survey for students who dropped out of the institution, brings the research on this topic a step forward. The study found that dropout rates of master’s students are 12%. To identify possible predictors of these dropouts, we employed a four-step hierarchical logistic regression model. Academic performance variables predict dropping out far better than background variables, though much of the variation remains unaccounted for. An exploratory factor analysis of dropout survey items identified five factors linked to departure: work obligations, institutional difficulties, family and personal obligations, degree’s economic feasibility, and harassment. These subjective reasons for dropping out should be major targets for dropout prevention efforts.
AB - While student attrition constitutes a major institutional concern at the undergraduate level, this topic is overlooked at the master’s level. Dropout rates have been documented, but no solid predictive models are to be found. Likewise, little is known about students’ decision to terminate their studies. With growing enrolment numbers in postgraduate programmes, this blind spot should be addressed. The multi-method research presented here, combining student administrative data from The Hebrew University of Jerusalem with a survey for students who dropped out of the institution, brings the research on this topic a step forward. The study found that dropout rates of master’s students are 12%. To identify possible predictors of these dropouts, we employed a four-step hierarchical logistic regression model. Academic performance variables predict dropping out far better than background variables, though much of the variation remains unaccounted for. An exploratory factor analysis of dropout survey items identified five factors linked to departure: work obligations, institutional difficulties, family and personal obligations, degree’s economic feasibility, and harassment. These subjective reasons for dropping out should be major targets for dropout prevention efforts.
KW - Attrition
KW - dropout
KW - institutional policies and practices
KW - master’s students
KW - postgraduate
UR - http://www.scopus.com/inward/record.url?scp=85088969851&partnerID=8YFLogxK
U2 - 10.1080/07294360.2020.1799951
DO - 10.1080/07294360.2020.1799951
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
AN - SCOPUS:85088969851
SN - 0729-4360
VL - 40
SP - 1070
EP - 1084
JO - Higher Education Research and Development
JF - Higher Education Research and Development
IS - 5
ER -