Same crisis, different effect? Dropout intention at the beginning of the COVID-19 pandemic, among medical, social science, and computer science students

Abstract

Abstract Background During the first COVID-19 lockdown, universities were forced to implement digital teaching within a very short timeframe. This transition was more difficult for programs of study characterised by a less flexible teaching structure and a high proportion of practical units (e.g., medicine). The present study investigated how pandemic-related changes in university education affected students’ dropout intention, comparing medical and non-medical students. Methods Data from two German cross-sectional studies conducted in 2016 and 2020 were analyzed with a focus on medical, social science, and computer science students. OLS regression models were used to predict dropout intention before the COVID-19 pandemic (n = 243) and during the first lockdown (n = 846). An Oaxaca-Blinder decomposition was calculated to explain subject-related differences in dropout intention. Results Dropout intention increased in all three student groups from 2016 to 2020, with medical students displaying the most moderate increase. During the first lockdown, greater time flexibility due to the digital teaching and greater ability to follow course content were associated with lower dropout intention. Contrary to social science and computer science students, medical students showed no association between dropout intention and overburden, but a high association between dropout intention and academic and social integration with peers. Conclusions Some degree of digital or hybrid teaching should be maintained, as the increased time flexibility it affords students is associated with lower dropout intention. However, on-campus teaching remains important for ensuring social exchange between students and conveying practical skills, which cannot be fully taught digitally.