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Student Diversity and E-Exam Acceptance in Higher Education

Authors :
Froehlich, Laura
Sassenberg, Kai
Jonkmann, Kathrin
Scheiter, Katharina
Stürmer, Stefan
Source :
Journal of Computer Assisted Learning. Aug 2023 39(4):1196-1210.
Publication Year :
2023

Abstract

Background: The use of e-exams in higher education is increasing. However, the role of student diversity in the acceptance of e-exams is an under-researched topic. In the current study, we considered student diversity in terms of three sociodemographic characteristics (age, gender, and second language) and three dispositional student characteristics (computer anxiety, test anxiety, and technology openness). Objectives: The main objective of this study was to investigate the relationship between student diversity and acceptance of e-exams. Methods: Our research combined cross-sectional analyses (N = 1639) with data from a natural experiment on the introduction of e-exams versus the established paper-pencil exams (N = 626) and used both self-report and institutional data. Sociodemographic and dispositional characteristics were indirectly related to pre-exam acceptance via expectancy variables from the Technology Acceptance Model framework. Results and Conclusions: Comparisons of post-exam acceptance showed that practical experience with the e-exam led to a significant increase in e-exam acceptance, and that students with low openness toward technology particularly benefited from this effect. Students' exam performance (i.e., grades) was unrelated to the exam format or their pre-exam acceptance of the e-exam format, and this was true across students' sociodemographic and dispositional characteristics. Takeaway: Student diversity plays a role in e-exam acceptance, but its influence is mitigated by first-hand experience with e-exams. The practical implications for higher education institutions aiming to implement e-exams are discussed.

Details

Language :
English
ISSN :
0266-4909 and 1365-2729
Volume :
39
Issue :
4
Database :
ERIC
Journal :
Journal of Computer Assisted Learning
Notes :
https://osf.io/kxfpy
Publication Type :
Academic Journal
Accession number :
EJ1384343
Document Type :
Journal Articles<br />Reports - Research
Full Text :
https://doi.org/10.1111/jcal.12794