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Student diversity and e‐exam acceptance in higher education.

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Title: 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. Aug2023, Vol. 39 Issue 4, p1196-1210. 15p.
Subjects: Statistics, Analysis of variance, Confidence intervals, Computer assisted testing (Education), Age distribution, Cross-sectional method, Self-evaluation, Time, Cultural pluralism, Health outcome assessment, Sex distribution, Pre-tests & post-tests, Academic achievement, Educational technology, Questionnaires, Factor analysis, Descriptive statistics, Student attitudes, Psychological adaptation, Sociodemographic factors, Anxiety, Data analysis software
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. Lay Description: What is already known about this topic: The use of e‐exams in higher education is increasingThe role of student diversity for e‐exam acceptance is unclearTechnology acceptance is predicted by expectancies towards new system What this paper adds: We investigated students' sociodemographic and dispositional diversityDiversity predicted e‐exam acceptance via the expectanciesIn a natural experiment, first‐hand experience increased e‐exam acceptanceNo difference between performance in e‐exams and paper‐pencil‐exams found Implications of the study findings for practitioners: Higher education institutions implementing e‐exams should consider diversitySupport for older students and students with low technology openness neededNo student groups systematically disadvantaged by e‐exam implementationPractice rooms can increase experience with new system before exam [ABSTRACT FROM AUTHOR]
Copyright of Journal of Computer Assisted Learning is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Student diversity and e‐exam acceptance in higher education.
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  Data: <searchLink fieldCode="AR" term="%22Froehlich%2C+Laura%22">Froehlich, Laura</searchLink><br /><searchLink fieldCode="AR" term="%22Sassenberg%2C+Kai%22">Sassenberg, Kai</searchLink><br /><searchLink fieldCode="AR" term="%22Jonkmann%2C+Kathrin%22">Jonkmann, Kathrin</searchLink><br /><searchLink fieldCode="AR" term="%22Scheiter%2C+Katharina%22">Scheiter, Katharina</searchLink><br /><searchLink fieldCode="AR" term="%22Stürmer%2C+Stefan%22">Stürmer, Stefan</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Computer+Assisted+Learning%22">Journal of Computer Assisted Learning</searchLink>. Aug2023, Vol. 39 Issue 4, p1196-1210. 15p.
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  Data: 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. Lay Description: What is already known about this topic: The use of e‐exams in higher education is increasingThe role of student diversity for e‐exam acceptance is unclearTechnology acceptance is predicted by expectancies towards new system What this paper adds: We investigated students' sociodemographic and dispositional diversityDiversity predicted e‐exam acceptance via the expectanciesIn a natural experiment, first‐hand experience increased e‐exam acceptanceNo difference between performance in e‐exams and paper‐pencil‐exams found Implications of the study findings for practitioners: Higher education institutions implementing e‐exams should consider diversitySupport for older students and students with low technology openness neededNo student groups systematically disadvantaged by e‐exam implementationPractice rooms can increase experience with new system before exam [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Computer Assisted Learning is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1111/jcal.12794
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      – Code: eng
        Text: English
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        PageCount: 15
        StartPage: 1196
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      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Analysis of variance
        Type: general
      – SubjectFull: Confidence intervals
        Type: general
      – SubjectFull: Computer assisted testing (Education)
        Type: general
      – SubjectFull: Age distribution
        Type: general
      – SubjectFull: Cross-sectional method
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      – SubjectFull: Self-evaluation
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      – SubjectFull: Health outcome assessment
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      – SubjectFull: Data analysis software
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              Text: Aug2023
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