High stakes in the assessment arms race: a mixed-methods analysis of reducing assessment in an undergraduate psychology programme

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Pye, R. ORCID: https://orcid.org/0000-0002-1395-7763, Gnagi, L. K., Chuah, A. B. Q. and Chung, K. L. ORCID: https://orcid.org/0000-0003-0012-8752 (2025) High stakes in the assessment arms race: a mixed-methods analysis of reducing assessment in an undergraduate psychology programme. Psychology, Learning & Teaching, 24 (2). pp. 195-213. ISSN 1475-7257 doi: 10.1177/14757257251336295

Abstract/Summary

Reducing assessment load has been identified as one practical way to allow space within programmes and modules for students to develop deeper learning practices and to increase student satisfaction. Yet despite the obvious benefits, both staff and students report preferring to maintain a high assessment load as a way to ensure student attention (staff), or to manage risk (students). This mixed-methods study looked at the reduction of the number of assessments across final year optional modules in the international branch campus of a UK university psychology programme on module grades and student perceptions. We found that module grades did not increase following reduction. Students reported anxiety about single-assessment module regimes, regardless of their experience of assessment reduction. Students overwhelmingly preferred two assessments per module, interestingly on the grounds of fairness from a diverse assessment portfolio. We suggest that a simple reduction in the number of assessments isn’t itself sufficient to meet the broad aims of slow scholarship, but that programme teams could consider how better as well as fewer assessments and the perceptions of workload might be more important to tackle.

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Item Type Article
URI https://centaur.reading.ac.uk/id/eprint/122570
Identification Number/DOI 10.1177/14757257251336295
Refereed Yes
Divisions Life Sciences > School of Psychology and Clinical Language Sciences > Department of Psychology
Uncontrolled Keywords assessment load; anxiety and risk; mixed-methods; fairness in assessment; workload
Publisher Sage
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