Zhao, H. orcid.org/0000-0002-9502-4763 and Dang, T.N.Y. (2026) Transforming written assessment design to embrace AI: what needs to be changed to encourage higher-order critical thinking. Education and Information Technologies. ISSN: 1360-2357
Abstract
Uncritical use of generative AI (GenAI) responses is a major concern among educators as it can hinder knowledge development, creativity, critical thinking and academic misconduct. To mitigate these repercussions, current discussions predominantly focus on changing assessment methods or policing students’ use of GenAI, which greatly shapes students’ GenAI use, for better or for worse. Few studies have examined how different assessment designs impact the way students use GenAI for coursework and the quality of GenAI-assisted writing. This study uncovered the relationships between assessment design and critical thinking in students’ writing through analysing lecturer feedback on 51 postgraduate ChatGPT-assisted students’ assignments across fourteen modules and assessment information related to the assignments. Results revealed that word limits, genres, information about organisational structures, and cognitive domains required by assessments significantly determined students’ critical thinking performance in their disciplinary writing. Based on the results, we suggested (a) setting word limits based on task complexity rather than module credits, (b) designing integrated tasks with varied assessment methods to encourage critical thinking and knowledge development, (c) providing an appropriate amount of structural information to create space for critical thinking and (d) explicitly signalising cognitive domains required by assessments to address GenAI’s impact on writing. We further encourage educators to critically reflect on the existing assessment guidance and practices to design assessments that cultivate critical AI users in an AI-empowered world.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Assessment design; Critical thinking; Lecturer feedback; ChatGPT; AI |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Education, Social Sciences and Law (Leeds) > School of Education (Leeds) |
| Funding Information: | Funder Grant number British Council Not Known |
| Date Deposited: | 23 Jan 2026 14:38 |
| Last Modified: | 23 Jan 2026 14:38 |
| Status: | Published online |
| Publisher: | Springer Nature |
| Identification Number: | 10.1007/s10639-025-13870-5 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:236814 |
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