Yang, H.
ORCID: https://orcid.org/0000-0001-9940-8273
(2026)
Advancements in artificial intelligence and the reframing of student assessment in geography education.
Journal of Geography in Higher Education.
ISSN 1466-1845
doi: 10.1080/03098265.2026.2628342
Abstract/Summary
The increasing presence of large language models (LLMs) like ChatGPT in higher education presents both opportunities and challenges for geography assessment. While these tools support learning, they also raise concerns about plagiarism and the authenticity of student work. This study investigates students’ use of ChatGPT for academic tasks and their perspectives on authentic assessment methods. Our survey revealed that 80% of students used ChatGPT, primarily for brainstorming (63%). To mitigate potential negative impacts, students favoured project-based assessments (70%) and fieldwork or internships (70%), citing benefits such as fostering creativity (70%) and learning process and skill development (67%). Student interviews revealed themes of academic support, integrity concerns, authentic assessment preference, and responsible AI integration in education. In response, we implemented a project-based learning (PBL) approach in the physical geography teaching, incorporating environmental data collection, analysis, and reporting. This was complemented by oral presentations and peer assessments to enhance assessment. The transition towards authentic assessment, integrating real-world applications, aims to cultivate deeper learning, originality, and self-reflection. Our findings highlight the importance of reassessing traditional evaluation methods in the context of AI advancements, ensuring both academic integrity and meaningful learning experiences in geography education.
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| Item Type | Article |
| URI | https://centaur.reading.ac.uk/id/eprint/128519 |
| Identification Number/DOI | 10.1080/03098265.2026.2628342 |
| Refereed | Yes |
| Divisions | Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science |
| Publisher | Taylor & Francis |
| Download/View statistics | View download statistics for this item |
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