Thesis
Artificial intelligence (AI): how can we use artificial intelligence in secondary school geography?
- Abstract:
- This research and development project uncovers how artificial intelligence (AI) can be used by secondary school geography teachers. A critical review of the literature suggests a gap for empirical research on AI in the geography classroom. Whilst AI has much to offer geography teachers, there are important ethical dilemmas (Wilby and Esson, 2023). Contextualised in an institution with a whole-school focus on creativity, the literature on creativity is critically reviewed. This practitioner research employs a qualitative methodology. Interviews with geography teachers (n=4) are the main research instrument to uncover how (and why) teachers use AI, how AI enhances creativity and the barriers to usage before and after an intervention. The project is designed in collaboration with colleagues, with professional learning being central to the intervention which seeks to develop participants’ use of AI. The findings firstly suggest that AI is used to varying degrees and for varying purposes, in general with a greater degree and variety of use following the intervention. Second, AI is positioned to assist, but not replace, students and teachers in their pursuit of creativity in geography education. Third, operational and broader, ideological barriers restrict teachers’ AI usage. Before the intervention, these included a lack of training and concerns with reliance, with concerns over access, inaccurate information, misuse and student apprehension prevailing after the intervention. The project suggests that avenues for further research include cross-department or cross-institutional studies exploring creative teaching and learning with AI, together with investigations into the impact of AI use on teachers and students.
Actions
Access Document
- Files:
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(Preview, Dissemination version, pdf, 11.5MB, Terms of use)
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Authors
Contributors
+ Puttick, S
- Institution:
- University of Oxford
- Division:
- SSD
- Department:
- Education
- Role:
- Supervisor
- ORCID:
- 0000-0003-4939-8323
- DOI:
- Type of award:
- MSc taught course
- Level of award:
- Masters
- Awarding institution:
- University of Oxford
- Language:
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English
- Keywords:
- Subjects:
- Deposit date:
-
2026-01-30
- ARK identifier:
Terms of use
- Copyright holder:
- Darragh Woods
- Copyright date:
- 2024
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