AI, Lesson Planning, and Avoiding Geographical Mediocrity
Geography teachers increasingly rely on generative AI for lesson planning, yet outputs frequently exhibit geographical mediocrity: lessons appearing adequate but lacking the spatial thinking and place-based analysis of quality geography education. This risk is amplified for out-of-field teachers lacking disciplinary expertise to recognise AI's shortcomings. Applying the AI-Locus of Control (AI-LOC) framework, we distinguish teachers who surrender pedagogical authority to AI from those retaining agency through disciplinary scaffolding and iterative judgement. A collaborative autoethnographic case study documents one academic's transformation from external to internal AI-LOC. We propose four implementation pathways, contributing an agency-based alternative to competency-based approaches to AI integration.
Authors
- Jodie Torrington (ORCID: https://orcid.org/0000-0003-2754-0691)
- Brian Ballsun-Stanton (ORCID: https://orcid.org/0000-0003-4932-7912)
- Susan Caldis (ORCID: https://orcid.org/0000-0002-6659-8629)
Institutions
- Macquarie University (AU)
Publication Details
- Journal
- EdArXiv (OSF Preprints)
- Published
- 2026-11-08
- DOI
- https://doi.org/10.35542/osf.io/wktcr
- Primary Topic
- Geography Education and Pedagogy
- Type
- preprint