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.

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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
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preprint

AI, Lesson Planning, and Avoiding Geographical Mediocrity

Jodie Torrington, Brian Ballsun-Stanton, Susan Caldis
1 links
EdArXiv (OSF Preprints)
Geography Education and Pedagogy
preprint

AI, Lesson Planning, and Avoiding Geographical Mediocrity

Jodie Torrington, Brian Ballsun-Stanton, Susan Caldis
preprint en

Abstract

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.

EdArXiv (OSF Preprints)
Macquarie University (AU)
Quality education
Geography Education and Pedagogy
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