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Artificial intelligence, cognitive offloading and implications for education
Open accessAbstract
This report investigates a profound new challenge driven by rapidly expanding use of artificial intelligence (AI) in schooling: the risk that students will outsource too much of the cognitive work that is crucial to establishing the knowledge, skill and ‘thinking infrastructure’ that enables both schooling success and lifelong capacity for ongoing learning and understanding. There is a growing body of evidence that using AI can short-circuit the cognitive effort required for sustainable, deep learning, with potentially long-term consequences. This cognitive offloading from human to AI is especially risky for school students (‘novice’ learners who are building foundational knowledge and skills) when they turn to AI as a tempting substitute, not an amplifier, increase their dependency on the tool and lose access to deeper learning and critical thinking capabilities. It also introduces extra equity risks for disadvantaged students. The report reviews the cognitive science behind this concerning shift and the growing evidence of its impact. It also outlines how these harmful effects can be counteracted through specific teaching and learning strategies and effective design of AI education technology, anchored on bolstering the central role of teachers. It includes specific recommendations for policy and teaching and learning strategies.
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Self-citationAI as a cognitive partner in learning: Emerging epistemic practices of reflective thought
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Dalsgaard, C., & Prilop, C. N. (2026) · Scandinavian Journal of Educational Research · doi:10.1080/00313831.2026.2733215
Schäffer, B., Lieder, F. R., & Krämer, F. (2026) · Springer eBooks · doi:10.1007/978-3-658-53148-5_10
Metadata
- Authors
- Lodge, J. M., & Loble, L.
- Venue
- University of Technology Sydney
- Publisher
- University of Technology Sydney
- Published
- 2026
- OpenAlex
- W7133520779
- Cited by
- 10
- References
- 0
- Citations by year
- 2026: 10
- Type
- report
- Language
- en
- Open access
- green
- doi.org
- Locations
- UTS Figshare
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- artificial intelligence in education, cognitive offloading, deep learning, critical thinking, novice learners, educational equity, disadvantaged students, teacher role, teaching and learning strategies, lifelong learning
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