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Eight validity criteria for AI systems as cognitive models of learning

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The review's central contribution is an evaluative framework of eight criteria that an AI system must satisfy before its cognitive-model status is granted rather than assumed: theoretical grounding, construct validity, mechanistic transparency, alignment with human learning trajectories, error-signature matching, causal-intervention tests, ecological validity, and instructional usefulness. The framework shifts the question from whether AI can model cognition to when it should be allowed to count as one, treating the criteria as "a structured set of validity criteria that together determine when an AI system should be allowed to count as a cognitive model of learning".

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  • Eight validity criteria determine when an AI system should count as a cognitive model of learning: The review's central contribution is an evaluative framework of eight criteria that an AI system must satisfy before its cognitive-model status is granted rather than assumed: theoretical grounding, construct validity, mechanistic transparency, alignment with human learning trajectories, error-signature matching, causal-intervention tests, ecological validity, and instructional usefulness. The framework shifts the question from whether AI can model cognition to when it should be allowed to count as one, treating the criteria as "a structured set of validity criteria that together determine when an AI system should be allowed to count as a cognitive model of learning". (Peng Wang et al. (2026))

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  • Peng Wang, Olga Viberg, Effie Lai-Chong Law, Samuel Greiff. (2026). When Can AI Models Explain Learning? Validity Criteria for AI as Cognitive Models in Education. Educational Psychology Review. https://doi.org/10.1007/s10648-026-10202-y
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type research-method
id eight-validity-criteria-for-ai-systems-as-cognitive-models-of-learning
title Eight validity criteria for AI systems as cognitive models of learning
description The review's central contribution is an evaluative framework of eight criteria that an AI system must satisfy before its cognitive-model status is granted rather than assumed: theoretical grounding, construct validity, mechanistic transparency, alignment with human learning trajectories, error-signa
status review
generated by process:settle-candidates on 2026-10-22
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