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Evidence record 5799 · automatically gathered

Uncertainty-aware Generative Learning Path Recommendation with Cognition-Adaptive Diffusion

Learning Path Recommendation (LPR) is critical for personalized education, yet current methods often fail to account for historical interaction uncertainty (e.g., lucky guesses or accidental slips) and lack adaptability to diverse learning goals. We propose U-GLAD (Uncertainty-aware Generative Learning Path Recommendation with Cognition-Adaptive Diffusion). To address representation bias, the framework models cognitive states as probability distributions, capturing the learner's underlying true

Record details

Published: 16 April 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Children & education
Retrieved: 14 July 2026

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How to cite this record

ethics.ai (16 April 2026), “Uncertainty-aware Generative Learning Path Recommendation with Cognition-Adaptive Diffusion,” evidence record 5799, https://ethics.ai/record/5799 (originally published by arXiv).

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