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Making Evidence Actionable in Adaptive Learning Closing the Diagnostic Pedagogical Loop

Evidence supporting an instructor-governed feedback loop that converts concept-level assessment evidence into vetted microinterventions is presented, and a tractable and auditable controller that closes the diagnostic pedagogical loop and enables equitable, load-aware personalization at the classroom scale is presented.
arXiv (opens in a new tab)

Enhancing performance factor analysis through skill profile and item similarity integration via an attention mechanism of artificial intelligence

A modified version of Performance Factor Analysis is proposed, which assesses student abilities by analyzing past responses and comparing them with peer performance on the same items, using parameters from a sigmoid function that leverages attention mechanisms to capture item order-based similarity and decay principles, providing a nuanced view of student skill profiles.
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Making Evidence Actionable in Adaptive Learning

This study presents evidence supporting an instructor-governed feedback loop that converts concept-level assessment evidence into vetted micro-interventions, and formalizes intervention assignment as a binary integer program with constraints for coverage, time, difficulty windows informed by ability estimates, prerequisites encoded by a concept matrix, and anti-redundancy enforced through diversity.
arXiv (opens in a new tab)
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