Human-AI Cognition & Performance / Learning Science and Adaptive Education
SUB-0035Adaptive Difficulty
Definition
Adaptive Difficulty examines the mechanisms, conditions and outcomes through which this factor shapes human cognition, learning, collaboration or sustainable performance in AI-supported settings.
Why this matters
Adaptive Difficulty may materially affect human capability, independence, confidence, safety and productivity. Poorly designed assistance can create hidden costs even where short-term output appears to improve.
Research questions
How quickly and on what evidence should learning difficulty change?
Hypotheses
Small difficulty adjustments based on error type and response confidence will outperform large score-based jumps.
Proposed methods
randomised classroom pilots; mastery-learning analysis; item-response modelling; learning analytics; interviews; longitudinal follow-up; pre-registered analysis; active comparison; subgroup and accessibility analysis; delayed retention or longitudinal follow-up; adverse-effect capture; reproducibility testing; participant debrief
Stakeholders and beneficiaries
learners; teachers; schools; families; curriculum authorities; education departments; edtech providers; researchers; Adaptive Difficulty domain specialists; affected user advisory panel