Human-AI Cognition & Performance / Mathematical Learning
SUB-0057Progress Measurement
Definition
Progress Measurement 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
Progress Measurement 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 can mathematical growth be measured across different curricula, supports and starting points?
Hypotheses
Support-adjusted mastery and reasoning growth will predict future success better than raw item scores.
Proposed methods
diagnostic assessment; item-level telemetry; worked-example experiments; adaptive-practice trials; interviews; longitudinal progression analysis; 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
students; teachers; families; numeracy specialists; schools; curriculum authorities; employers; edtech providers; assessment authorities; learning analytics teams