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Human-AI Cognition & Performance / Mathematical Learning

SUB-0056

Mathematics Confidence

Definition

Mathematics Confidence 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

Mathematics Confidence 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

Which experiences reduce mathematics anxiety and increase willingness to attempt difficult problems?

Hypotheses

Private low-stakes practice with attribution to strategy will improve confidence more than gamified rewards.

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; mathematics educators; numeracy intervention specialists