Human-AI Cognition & Performance / Mathematical Learning
SUB-0056Mathematics 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