Trust-utility gap in introductory physics education: Students' adoption, domain-specific skepticism, and preferences for AI integration

Synthesis: Fouad & Bentley (2026) survey 81 introductory physics students and find a striking 50-percentage-point trust-utility gap: 91% use AI for coursework but only 41% trust AI physics explanations — evidence of domain-calibrated skepticism, not uncritical adoption. Students spontaneously identified where AI fails in physics (visual-spatial reasoning, circuits, abstract reasoning), aligning with known benchmarks. 65% prefer optional over mandatory AI integration.

A mixed-methods survey of 81 introductory physics undergraduates reveals a 50-point trust-utility gap: 91% [95% CI: 83%–96%] use AI for physics coursework, but only 41% [95% CI: 30%–52%] trust AI-generated physics explanations. Thematic analysis identified eight themes; the most distinctive finding was that 40% of qualitative respondents spontaneously articulated where AI fails — visual-spatial reasoning, circuit analysis, and abstract physical reasoning — aligning with known benchmarks. Students show domain-calibrated skepticism rather than uncritical adoption, and 65% prefer optional AI integration.

91% use AI for physics, only 41% trust it — 50-point trust-utility gap

Students show domain-specific skepticism, not naive acceptance

40% spontaneously identified AI failure modes: visual-spatial reasoning, circuits, abstract physics

Student trust calibration tracks AI competence boundaries (consistent with Kortemeyer benchmarks)

65% prefer optional over mandatory AI integration

Verification gap identified: self-reported vs actual verification behavior

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Citation

Fouad, E., & Bentley, I. (2026). Trust-utility gap in introductory physics education: Students' adoption, domain-specific skepticism, and preferences for AI integration.