Teachers report domain-driven explanations are more influential for building trust than data-driven explanations¶

Claim · All claims
Evidence · 1 study · causal r1 · q1
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q1 i? All seven think-aloud teachers who reported XAI increased understandability found domain-driven explanations more influential in building trust than data-driven ones. → Yael Feldman-Maggor 2025

Evidence¶

Yael Feldman-Maggor 2025¶

Yael Feldman-Maggor, Mutlu Cukurova, Carmel Kent, Giora Alexandron. (2025). The Impact of Explainable AI on Teachers' Trust and Acceptance of AI EdTech Recommendations: The Power of Domain-specific Explanations. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-025-00486-6

q1 · i? · causal · r1

Qualitative think-aloud analysis (11 teachers; insights reported only when observed among at least three). One teacher commented that "Semantic information about the difficulties and strengths helped me trust more"; another shifted from doubt to conviction after domain-driven explanations.

"However, all seven teachers found that domain-driven explanations were more influential in building their trust in the tool. This suggests that some teachers prefer domain-driven explanations over data-driven ones in fostering trust."

Discussion¶

Related Claims¶

• Domain-driven explanations significantly increase teachers' understandability, trust, and acceptance compared to data-driven explanations — related
• Understandability alone is insufficient to establish trust for some teachers, who require real classroom experience — related
• Pedagogical considerations and workload reduction potential are additional factors influencing teachers' acceptance of AI-EdTech, beyond trust — related
• User acceptance of AI-driven decisions depends on explanation type, with sensitivity-analysis and certification explanations increasing acceptance — related