For teachers, explainability (Correct-AI) and both agency and explainability (Answer-AI) influenced intention to use indirectly through global utility and perceived usefulness¶

Claim · All claims
Evidence · 1 study (2 entries) · causal r2 · q3
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? In the teacher Correct-AI model, explainability positively impacted global utility (β = 0.7161, p = 0.0057) and perceived usefulness (β = 0.6634, p = 0.0059), with significant indirect effects on ITU through GU (Effect = 0.2606) and perceived usefulness (Effect = 0.4116). → Alexander John Karran 2025 q3 i? In the teacher Answer-AI model, agency negatively (β = -0.5969, p = 0.0271) and explainability positively (β = 0.8700, p = 0.0008) impacted global utility, with significant indirect effects on ITU through GU (agency Effect = -0.3337; explainability Effect = 0.5194). → Alexander John Karran 2025 (2)

Evidence¶

Alexander John Karran 2025¶

Alexander John Karran, Patrick Charland, Joé Trempe-Martineau, Ana Ortiz de Guinea Lopez de Arana, Anne-Marie Lesage, Sylvain Sénécal & Pierre-Majorique Léger. (2025). Multi-stakeholder perspective on responsible artificial intelligence and acceptability in education. npj Science of Learning 10:44. https://doi.org/10.1038/s41539-025-00333-2

q3 · i? · causal · r2

Mediation analysis of teacher responses to Correct-AI. The direct effect of explainability on ITU was not statistically significant (β = -0.0215, p = 0.9366); both indirect effects through GU and perceived usefulness were statistically significant, indicating partial mediation.

"explainability had a significant positive impact on global utility (β = 0.7161, p = 0.0057), indicating that higher levels of explainability were associated with higher levels of perceived personal and overall benefit"

Alexander John Karran 2025 (2)¶

Alexander John Karran, Patrick Charland, Joé Trempe-Martineau, Ana Ortiz de Guinea Lopez de Arana, Anne-Marie Lesage, Sylvain Sénécal & Pierre-Majorique Léger. (2025). Multi-stakeholder perspective on responsible artificial intelligence and acceptability in education. npj Science of Learning 10:44. https://doi.org/10.1038/s41539-025-00333-2

q3 · i? · causal · r2

Mediation analysis of teacher responses to the Answer-AI chatbot vignette. Direct effects of agency (β = -0.2283, p = 0.2847) and explainability (β = -0.1479, p = 0.5028) on ITU were not statistically significant; both indirect effects through GU were statistically significant.

"both agency and explainability had a significant impact on perceived GU negatively ( β =-0.5969, p = 0.0271) in the case of agency and positively ( β = 0.8700, p = 0.0008) in the case of explainability"

Discussion¶

Related Claims¶

• For students, AI agency reduced intention to use Correct-AI indirectly through lower perceived global utility and justice, with no direct effect — related
• For students, privacy (Answer-AI) and explainability (Emotion-AI) each positively influenced intention to use indirectly through perceived global utility — related
• Higher AI agency is associated with lower intention to use AI in education, while transparency, explainability, and privacy do not directly predict intention to use — related