Supplementary file 1_Independent judgment before viewing generative AI recommendations reduces susceptibility to misleading advice: a randomized scenario-based experiment with preservice teachers.docx

After data-quality exclusions, 218 participants remained in the main analysis. Participant-clustered logistic generalized estimating equations tested sequence, recommendation quality, and their interaction.</p>Results<p>Under misleading recommendations, Group A had higher expert-keyed joint accuracy than Group B, OR = 1.912, 95% CI [1.413, 2.589], p < 0.001. The estimate remained significant among all 160 randomized A/B participants with available outcomes, OR = 1.814, 95% CI [1.345, 2.448], p < 0.001, and was similar after version adjustment.

The difference appeared in both final plan accuracy and final rationale accuracy. Group A was also less likely to reproduce the misleading recommendation completely, OR = 0.403, 95% CI [0.296, 0.549], p < 0.001. Under expert-keyed recommendations, the between-group contrast was not statistically significant, OR = 0.821, 95% CI [0.598, 1.128], p = 0.225.</p>Discussion<p>Recording an independent judgment before viewing AI was associated with lower susceptibility to misleading recommendations in the selected controlled scenarios.

The result supports further evaluation of independent-first workflows in teacher education, but it does not isolate a single cognitive mechanism or establish transfer to authentic classroom decision-making. These findings extend research on cognitive-forcing designs to contextualized pedagogical judgments that require both instructional action selection and evidence-based justification.</p>