Supplementary file 1_Designing for AI literacy: psychological mechanisms and self-determination.pdf

In the structural model, TBI positively predicted autonomy, competence, relatedness, and AI literacy performance. OET positively predicted autonomy, relatedness, and performance but did not significantly predict competence. Competence was the strongest psychological predictor of performance, followed by autonomy, whereas relatedness had no independent effect.

Bootstrap analysis showed that instructional approach operated indirectly through autonomy and competence, while task type operated primarily through autonomy. The single factorial interaction term did not retain a significant direct effect after the psychological needs were included. fsQCA further identified multiple sufficient configurations leading to high AI literacy performance.</p>Discussion<p>These findings demonstrate that instructional design affects AI literacy through differentiated motivational pathways rather than through a uniform activation of all three psychological needs.

Within this single-institution, short-duration experiment, the findings should be interpreted cautiously and require longer, multi-site replication.</p>