ArticleJournal of Intelligence2026
From Confidence to Commitment: Self-Perceived Competence and the Motivational Pathways to Intellectual Engagement with AI Learning Tools.
Article in Journal of Intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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7 authors.
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Abstract
Artificial intelligence (AI) tools are becoming part of how students think, not only what they use. Whether a learner engages with such a tool or delegates to it is a decision about how their own cognitive resources are deployed, which places that decision within the realm of study of human intelligence. Investment accounts of intellectual development hold that ability is built through motivated engagement with cognitively demanding material, yet technology acceptance frameworks emphasize utility judgments and underrepresent the motivational processes that drive such engagement. This study tests an extended Technology Acceptance Model in which self-efficacy shapes perceived usefulness through motivation and enjoyment. Survey data from 185 undergraduate School of Business students at a Saudi university who used generative AI tools during coursework were analyzed using partial least squares structural equation modeling. All nine hypotheses were supported. Self-efficacy strongly predicted both motivation and enjoyment, but motivation was the dominant mediating pathway to perceived usefulness (β = 0.295,
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