Harnessing Artificial Intelligence in universities

This research examines the complex relationships between artificial intelligence learning motivation (AILM), intention (AILI), efficacy (AILE), and student creativity (SC) among Saudi Arabian undergraduate and graduate students. A quantitative approach was employed, gathering data from bilingual questionnaires administered to 466 students across five Saudi universities, utilizing validated scales for AILM (intrinsic/extrinsic), AILI, AILE, and SC. Partial least squares structural equation modeling (PLS-SEM) was utilized to access direct and indirect effects. The analysis established the nine hypotheses, signifying that AILM significantly influences AILI and AILE, thus, enhances SC. AILE and AILI could act as mediators between AILM and SC, whereas the serial mediation path (AILM→AILI→AILE→SC) represents the highest mediator. The research implies the importance for Saudi Arabia's Vision 2030-compliant education reforms that promote both intrinsic and extrinsic motivation (ILM and ELM), intention reciprocated into learning behavior, and the development of AILE to enhance SC.