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Abstract
This research integrates teacher AI competence (TAC), student learning agility (SLA), and student engagement (SE), as factors affecting student academic performance (SAP). We employed a survey methodology in which the instrument’s validation was conducted through content and face validity, as well as a content validity index and measurement model in SmartPLS. A total of 380 lecturers from three universities participated as respondents in this survey study. Partial least squares structural equation modeling (PLS-SEM) procedures were employed for the primary data analysis of the study. The findings informed the validity and reliability of the model, highlighting the important roles of SLA and SA in relation to SAP. In addition, TAC was also correlated with SAP and SLA, while it has no relationship with SA.
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