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Academic performance in AI Era: salient factors in higher education.

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Title: Academic performance in AI Era: salient factors in higher education.
Authors: Hendra, Robi1, Rasyono, Rasyono2, Habibi, Akhmad1,3 akhmad.habibi@unja.ac.id, Yaqin, Lalu Nurul4, Alahmari, Sarah A.5, Alharmali, Turki Mesfer6, Wijaya, Hansein Arif1
Source: Journal of E-Learning & Knowledge Society. Aug2025, Vol. 21 Issue 2, p18-30. 13p.
Subject Terms: *Student engagement, *Higher education, *Academic achievement, *Data analysis, *Artificial intelligence, *Instructional systems, Structural equation modeling, Sampling methods
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. [ABSTRACT FROM AUTHOR]
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Database: Education Research Complete
Description
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. [ABSTRACT FROM AUTHOR]
ISSN:18266223
DOI:10.20368/1971-8829/1136015