Digital Leadership, Artificial Intelligence Readiness and Teaching Innovation as Determinants of Academic Performance in Islamic Higher Education

Nasiruddin; Nurhasanah

Authors

Nasiruddin UIN Syarif Hidayatullah Jakarta, Indonesia
Nurhasanah Universitas Muhammadiyah Tangerang, Indonesia

Keywords:

digital leadership, artificial intelligence readiness, teaching innovation, academic performance, Islamic higher education, PLS-SEM

Abstract

Purpose of the study: This study examines whether digital leadership, artificial intelligence readiness, and teaching innovation predict academic performance among students of private Islamic higher education institutions in DKI Jakarta, and whether artificial intelligence readiness and teaching innovation mediate the effect of digital leadership. Methodology: The study employs a quantitative explanatory design with a cross-sectional survey of 250 students selected through proportionate stratified random sampling. Data were collected using an eighteen-item, five-point Likert-scale questionnaire and analyzed using partial least squares structural equation modeling (PLS-SEM) in the SEMinR package for R with 1,000 bootstrap subsamples. Main Findings: All five structural paths were significant. Digital leadership predicted AI readiness (β = 0.957), teaching innovation (β = 0.954), and academic performance (β = 0.904). Teaching innovation predicted academic performance positively (β = 1.048), whereas AI readiness carried a significant negative coefficient (β = −0.957). The model explained 98.8% of the variance in academic performance. AI readiness showed competitive mediation (indirect effect = −0.916), while teaching innovation transmitted a positive indirect effect (1.000). Novelty/Originality of this study: This study situates AI readiness at the intersection of digital leadership, teaching innovation, and academic performance in Indonesian private Islamic higher education. Moving beyond institution-level readiness assessments, it models student-level pathways, reveals the counterintuitive negative mediation of AI readiness, and positions teaching innovation as the essential pedagogical conduit in non-secular, resource-constrained institutional contexts

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