Generative AI Competence and Student Engagement in Higher Education

Journal of Interdisciplinary Studies in Education 2026 Open access

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Authors: Samuel Nii Adamah Sampah, Macharious Nabang, Elikem Kofi Krampa, Mustapha Issah, Francis Koduah, Harry Barton Essel, Joe Adu-Agyem
DOI: 10.32674/3s3cx241
Cited by: 3

Abstract

This study investigates university students' competence and engagement with Generative AI applications, analyzing usage, perceived autonomy, and AI formal learning as predictive mediators. The study used a cross-sectional survey design to collect data from 262 students across various disciplines. Analysis using PLS-SEM revealed that GenAI competence is a powerful, direct driver of students’ engagement (β = 0.255, p < 0.001), accounting for 64.5% of its variance (R² = 0.645), with the direct path showing a small to medium effect size (f² = 0.117). This relationship is significantly mediated through three distinct pathways: GenAI utilization (β = 0.155, p < 0.001), Perceived Autonomy (β = 0.121, p = 0.005), and AI Formal Learning (β = 0.092, p = 0.005).

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Ethics and Social Impacts of AI AI in Service Interactions

Publication details

Journal / source
Journal of Interdisciplinary Studies in Education
Publisher
STAR Scholars Network
Volume
15
Issue
2
Pages
109–146
Publication date
26 April 2026