Leveraging AI and pedagogical competence to enhance learning interest and outcomes: evidence from Islamic university

Abstract

This study investigates the effects of artificial intelligence (AI)-supported intelligent educational systems and teacher pedagogical competence (TPC) on students’ learning interest (LI) and learning outcomes (LO) in an Islamic higher education context. AI is operationalized as AI-supported learning system features embedded in institutional learning platforms, particularly natural language processing (NLP)-based automated feedback and AI-driven recommendation functionalities that support adaptive and personalized learning. The study was conducted at the As-Syifa Institute, Subang, Indonesia, involving 366 undergraduate students from the first, third, and fifth semesters. Data were analyzed using partial least squares-structural equation modeling (PLS-SEM) with SmartPLS 4 to examine the structural relationships among AI system use, TPC, LI, and LO. The results demonstrate that AI-supported learning system features have significant positive effects on both LI and LO. TPC also shows a strong direct effect and mediates the relationship between AI-supported systems and student outcomes. These findings highlight the importance of human-AI integration, indicating that pedagogical competence plays a critical role in translating AI system functionalities into meaningful educational benefits. This study contributes to the AI-in-education literature by providing empirical evidence on pedagogically mediated AI-supported learning systems and offers insights for the design and evaluation of adaptive and intelligent learning environments in higher education.