Advancing Higher Education: Longitudinal Study on AI Integration and Its Impact on Learning

Marviola Hardini; Hetilaniar Hetilaniar; Semaria Eva Elita Girsang; Souza Nurafrianto Windiartono Putra; Ihsan Nuril Hikam

doi:10.34306/ijcitsm.v5i1.185

Authors

Marviola Hardini University of Raharja https://orcid.org/0000-0003-3336-2131
Hetilaniar Hetilaniar University PGRI Palembang https://orcid.org/0000-0001-6564-4358
Semaria Eva Elita Girsang Simalungun University, https://orcid.org/0000-0002-2337-2064
Souza Nurafrianto Windiartono Putra Universit¨at des Saarlandes
Ihsan Nuril Hikam University of Raharja https://orcid.org/0009-0000-0345-9763

DOI:

https://doi.org/10.34306/ijcitsm.v5i1.185

Keywords:

Artificial Intelligence, Higher Education, Personalized Learning, Student Engagement

Abstract

The integration of Artificial Intelligence (AI) into higher education is reshaping the learning landscape. This longitudinal study explores AI impact on learning outcomes, student engagement, and the overall educational experience, focusing on five key variables: AI-enabled Personalized Learning (AIPL), Student Engagement Metrics, Cognitive Skill Development (CSD), Digital Literacy Advancement (DLA), and Educational Resource Optimization (ERO). Using Structural Equation Modeling (SEM) with SmartPLS, the study analyzes these variables to assess AI effectiveness as a pedagogical tool. By evaluating how AI influences student engagement and academic performance, this research highlights the potential of AI to enhance cognitive skills and digital literacy, optimize educational resources, and improve learning efficiency. The study spans multiple academic terms to track the evolving impact of AI, ensuring its long-term sustainability in modern education. The findings aim to inform future strategies for AI integration in higher education, contributing to the broader discourse on AI transformative role in education and providing actionable insights for educators and policymakers. By focusing on the core principles of AI-driven innovation and learning optimization, this research seeks to offer evidence-based recommendations to improve the quality and accessibility of education.

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