Artificial Intelligence Usage and Academic Performance Among University Students: The Mediating Role of Self-Regulated Learning

Ayesha Kiren; Syed Kinza ul Emman; Amanna Rahat; Marium Akhtar

doi:10.47067/ramss.v9i2.659

Authors

Ayesha Kiren University of Agriculture, Faisalabad, Pakista
Syed Kinza ul Emman Lecturer, Department of Business Management & Social Sciences, The Millennium Universal College, Lahore, Pakistan
Amanna Rahat DBA Scholar, Inti International University, Malaysia
Marium Akhtar M.Phil. Scholar (Peace and Conflict Studies), National Defense University, Islamabad, Pakistan

DOI:

https://doi.org/10.47067/ramss.v9i2.659

Keywords:

Artificial Intelligence, Academic Performance, Self-Regulated Learning, University Students, Higher Education, Generative AI, Digital Learning, Educational Technology

Abstract

Artificial Intelligence (AI) has rapidly emerged as a transformative technology in higher education, offering personalized learning support, intelligent tutoring, and enhanced academic assistance that may improve students' educational outcomes. This study examined the effect of Artificial Intelligence usage on university students' academic performance and investigated the mediating role of self-regulated learning in this relationship. A quantitative research approach employing a cross-sectional survey design was adopted. Data were collected through a structured questionnaire from 423 undergraduate and postgraduate students enrolled in six public universities in Punjab, Pakistan, using convenience sampling. The data were analyzed using IBM SPSS Statistics through descriptive statistics, Pearson correlation, regression analysis, and mediation analysis. The findings revealed a significant positive relationship between Artificial Intelligence usage and academic performance (r = 0.648, p < .01). Regression analysis further demonstrated that Artificial Intelligence usage significantly predicted self-regulated learning (? = 0.653, p < .001), explaining 42.6% of its variance. Mediation analysis confirmed that self-regulated learning significantly and partially mediated the relationship between Artificial Intelligence usage and academic performance through both direct (? = 0.341, p < .001) and indirect effects (? = 0.308, p < .001). These findings indicate that Artificial Intelligence enhances students' academic performance not only by directly supporting learning activities but also by fostering self-regulated learning skills such as goal setting, time management, self-monitoring, and independent learning. The study concludes that the responsible integration of Artificial Intelligence into higher education can substantially improve students' academic success by strengthening both learning processes and self-regulatory capabilities, providing important implications for educators, policymakers, and universities seeking to promote effective and ethical AI-assisted learning environments.

Author Biography

Amanna Rahat, DBA Scholar, Inti International University, Malaysia

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