Evaluating AI-Supported Learning: A Mixed-Methods Study of Student Performance, Self-Regulation, and Parental Roles

Abstract

This study examines the impact of AI-supported learning on student academic performance, self-regulated learning, and parental involvement through a mixed-methods research design conducted in Multan. Data were collected from selected colleges and universities as well as households in Multan, Punjab, Pakistan, where students are actively engaged in AI-supported and digital learning environments. This study utilized a convergent parallel mixed methods design, combining quantitative and qualitative information to supply a thorough understand of AI-supported academic practices. A structured Likert scale questionnaire was administered to 224 students and 8 semi-structured interviews with students and parents were conducted to gather quantitative data and qualitative data respectively. An analysis of statistical data was carried out with SPSS through descriptive statistics, Pearson correlation, regression analysis and ANOVA, while the thematic analysis was used to analyze the qualitative data in order to find out the common features and themes. The result showed that there was a strong positive correlation between the application of AI-supported learning and academic performance (r = 0.612, p < 0.01) that means that the more students use AI, the higher their academic performance is. Finally, using regression analysis, it was found that AI-supported learning has a significant effect on self-regulated learning (R² = 0.346, ? = 0.588, p < 0.001), which indicates that AI technologies can predict students' SRL ability in planning, monitoring and evaluating learning processes. Furthermore, ANOVA results showed that the differences among parental involvement levels according to the level of use of AI-supported learning were significant (F = 24.56, p < 0.001), demonstrating the crucial role of parental supervision and guidance in students' utilization of AI technology. Some of the key advantages of AI-integrated learning that came to light in the thematic findings were enhanced understanding, personalization, motivation and support. There was also a complaint that the students were relying too heavily on AI, not thinking through their work, cheating, and privacy issues and spending too much time on their screens. Parents were identified as a key role as supports responsible learning behaviors and monitoring AI usage. Last, and most promising, AI application in learning, if used appropriately and ethically, and coupled with appropriate and ethical parent involvement and engagement in children's learning, offers great promise in enriching education and student performance.