AI-Supported Higher Education and Students’ Psychological Well-Being: Examining The Roles of Academic Resilience and Learning Autonomy

Abstract

This study examined the relationship between AI-supported higher education, academic resilience, learning autonomy, and students’ psychological well-being. A quantitative, cross-sectional research design was employed to investigate how technology-supported educational experiences and students’ personal academic resources were associated with psychological well-being in contemporary higher education. Data were collected from 321 university students enrolled in higher education institutions in Pakistan through a structured, adapted questionnaire administered online using Google Forms. The questionnaire assessed AI-supported higher education, academic resilience, learning autonomy, and psychological well-being using established measures, including the Academic Resilience Scale (ARS-30), the Psychological Well-Being Scale based on Ryff’s multidimensional model, and a Learner Autonomy scale. The collected data were organized in Microsoft Excel and analyzed using IBM SPSS Statistics. Descriptive statistics, Cronbach’s alpha, Pearson product-moment correlation, multiple linear regression, independent-samples t-test, one-way analysis of variance (ANOVA), and Tukey HSD post-hoc analysis were employed according to the research objectives. The findings showed that AI-supported higher education, academic resilience, and learning autonomy were positively associated with psychological well-being. The regression findings further indicated that all three variables significantly contributed to students’ psychological well-being, while demographic analysis showed significant differences across selected age groups and frequency of AI use. The findings suggest that students’ psychological resources may play an important role in shaping their experiences within increasingly technology-supported learning environments. The study highlights the importance of integrating technological and psychological perspectives when examining contemporary higher education and provides useful evidence for understanding how AI-supported learning and students’ personal academic resources are associated with positive psychological functioning. The study may provide a useful foundation for educators and researchers seeking to develop supportive higher education environments that consider both technological advancement and students’ psychological needs.