The Impact of AI-Supported Learning on Self-Regulated Learning and Learning Outcomes in Adult Education: Evidence from a Cross-Sectional Study in China

Abstract

In recent years, the rapid development of artificial intelligence (AI) has reshaped educational practices across K–12 and higher education, yet its role in adult education remains underexplored. Adult education is a crucial domain for lifelong learning and workforce development, where learners face unique challenges such as balancing study with work and family responsibilities. Against this backdrop, this study examines the impact of AI-supported learning on self-regulated learning (SRL) and learning outcomes among adult learners in China. Using a quantitative, cross-sectional survey design, data were collected from 138 participants enrolled in diverse adult education programs. A structured questionnaire assessed AI-supported learning usage, SRL, and self-reported learning outcomes. Correlation analysis revealed significant positive associations among all three variables. Hierarchical regression showed that AI-supported learning usage strongly predicted SRL (β = .52, p < .001) and moderately predicted learning outcomes (β = .33, p < .001) after controlling for demographics. Mediation analysis using the PROCESS macro indicated that SRL partially mediated the relationship between AI-supported learning usage and learning outcomes, accounting for 39% of the total effect. Findings highlight the value of integrating AI tools that enhance SRL skills to improve learning performance in adult education, offering practical guidance for educators and policymakers. Future research should adopt longitudinal or experimental designs to establish causal effects and explore how AI interacts with learner diversity across cultural and institutional contexts.

Keywords: AI-supported learning; self-regulated learning; learning outcomes; adult education.

DOI: 10.7176/JEP/16-9-12

Publication date:August 31^st 2025