AI-enabled remote learning: promoting educational equity and mental health sustainability in resource-scarce contexts

This study examines the impact of artificial intelligence (AI)-powered remote learning platforms on students' academic performance and mental health in resource-scarce environments, with a focus on educational equity and sustainable mental health outcomes. We conducted a 12-week randomized controlled trial (RCT) to compare the effects of AI-powered platforms and traditional face-to-face teaching on academic performance, emotional regulation, anxiety, depression, and related indicators. The participants were high school and university students, with pre- and post-assessments used to evaluate both academic outcomes and mental health. Data were analyzed using Structural Equation Modeling (SEM) and Bootstrap. The results show that the AI platform significantly improved students' academic performance (p < 0.001), a finding linked to personalized learning pathways and real-time feedback. Moreover, the AI intervention effectively reduced anxiety (β = -3.378, p < 0.001) and depression (β = -2.919, p < 0.001). However, its effect on emotional regulation was not statistically meaningful (p > 0.05), indicating that while AI systems can alleviate emotional distress, their effect on emotional regulation remains limited. In summary, the study provides evidence that AI-powered learning can narrow equity gaps in resource-scarce contexts, particularly by strengthening academic achievement and reducing negative emotional symptoms. Future studies could extend intervention periods and provide more specialized emotional support to improve both educational and psychological outcomes. These findings highlight the role of educational technology in promoting equity and wellbeing, while also noting the need for context-specific strategies to address emotional regulation.