Harnessing AI in Education for Sustainable Development: The Interplay of AI-Supported Blended Learning, Student Self-Regulation, and Cognitive Load
TL;DR
Findings show that the use of AImediates the relationship between DT and students’ behavioural and academic outcomes, and shows that the use of AI helps shape student experiences and outcomes.
Abstract
Although blended learning (BL) represents a transformative educational model, it is unclear how digital transformation (DT) shapes the dynamics of BL, particularly through the integration of artificial intelligence (AI), in higher education. This study examines how artificial intelligence–supported self-regulated learning (AI-SRL), informed by cognitive load theory and AI-driven pedagogy, can enhance BL models to promote equitable, inclusive education and advance sustainable development within the context of ongoing DT. Three hundred and ten higher-education students in the United Arab Emirates (UAE) who participated in BL courses completed an online survey. In addition, 11 faculty members and academic leaders were interviewed. The findings show that the use of AI mediates the relationship between DT and students’ behavioural and academic outcomes – namely, procrastination, heuristic processing, and academic achievement. DT increases the adoption of AI to improve academic performance while simultaneously increasing procrastination and reliance on heuristic (surface-level) processing. AI-SRL mitigates these negative outcomes, reducing procrastination and heuristic processing. Furthermore, AI-integrated pedagogy empowers students to harness the benefits of AI-enhanced DT to improve academic performance while minimising adverse cognitive and behavioural effects. This study provides a nuanced understanding of BL in higher education, showing that the use of AI helps shape student experiences and outcomes.