Exploring Learning Analytics (LA), Artificial Intelligence (AI) and User Feedback to Evaluate the Impact of WebXR in Distance Education

This study explores the use of Learning Analytics (LA), artificial intelligence (AI), and user feedback to evaluate the impact of immersive WebXR content in distance education. It examines how the integration of WebXR with generative AI agents into Moodle, a widely used virtual learning environment (VLE), can enhance student engagement, learning outcomes, and satisfaction. The research design includes two learner groups: an experimental group interacting with AI-enhanced WebXR environments, and a control group receiving the same course content of ICT subject, through conventional online learning design methods. Using LA combined with the DeLone and McLean Information Systems Success Model, the study assesses system quality, information quality, service quality, user satisfaction, intention to use, net benefit, academic engagement, and learning gains. A mixed methods approach collects log data from both the Moodle LMS and WebXR platform, alongside self-reported learner feedback, to provide a comprehensive evaluation framework. The findings aim to offer empirical evidence on the effectiveness of immersive technologies enhanced by LA and AI, providing actionable insights and practical recommendations for integrating WebXR tools into existing LMS platforms to foster innovative, engaging, and inclusive distance learning experiences.