Facilitating Relational Feedback through AI-powered Learning Analytics

Feedback plays a crucial role in student success in higher education but often fails to engage students effectively. This PhD thesis focuses on improving the quality of feedback by emphasizing the relational aspects, which consider the emotional and interpersonal dynamics between instructors and students. The research developed a framework for relational feedback using a systematic review and proposed using advanced AI to help instructors provide relational feedback. Studies were conducted to test the effectiveness of relational feedback, and explore AI's potential in reducing instructors' workload. The findings suggest ways to better integrate relational feedback into teaching, potentially enhancing student engagement and learning outcomes.