Blending with AI: The role of student characteristics in blended learning personalisation

Abstract

Blended learning personalisation tailors experiences to individual student needs, leveraging technology to create flexible and inclusive learning environments. Achieving this requires understanding student characteristics that comprise personal backgrounds, attitudes, preferences and prior knowledge and how these inform the student–teacher–technology–curriculum relationship. Artificial intelligence (AI) presents further opportunities for blended learning personalisation in contemporary higher education, highlighting the need to understand student perspectives on AI's potential role. This mixed methods study investigated which student characteristics are associated with preferences for different personalisation approaches, including how students perceive AI’s role in blended learning environments. We surveyed 113 students at an Australian research-focused university, followed by semi-structured interviews with a subset of 20 participants. Our results suggest that student characteristics vary in significance, being significant in shaping feedback and supporting learning, but not in how learning materials are personalised. We provide recommendations for further research and practice on AI implementation and blended learning personalisation.

Implications for practice or policy:

• Course designers could enhance personalisation interventions by focusing on feedback rather than alternative learning materials.
• Policymakers should design AI implementation policies as context sensitive rather than uniform.
• Educators implementing student-facing AI tools should provide clear guidance on appropriate use to address concerns about overreliance and academic integrity.
• Programme leaders should review learning experiences across year levels, given the variation in student perceptions of course quality.