Factors Influencing AI Learning Motivation and Personalisation Among Pre-service Teachers in Higher Education

This study examines the integration of artificial intelligence (AI) in education, focusing on motivating pre-service teachers to utilise AI technologies. The research assesses factors influencing their motivation for AI learning and personalisation in higher education. Over 14 weeks, 180 pre-service teachers participated in a qualitative case study with quantitative content analysis. Results indicate a positive attitude towards AI use among these future educators. The study concludes that AI-enhanced learning can significantly improve teacher-student interactions through personalised feedback, learning guidance and collaborative experiences across various platforms. Findings suggest AI has the potential to enhance personalised learning by tailoring content to individual student needs, preferences and learning styles. Educational policies should encourage a balanced approach to AI implementation, recognising its benefits whilst maintaining human interaction. Although AI may reduce face-to-face engagement, striking a balance where it supports rather than replaces human interaction can strengthen teacher-student relationships. By providing detailed insights into students’ progress and challenges, AI can help teachers offer more targeted support and encouragement.