Integrating Personality and Learning Profiles of Students in Formative Course Evaluation System for Gaining Insights on Diversity and Improving Learner Experience Analytics Dashboard

The study address the scarcity of empirical design research on personalized feedback analytics in higher education. It focuses on the redesign and testing of a prototype, aiming to tackle the design dilemmas associated with personality profiles and personalized analytics for both teachers and stu-dents. Building upon the existing Wyblo App, the click-through prototype integrates VARK and MBTI models for learning preferences and personality analysis. Employing a design thinking methodology and a mixed-methods approach, the research defined requirements through interviews, surveys, and existing literature. The prototype's interfaces provided teachers with personality and learning preferences-based feedback analysis, aiding in pedagogical decisions. For students, the analytics offered personalized insights and recommendations compared to peers. The positive feedback from initial testing served as anecdotal evidence, emphasizing the need for broader, authentic testing for reliable generalization. The study envisions inspiring learning technology designers to incorporate personalized insights into course evaluation analytics, fostering reflective practices for both students and teachers based on individualized learning preferences and teaching approaches.