A Personalized Learning Approach to Support Students with Diverse Academic Backgrounds

Teaching design thinking and human-computer interaction (HCI) from technical disciplines are challenging due to the need for frequent content refreshes using up-to-date technology examples and students' negative preconceptions about the material. In particular, students typically find the course content too easy and the grading too subjective. Beyond these issues, the problems in our HCI course are exacerbated by the diversity of academic backgrounds in the student population. Over the years, we have struggled to deliver the course material at a pace that is appropriate for everyone and to develop assessments that can fairly evaluate the relevant design and technical skills involved. Here, we propose a personalized learning approach to tackle the problem of delivering content that suits students with diverse academic backgrounds. Specifically, we designed four features to personalize assessments in the HCI course: alternative pathways, flexible timing, multiple test attempts, and choice in programming options. Our study with 360 students showed a high uptake in all the personalization features and a positive impact on student performance and perception of the course. This case study describes how we implemented these personalized learning features successfully in a large university class to improve the student's learning experience. We discuss implementation tradeoffs and the generalizability of these features.