Developing a Framework for Personalized Video-Based Quantum Information Science Education

This is a white paper on Workforce Development for Quantum Information Sciences (QIS) led by the Center for Real-Time Computing at Old Dominion University (ODU). We plan to investigate the potential of video lectures in supporting QIS. Specifically, we focus on following four objectives: ($a$) design a two-course series for both Master-level and PhD students; b) an upgrade of Experimental Lecture System (ELeSy) to test new, innovative, and transformative approaches for inclusive QIS education; c) design and implementation of a mixed-method systematic empirical study on the effects of video learning styles (in-person flipped classroom and voluntary video use) on graduate students' QIS studies, and d) integration of the empirical results and requirements and development of a framework with practical (e.g., best practices) and technical (e.g., systems' design guidelines) knowledge, addressing how instructors and developers can increase video lecture benefits by incorporating AI-based learning tools. The contributions of our white paper are a) methodology for evaluating a novel experimental video analytics system, b) the systematic empirical evaluation of video lectures as a learning technology for QIS, and c) motivating the discussion on how instructors and developers can increase video lecture benefits. The project results (over the next three to five years) will be shared with the broader community and participants.