AI Unplugged: Embodied Interactions for AI Literacy in Higher Education
This addresses the need for non-code-centric AI education for university students, though it is incremental as it adapts existing CS Unplugged methods to AI.
The paper tackled the problem of fostering holistic AI literacy in higher education by integrating embodied, unplugged activities into an Introduction to AI course, resulting in students building intuition for complex AI concepts and more easily transitioning to mathematical formalizations and code implementations.
As artificial intelligence (AI) becomes increasingly integrated into daily life, higher education must move beyond code-centric instruction to foster holistic AI literacy. We present a novel pedagogical approach that integrates embodied, unplugged activities into a university-level Introduction to AI course. Inspired by the effectiveness of CS Unplugged in K-12 education, our physical, collaborative activities gave students a first-person perspective on AI decision-making. Through interactive games modeling Search Algorithms, Markov Decision Processes, Q-learning, and Hidden Markov Models, students built an intuition for complex AI concepts and more easily transitioned to mathematical formalizations and code implementations. We present four unplugged AI activities, describe how to bridge from unplugged activities to plugged coding tasks, reflect on implementation challenges, and propose refinements. We suggest that unplugged activities can effectively bridge conceptual reasoning and technical skill-building in university-level AI education.