Author(s):
Need. The project aims to fulfill the need of advancing education in Artificial Intelligence. It does so by building and evaluating ACHIEVE, an extended reality (XR) system that provides learners with an immersive and interactive visualization of neural networks. The learner wears an XR headset to see the neural network integrated into their physical surroundings. This way the learner can still interact with important elements of their physical surroundings, such as their laptop, fellow students, or the instructor. Furthermore, seeing the physical world anchors the learner, reducing the risk of cybersickness.Guiding questions. The project is guided by the following questions. (1) How to design and implement an XR environment to best support learning in AI through immersive and interactive mixed reality visualization? (2) How do different levels of embodied learning, i.e., immersive vs. non-immersive, relate to students’ ability to learn, apply, and transfer learned AI concepts and practices? (3) How do students’ characteristics (i.e., cognitive load and spatial abilities) and backgrounds (i.e., STEM vs. non-STEM major, academic level, and gender) relate to students’ ability to learn, apply and transfer their learning of AI concepts?Outcomes. The project targets foundational topics in AI and will contribute to discipline-based education research in AI education. The findings will generate new knowledge about students’ conceptual understanding of AI constructs and procedural understanding of AI practices. The project will generate pedagogical strategies grounded in embodied learning for teaching and learning complex topics in computing. The project will develop and validate ACHIEVE, a real-time interactive VR AI learning tool.Broader Impacts. The project will engage educators and interdisciplinary researchers with backgrounds in discipline-based education research and CS to create learning resources and research instruments. The resources will be grounded in theoretical and instructional approaches that emphasize the development of complex forms of learning. The project will directly impact 250 undergraduates. Project scalability and dissemination plans include extrapolating to The National Data Mine Network: an additional 300 undergrads at a cross-section of minority-serving institutions. The project aims to broaden participation in computing, with a particular focus on increasing women representation.
Coauthors
Voicu Popescu, Purdue University, West Lafayette, IN; Alejandra Magana, Purdue University, West Lafayette, IN; Bedrich Benes, Purdue University, West Lafayette, IN;
