{"id":2536,"date":"2026-08-17T19:33:06","date_gmt":"2026-08-18T02:33:06","guid":{"rendered":"https:\/\/labs.wsu.edu\/caire\/?page_id=2536"},"modified":"2026-08-17T19:33:07","modified_gmt":"2026-08-18T02:33:07","slug":"nivdia-vta","status":"publish","type":"page","link":"https:\/\/labs.wsu.edu\/caire\/nivdia-vta\/","title":{"rendered":"NIVDIA-VTA"},"content":{"rendered":"
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NIVDIA-Virtual Teaching Assistant (VTA)<\/span><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n<\/div>\n\n\n\n\n\n\n
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Project Description<\/h2>\n\n

The Virtual Teaching Assistant (VTA) project develops and evaluates a multimodal AI learning system that provides students with timely, trustworthy, and course-grounded support while helping instructors better understand student learning. Many existing AI assistants rely primarily on text and may struggle to interpret the diverse resources students encounter in STEM courses, including lecture slides, diagrams, figures, assignments, audio, and video.<\/p>\n\n

The VTA addresses this challenge through a Mixture-of-Experts (MoE) architecture that integrates specialized text, vision–language, and audio capabilities. Student questions are dynamically routed to appropriate AI experts, while responses are grounded in course materials and linked back to their sources. At the same time, the system provides instructors with learning analytics that surface common misconceptions, engagement patterns, and areas where students may need additional support. The project will pilot the VTA in an undergraduate classroom to examine both its technical performance and its potential to support student learning and instructor decision-making.<\/p>\n\n

WSU Insider: NVIDIA grant will support AI for teaching and learning<\/a><\/p>\n <\/div>\n\n