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Meeting

2026 TMS Annual Meeting & Exhibition

Symposium

AI/ML/Data Informatics for Materials Discovery: Bridging Experiment, Theory, and Modeling

Presentation Title

Enhancing the Hybrid Learning Experience: Navigating Lecture Videos with AI

Author(s)

Ramsey Issa, Dmitry Bedrov, Taylor Sparks

On-Site Speaker (Planned)

Ramsey Issa

Abstract Scope

As hybrid learning becomes more prevalent, students often struggle to locate and revisit specific concepts hidden within hours of recorded lecture videos, leading to reduced engagement. To address this challenge, we present an interactive chatbot designed to support hybrid learning in a materials science course on engineering materials. The chatbot answers student questions about a series of recorded lecture videos using a retrieval-augmented generation framework. Each lecture is transcribed, segmented with timestamps, and embedded for semantic similarity search. When a student poses a question, the chatbot retrieves the most relevant transcript snippets and uses a language model to generate grounded, context-aware responses. Importantly, it also directs students to the exact video and timestamp where the topic is discussed, enabling precise navigation to relevant material. This approach promotes targeted review, fosters self-directed learning, increases student engagement, and reduces instructor workload by automating responses to frequently asked questions.

Proceedings Inclusion?

Planned:

Keywords

Other, Other, Other

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