Speaker: Arun Balajiee Lekshmi Narayanan

Abstract: A powerful set of educational tools has emerged over the last decade with the rise in the adoption of online adaptive learning content. An increasingly popular tool in this space is the ``intelligent textbook'' as a platform to support and distribute content for e-learning, given its resemblance with real-life physical books. Existing efforts in this direction include the development of digital textbooks where both textual content and interactive learning activities (i.e., examples, problems, etc.) are carefully handcrafted by the authors so that they are perfectly placed to follow the knowledge acquisition-practice flow. However, this approach is very time-consuming, and it requires the work of high-expertise authors. In this presentation, I will discuss three different (implemented and proposed) modifications to automate this process of enhancing and embedding smart content recommendation and intelligent agents in digital textbooks.*

*Note: The actual scope of the presentation may vary from the claims made in the abstract.

Bio: Arun Balajiee Lekshmi Narayanan is a PhD student in the Intelligent Systems Program. His research interests include Human Computer Interaction, Artificial Intelligence in Education Technologies, and Intelligent Tutoring Systems.

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