Awaking the Slides: A Tuning-free and Knowledge-regulated AI Tutoring System via Language Model Coordination

The vast pre-existing slides serve as rich and important materials to carry lecture knowledge. However, effectively leveraging lecture slides to serve students is difficult due to the multi-modal nature of slide content and the heterogeneous teaching actions. We study the problem of discovering effective designs that convert a slide into an interactive lecture. We develop Slide2Lecture, a tuning-free and knowledge-regulated intelligent tutoring system that can (1) effectively convert an input lecture slide into a structured teaching agenda consisting of a set of heterogeneous teaching actions; (2) create and manage an interactive lecture that generates responsive interactions catering to student learning demands while regulating the interactions to follow teaching actions. Slide2Lecture contains a complete pipeline for learners to obtain an interactive classroom experience to learn the slide. For teachers and developers, Slide2Lecture enables customization to cater to personalized demands. Slide2Lecture's online deployment has made more than 200K interactions with students in the 3K lecture sessions. We release our implementation at https://github.com/NewEduAI/Release.

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Publication Details

Published
2025-04-04
DOI
https://doi.org/10.1145/3690624.3709423
Citations
2
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
3.39
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article

Awaking the Slides: A Tuning-free and Knowledge-regulated AI Tutoring System via Language Model Coordination

Juanzi Li, Daniel Zhang-Li, Huiqin Liu, Z. X. Zhang et al.
2 citations
Online Learning and Analytics
3.39
article

Awaking the Slides: A Tuning-free and Knowledge-regulated AI Tutoring System via Language Model Coordination

Juanzi Li, Daniel Zhang-Li, Huiqin Liu, Z. X. Zhang, Jifan Yu, Lei Hou, Haohua Wang, Shangqing Tu, Zhiyuan Liu, Joy Jia Yin Lim, Linlu Gong
article en
2 citations

Abstract

The vast pre-existing slides serve as rich and important materials to carry lecture knowledge. However, effectively leveraging lecture slides to serve students is difficult due to the multi-modal nature of slide content and the heterogeneous teaching actions. We study the problem of discovering effective designs that convert a slide into an interactive lecture. We develop Slide2Lecture, a tuning-free and knowledge-regulated intelligent tutoring system that can (1) effectively convert an input lecture slide into a structured teaching agenda consisting of a set of heterogeneous teaching actions; (2) create and manage an interactive lecture that generates responsive interactions catering to student learning demands while regulating the interactions to follow teaching actions. Slide2Lecture contains a complete pipeline for learners to obtain an interactive classroom experience to learn the slide. For teachers and developers, Slide2Lecture enables customization to cater to personalized demands. Slide2Lecture's online deployment has made more than 200K interactions with students in the 3K lecture sessions. We release our implementation at https://github.com/NewEduAI/Release.

University Town of Shenzhen (CN), Tsinghua University (CN)
Quality Education
Openalex Percentile: Top 8%
Online Learning and Analytics
3.39
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