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Developing an LLM-based programming tutorial tool
This project involves creating an intelligent tool designed to enhance the learning experience for students and developers engaging with programming tutorial videos. The tool will use LLMs to automatically analyze and synchronize video content with the corresponding code snippets presented during the tutorial. By mapping specific video timestamps to the code being discussed by the instructor, users can easily navigate between the instructional content and the relevant code.
Keywords: programming education, large language models
Background:
Programming tutorial videos are a popular resource for learning, but learners often find it time-consuming and frustrating to manually navigate between the code and the corresponding explanations in the video. By integrating LLMs with video content, this project aims to provide a seamless learning experience where the video and code are synchronized in real time.
This project involves creating an intelligent tool designed to enhance the learning experience for students and developers engaging with programming tutorial videos. The tool will use LLMs to automatically analyze and synchronize video content with the corresponding code snippets presented during the tutorial. By mapping specific video timestamps to the code being discussed by the instructor, users can easily navigate between the instructional content and the relevant code.
- Code Highlighting: As the video plays, the relevant sections of the code are highlighted, helping learners visualize how the code and the explanations are connected in real time.
- Navigation Shortcuts: Users can click on any part of the code to instantly navigate to the point in the video where that code is being explained, improving accessibility and reducing the need for manual searching.
Target Venue: CHI’2026, UIST2026
Potential Extensions:
- Expand the tool to support other types of tutorial content, such as data science workflows or software engineering processes.
- Develop features like quizzes or coding exercises linked directly to the tutorial content for active learning.
Please attach your **CV** and **transcript**
Background: Programming tutorial videos are a popular resource for learning, but learners often find it time-consuming and frustrating to manually navigate between the code and the corresponding explanations in the video. By integrating LLMs with video content, this project aims to provide a seamless learning experience where the video and code are synchronized in real time.
This project involves creating an intelligent tool designed to enhance the learning experience for students and developers engaging with programming tutorial videos. The tool will use LLMs to automatically analyze and synchronize video content with the corresponding code snippets presented during the tutorial. By mapping specific video timestamps to the code being discussed by the instructor, users can easily navigate between the instructional content and the relevant code.
- Code Highlighting: As the video plays, the relevant sections of the code are highlighted, helping learners visualize how the code and the explanations are connected in real time.
- Navigation Shortcuts: Users can click on any part of the code to instantly navigate to the point in the video where that code is being explained, improving accessibility and reducing the need for manual searching.
Target Venue: CHI’2026, UIST2026
Potential Extensions:
- Expand the tool to support other types of tutorial content, such as data science workflows or software engineering processes. - Develop features like quizzes or coding exercises linked directly to the tutorial content for active learning.
Please attach your **CV** and **transcript**
- Gain experience in developing an educational technology tool.
- Learn how to integrate and apply Large Language Models in real-world applications.
- Improve skills in web development.
- Collaborate with a PhD student, enhance engineering skills and gain insight into academic research.
- Gain experience in developing an educational technology tool. - Learn how to integrate and apply Large Language Models in real-world applications. - Improve skills in web development. - Collaborate with a PhD student, enhance engineering skills and gain insight into academic research.
