VizGroup: An AI-assisted Event-driven System for Collaborative Programming Learning Analytics
Xiaohang Tang, Sam Wong, Kevin Pu, Xi Chen, Yalong Yang, Yan Chen
Abstract
Programming instructors often conduct collaborative learning activities, like Peer Instruction, to foster a deeper understanding in students and enhance their engagement with learning. These activities, however, may not always yield productive outcomes due to the diversity of student mental models and their ineffective collaboration. In this work, we introduce VizGroup, an AI-assisted system that enables programming instructors to easily oversee students’ real-time collaborative learning behaviors during large programming courses. VizGroup leverages Large Language Models (LLMs) to recommend event specifications for instructors so that they can simultaneously track and receive alerts about key correlation patterns between various collaboration metrics and ongoing coding tasks. We evaluated VizGroup with 12 instructors in a comparison study using a dataset collected from a Peer Instruction activity that was conducted in a large programming lecture. The results showed that VizGroup helped instructors effectively overview, narrow down, and track nuances throughout students’ behaviors.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 49fbbdb2-9ee7-460e-bcee-c23928373434Cited by top-tier papers6
- Unlocking Scientific Concepts: How Effective Are LLM-Generated Analogies for Student Understanding and Classroom Practice?Zekai Shao, Siyu Yuan, Lin Gao, Yixuan He et al.CHI 2025 · 12 citations
- LitLinker: Supporting the Ideation of Interdisciplinary Contexts with Large Language Models for Teaching Literature in Elementary SchoolsHaoxiang Fan, Changshuang Zhou, Hao Yu, Xueyang Wu et al.CHI 2025 · 8 citations
- CPVis: Evidence-based Multimodal Learning Analytics for Evaluation in Collaborative ProgrammingGefei Zhang, Shenming Ji, Yicao Li, Jingwei Tang et al.CHI 2025 · 8 citations
- CoGrader: Transforming Instructors' Assessment of Project Reports through Collaborative LLM IntegrationZixin Chen, Jiachen Wang, Yumeng Li, Haobo Li et al.UIST 2025 · 3 citations
- ViseGPT: Towards Better Alignment of LLM-generated Data Wrangling Scripts and User PromptsJiajun Zhu, Xinyu Cheng, Zhongsu Luo, Yunfan Zhou et al.UIST 2025 · 1 citation
Builds on8
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah et al.NeurIPS 2020 · 64,255 citations
- AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model PromptsTongshuang Wu, Michael Terry, Carrie Jun CaiCHI 2022 · 465 citations
- Glancee: An Adaptable System for Instructors to Grasp Student Learning Status in Synchronous Online ClassesShuai Ma, Taichang Zhou, Fei Nie, Xiaojuan MaCHI 2022 · 51 citations
- Pair-Up: Prototyping Human-AI Co-orchestration of Dynamic Transitions between Individual and Collaborative Learning in the ClassroomKexin Bella Yang, Vanessa Echeverría, Zijing Lu, Hongyu Mao et al.CHI 2023 · 43 citations
- VizProg: Identifying Misunderstandings By Visualizing Students' Coding ProgressAshley Ge Zhang, Yan Chen, Steve OneyCHI 2023 · 31 citations
Related papers
- From Code Generation to Conceptual Learning: Student Use of LLMs in a Web Programming CourseHajara-Yasmin Isa, Matthew Weston, Muhammad Rizky Wellyanto, Ishita Karna et al.CHI 2026 · 1 citation
- VIVID: Human-AI Collaborative Authoring of Vicarious Dialogues from Lecture VideosSeulgi Choi, Hyewon Lee, Yoonjoo Lee, Juho KimCHI 2024 · 16 citations
- CoPrompt: Supporting Prompt Sharing and Referring in Collaborative Natural Language ProgrammingLi Feng, Ryan Yen, Yuzhe You, Mingming Fan et al.CHI 2024 · 28 citations
- CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator NeedsMajeed Kazemitabaar, Runlong Ye, Xiaoning Wang, Austin Zachary Henley et al.CHI 2024 · 246 citations
- StuGPTViz: A Visual Analytics Approach to Understand Student-ChatGPT InteractionsZixin Chen, Jiachen Wang, Meng Xia, Kento Shigyo et al.IEEE VIS 2024 · 14 citations
