# Walking through Discussions: A Mobile Visual Analytics System for In-Situ Group Discussion Analysis

arXiv: https://arxiv.org/abs/2608.08617 · HTML: https://mlsanity.com/paper/2608.08617/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 69 references that are in the map.
- First posted on arXiv 9 Aug 2026.

## Builds on (most cited first, 17 of 17)

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- [An Automated Approach to Reasoning About Task-Oriented Insights in Responsive Visualization](https://mlsanity.com/paper/2107.08141/) (2021)
- [Glanceable Data Visualizations for Older Adults: Establishing Thresholds and Examining Disparities Between Age Groups](https://mlsanity.com/paper/2403.12343/) (2024)
- [Micro Visualizations on a Smartwatch: Assessing Reading Performance While Walking](https://mlsanity.com/paper/2407.17893/) (2024)
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## Abstract (arXiv)

Group discussion-based teaching is widely used to foster collaborative learning, yet teachers in physical classrooms often struggle to simultaneously monitor multiple groups and quickly diagnose a target group before intervening. Existing visual analytics tools primarily support post-hoc analysis on desktop, providing limited support for in-situ walk-around teaching. To address this gap, we present MobileGroupVis, a mobile visual analytics system for in-situ analysis of classroom group discussions. MobileGroupVis integrates multi-group monitoring, single-group diagnosis, and instructional intervention into a concise analytical workflow tailored for small-screen touch interaction. The system is powered by a lightweight streaming analysis pipeline that converts group audio into structured discussion data and further extracts interaction patterns, topic progression, and topic deviation through a dialogue analysis module. To enable both glanceable overview and traceable diagnosis, we design six coordinated views, including a compact glyph that visually encodes word count, interaction intensity, and topic deviation for efficient cross-group comparison and anomaly localization, along with detailed views for opinion evolution, interaction dynamics, topic coverage, and dialogue records. We evaluate MobileGroupVis through two case studies and expert interviews. The results provide preliminary evidence that MobileGroupVis supports teachers in understanding discussion processes, identifying groups in need of attention, and facilitating in-class intervention.
