[4R3-OS-22b] グループインタラクションとAI

[4R3-OS-22b-03] Quantitative Visualization of Online or Face-to-face Discussions for Reflection

〇Kohei Nagira¹, Takeshi Mizumoto¹ (1. Hylable Inc.)

Keywords:Metacognition, Discussion analysis, Discussion visualization, Speech signal processing, Quantitative analysis

The ability to communicate effectively with people of diverse backgrounds is becoming increasingly important, and one way to improve communication skills is through reflection. However, the conventional reflection that relies on subjective self-assessment may not identify areas for improvement, particularly for people with low meta-cognition. To address this issue, the authors have developed a system for quantifying and visualizing discussions in the form of "amount of speech and its change over time," "turn-taking," and "S-T analysis." The system supports objective fact-based reviews of online and face-to-face discussions and has analyzed over 60,000 people. This paper provides an overview of the system and introduces its visualization examples in educational field.