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AI tutoring system improves public speaking with multimodal feedback

By PulseAugur Editorial · [1 sources] ·

Researchers have developed an interpretable closed-loop Intelligent Tutoring System (ITS) designed to enhance public speaking skills through multimodal feedback. The system utilizes an XGBoost model to analyze facial, vocal, textual, and oculomotor features from video segments, providing feedback aligned with a seven-dimensional rating scale. Trained on over 10,000 MOOC video segments, the ITS demonstrated scoring accuracy comparable to expert ratings and led to significant skill improvements in adult learners over a 30-day practice period. AI

IMPACT Demonstrates how AI can provide structured, interpretable feedback for skill development, potentially improving educational tools.

RANK_REASON Publication of an academic paper detailing a new AI system and its evaluation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI tutoring system improves public speaking with multimodal feedback

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Publication of an academic paper detailing a new AI system and its evaluation. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Hung-Yue Suen, Kuo-En Hung ·

    An Interpretable Closed-Loop Intelligent Tutoring System for Multimodal Affective Feedback in Asynchronous Presentation Training

    arXiv:2605.17468v2 Announce Type: replace-cross Abstract: This paper presents an interpretable closed-loop Intelligent Tutoring System (ITS) that supports feedback-guided practice for developing on-camera oral presentation skills at scale. The system operationalizes a seven-dimen…

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