Automated Group Discussion Feedback and Scoring with AI
DOI:
https://doi.org/10.47392/IRJAEH.2025.0161Keywords:
Academic discussions, Participant engagement, Structured interactions, Personalized feedback, Ethical guidelines, Behavior analysis, Real-time monitoringAbstract
In traditional group discussions, the absence of a human moderator can lead to issues such as dominance by certain individuals, lack of adherence to discussion rules, and insufficient feedback for participants. To address these challenges, an AI-driven group discussion platform is being developed to ensure structured, fair, and productive interactions. The platform will monitor discussions via video, using machine learning to analyze participants' behavior and adherence to ethical guidelines. AI will provide real-time guidance and personalized feedback, assessing individual contributions to highlight strengths and areas for improvement. Comprehensive reports will be generated for each participant, tracking their progress over time. The platform will support two modes: a random call discussion mode for spontaneous interactions and a dedicated college mode for student discussions within an academic context. Timed sessions will ensure focused and efficient discussions. By integrating continuous assessment and rewarding active participation, the platform aims to enhance communication skills, promote ethical behavior, and foster a collaborative learning environment.
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