2021/07/30 by Ajay Kulkarni, Kulkarni, Ajay, Olga Gkountouna +1
Computer Science · #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Machine Learning (cs.LG) #Online Learning and Analytics #Teaching and Learning Programming #cs.AI #cs.CY #cs.LG
paper · pdf · doi:10.48550/arxiv.2108.07693
Published in the 14th International Conference on Educational Data Mining (EDM21)
arxiv created 2021/07/30 · openalex publication_date 2021/07/30 · arxiv updated 2021/08/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a demonstration of REACT, a new Real-time Educational AI-powered Classroom Tool that employs EDM techniques for supporting the decision-making process of educators. REACT is a data-driven tool with a user-friendly graphical interface. It analyzes students' performance data and provides context-based alerts as well as recommendations to educators for course planning. Furthermore, it incorporates model-agnostic explanations for bringing explainability and interpretability in the process of decision making. This paper demonstrates a use case scenario of our proposed tool using a real-world dataset and presents the design of its architecture and user interface. This demonstration focuses on the agglomerative clustering of students based on their performance (i.e., incorrect responses and hints used) during an in-class activity. This formation of clusters of students with similar strengths and weaknesses may help educators to improve their course planning by identifying at-risk students, forming study groups, or encouraging tutoring between students of different strengths.