  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.
