By Monsur Chowdhury (University of Georgia)
Information
Engaging students in statistics education requires interactive learning, timely feedback, and personalized support. This project integrates Peer Learning Assistants (PLAs) and an AI-driven chatbot to enhance student engagement and learning outcomes. By leveraging human mentorship and AI-based tutoring, we create a blended learning environment that supports active learning practices.
The customized chatbot serves as an intelligent tutor, providing 24/7 support by answering statistical queries, guiding students through problem-solving, and reinforcing theoretical concepts. Designed to accommodate diverse learning styles, the chatbot delivers instant feedback, encourages self-paced learning, and ensures continuous access to educational resources.
Meanwhile, Peer Learning Assistants (PLAs) complement this technology-driven approach by fostering collaborative learning. PLAs guide students through discussions, assist with coding exercises, and offer structured problem-solving support, creating an engaging and supportive learning community. This human-centered approach promotes deeper understanding, critical thinking, and confidence in statistical concepts.
This model has been implemented in STAT 2360 and STAT 6800 with 30 students in each class at the University of Georgia, leading to increased student participation, confidence, and academic performance. Course assessments and student feedback highlight improved conceptual understanding and a stronger sense of community-based learning.
Our poster presents the structure, implementation, and impact of this dual-framework approach, demonstrating how PLAs and AI-driven support can transform statistics education. Findings suggest that integrating human interaction with AI assistance creates a more inclusive and effective learning environment. Future directions include scaling this model across additional courses and refining AI capabilities for more personalized learning experiences