Project Lead: Fatemeh Salehian Kia, School of Information
Project description
This project pilots a syndicate teaching model to address the limitations of lecture-based teaching in large computational courses. The model combines shorter lectures to introduce concepts with small-group syndicate sessions, fostering active learning, problem-solving, and critical thinking. Each syndicate group, led by teaching assistants, engages 20–25 students in guided, interactive exercises supported by PrairieLearn, an adaptive platform offering auto-graded tasks, immediate feedback, and performance analytics. Implemented in three courses—Computer Programming for Information Professionals, Database Design, and Human-Centered AI—this scalable approach enhances student engagement and learning outcomes. The project will evaluate and refine the model for broader implementation at UBC.
Research questions
- How does the integration of syndicate teaching, facilitated by PrairieLearn, impact students’ behavioral engagement (e.g., participation rates, task completion) and cognitive engagement (e.g., attempts at higher-order questions, time spent on complex tasks, progression through challenges) in the pilot courses?
- How effective is PrairieLearn in scaling the syndicate teaching approach by providing immediate feedback, facilitating hands-on exercises, and supporting large-scale instruction through features like auto-grading, analytics, and content adaptability?
- What are students’ perceptions of the syndicate teaching model, and how do these perceptions align with their engagement and learning outcomes?