Project Lead: Bowen Hui, Computer Science, Mathematics, Physics, and Statistics UBCO
Project description
Our context is to help instructors form teams in large classes using a tool we built called Teamabe Analytics. In large classes, there are typically too many constraints (expressed by the instructor and/or in combination with the student preferences). When Teamable Analytics returns a list of formed teams, it is crucial to help the instructor understand which teams are formed based on the stated pedagogical objectives and which teams need to be fixed. Since our target users come from interdisciplinary backgrounds, we decided to introduce a simple visualization feature to help instructors diagnose how well the generated teams conform with the stated criteria. Our goal is to investigate which visualization should be used for the target users, whether these techniques improve the team formation process, and whether user trust is impacted.
Research questions
- How do we apply existing data visualization guidelines to create visualizations that help instructors diagnose their teams?
- How well do these techniques help instructors understand the structure of their teams?
- Does user trust in the software increase as a result of this visualization diagnosis process?