Students are most comfortable in group-work assignments that are structured to require contributions from all students.  This prevents dysfunctional situations in which some students “slack” or others dominate the group. Professor Szecsei’s students needed to work collaboratively to hold the robots into position, analyze the components of speech and movement, and offer ideas about both artistic expression and computer programming.

Professor Szecsei operated as a “guide on the side” rather than a “sage on the stage”:  When the students wanted the robots to be able to respond to each other, Professor Szecsei directed students to resources about routers, Raspberry Pis, and Python chat scripts.  Both the students and Professor Szecsei enjoyed this process more than if she had simply delivered a lecture on networking.   

Professor Szecsei’s students often record the robots performing so the class can assess how the programming might be improved.  Providing opportunities to reflect on learning, whether through writing or through group analysis of a video can help ensure that all students are making important intellectual connections.    

Professor Szecsei recommends designing a system for documenting which students collaborated on which part, and she also implemented peer-assessment in which students gave feedback on how their peers were contributing to the projects.  Practitioners find that student buy-in is improved when students understand how they will be graded.  Practitioners recommend discussing the grading system with students, especially in team-based learning.  Furthermore, this rubric from the UI Center for Teaching offers some ideas for grading problem-based learning assignments.