By Qian Zhao (Stanford University)
Information
Group projects can be an effective way to teach data science because they help students develop a wide range of intellectual, social, and professional skills. As instructors, can we use group projects as an opportunity to build students’ confidence and skill as self-directed learners? In this beyond session, we describe a few ideas through case studies of two projects at Stanford Data Science for Social Good summer program. In one project, the mentor teaches classification accuracy and fairness in the context of designing and communicating student assignment policies. In the second project, the mentor teaches how to use SQL to analyze data from police encounters. These examples show that the instructor can co-create the learning environment and model the learning process through (1) guiding students to identify what they need to learn, (2) providing handouts for individual learning, (3) facilitating discussions, practice, or providing just-in-time teaching, (4) observing how students apply their new knowledge to project work, and (4) inviting students to discuss different approaches and come to a consensus as a group. We will guide participants to incorporate these ideas in their own teaching of project-based courses.