Scaling up Data Science Course Projects: A Case Study

Abstract

Large-scale, online Data Science (DS) courses and degree programs are becoming increasingly common due to the global rise in popularity and demand for data scientists. Although project-based learning is integral to gaining hands-on experience in DS education, providing fair, timely, and high-quality feedback on varied projects for a large number of diverse students is challenging. To address those challenges in scaling up the assessment of DS group projects, we integrated multiple techniques, such as rapid feedback, peer grading, graders as meta-reviewers, etc. We present a case study of deploying those strategies for group projects in a large online DS course titled Text Information Systems offered in Fall, 2020. We synthesize our findings from analyzing student and grader survey responses, and share useful lessons and future work.