One Size Doesn't Fit All: Diversifying Data Science Course Projects by Student Background and Interests

Abstract

A key challenge to a data science program is how to tailor its curriculum to accommodate the needs and interests of students from diverse academic backgrounds. To address this challenge, we propose Proj4X, a general project model that gives students the flexibility in choosing subject areas for the projects based on their background and interests, while requiring every project to address the key knowledge and skills covered in the course. Although project-based learning has been well researched, only a few studies have addressed the challenges in managing student-initiated projects. We have applied Proj4X to a graduate database course in our data science program. We used student peer evaluation to measure the performance of projects objectively and study the effect of group size on the performance of projects and the correlation between specific aspects of a project and its overall rating. Student feedback shows that Proj4X can greatly foster the collaboration among students of diverse backgrounds and inspire them to work on a wide range of interesting topics: from satellite tracker, hospital search during pandemic, to wildlife diversity monitoring.