Integrating Introductory Data Science into Computer and Information Literacy through Collaborative Project-based Learning

Abstract

In this era of technology and science, data skills are critical for full participation in the workforce and contemporary society. Alarmingly not all graduates exit college with what are nothing less than survival skills. The goals of the course curriculum innovation are to raise the awareness of data science, promote retention, increase the interest and curiosity, and boost essential data skills for all students on campus. These goals are similar to existing efforts on the design of introductory data science courses for majors and non-majors. The distinctiveness of this course curriculum resides in hands-on learning by examples, case studies, and team-based projects within a low-stakes format, where students from different disciplines early in their college careers collaborated to ethically solve problems in the repetition of data science life cycles. The Innovative Practice Category Work in Progress paper presents our experience in integrating introductory data science into a college-wide computer and information literacy course via collaborative practices of exemplar and project-based learning. The collaborative learning with wide interdisciplinary focus enriched our pedagogues and scalability. Its effectiveness has been measured in a poster session and student perceptions on 5-point Likert scales. Furthermore, integrating introductory data science into a computer and information literacy course served to optimize existing educational resources and facilitate multiple pathways in college. The methodology and studio-like training shown in the experience report can be expanded to upper-level data science courses.