Abstract

Collaborative Problem Solving (CPS) skills are necessary for success in today’s workforce, especially in STEM fields like data science and engineering. Many who work in these fields often work with diverse groups of colleagues to solve critical problems. Despite this importance, more effective and personalized teaching methods for CPS skills are needed. In this paper, we present a pilot study that addresses strategies for teaching CPS tailored to data scientists. Inspired by the PISA Collaborative Problem Solving framework, we've designed a specialized module to teach students best practices in deploying CPS competencies needed at the early stages of collaboration, a subset of essential CPS skills. Our study examines the module’s effectiveness in cultivating CPS competencies among students. Students exposed to CPS best practices demonstrate an ability to apply them in a mock data science exercise. These findings contribute to the growing knowledge of teaching and applying CPS skills, providing a promising pathway for CPS education. By leveraging the PISA framework and targeted strategies, our research builds on prior work and lays the foundation for future work leveraging virtual agents to teach these skills.

Date

June 22, 2025

Authors

Neel Manmohan Parekh, Kevin Scroggins, Yolanda Gil, Emmanuel J Dorley

Conference

2025 ASEE Annual Conference & Exposition