Coding Code: Qualitative Methods for Investigating Data Science Skills

Wednesday, January 31st, 20244:00 pm – 5:00 pm ET

Presented by: Allison Theobold (California Polytechnic State University, San Luis Obispo), Megan Wickstrom (Montana State University), Stacey Hancock (Montana State University)


Abstract: In this January edition of the JSDSE/CAUSE webinar series, we highlight the 2023 article: Coding Code: Qualitative Methods for Investigating Data Science Skills The authors will discuss how to conceptualize and carry out a qualitative coding process with students' computing code, which allows them to explore research questions about students' learning. Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these studies illuminate different aspects of students’ programming behavior or conceptual understanding, a method has yet to be employed that can shed light on students’ learning processes. This type of inquiry necessitates qualitative methods, which allow for a holistic description of the skills a student uses throughout the computing code they produce, the organization of these descriptions into themes, and a comparison of the emergent themes across students or across time.
Please join us!
Leigh Johnson