A Qualitative Study of Students' Computational Thinking Skills in a Data-Driven Computing Class

Critical thinking, problem solving, the use of tools, and the ability to consume and analyze information are important skills for the 21st century workforce. This article presents a qualitative case study that follows five undergraduate biology majors in a computer science course (CS0). This CS0 course teaches programming within a data-driven context and is part of a university-wide initiative to improve students' quantitative scholarship. In this course, students learn computing concepts and computational thinking by writing programs in MATLAB that compute with data, by performing meaningful analyses, and by writing about the results. The goal of the study reported here is to better understand the thought processes students use in such a data-driven approach. Findings show that students engage in an ongoing organizational process to understand the structure of the data. The computational and visualization tasks appear to be closely linked, and the visualization component appears to provide valuable feedback for students in accomplishing the programming tasks.