Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

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

A Qualitative Study of Students' Computational Thinking Skills in a Data-Driven Computing Class A Qualitative Study of Students' Computational Thinking Skills in a Data-Driven Computing Class TIMOTHY T. YUEN and KAY A. ROBBINS, University of Texas at San Antonio 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. Categories and Subject Descriptors: [Social and Professional Topics]: Computing Education General Terms: Computational Thinking, Computer http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Computing Education (TOCE) Association for Computing Machinery

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

Loading next page...
 
/lp/association-for-computing-machinery/a-qualitative-study-of-students-computational-thinking-skills-in-a-NA2PpAsJaQ
Publisher
Association for Computing Machinery
Copyright
Copyright © 2014 by ACM Inc.
ISSN
1946-6226
DOI
10.1145/2676660
Publisher site
See Article on Publisher Site

Abstract

A Qualitative Study of Students' Computational Thinking Skills in a Data-Driven Computing Class TIMOTHY T. YUEN and KAY A. ROBBINS, University of Texas at San Antonio 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. Categories and Subject Descriptors: [Social and Professional Topics]: Computing Education General Terms: Computational Thinking, Computer

Journal

ACM Transactions on Computing Education (TOCE)Association for Computing Machinery

Published: Dec 12, 2014

There are no references for this article.