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

Autor/inn/en	Yuen, Timothy T.; Robbins, Kay A.
Titel	A Qualitative Study of Students' Computational Thinking Skills in a Data-Driven Computing Class
Quelle	In: ACM Transactions on Computing Education, 14 (2014) 4, Artikel 27 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1946-6226
DOI	10.1145/2676660
Schlagwörter	Qualitative Research; Critical Thinking; Thinking Skills; Problem Solving; Computation; Computer Science Education; Undergraduate Students; Biology; Programming; Data Analysis; Cognitive Processes; Visualization; Majors (Students); Skill Development; Pretests Posttests; Interviews; Coding; Organization; Texas + Suchen Sie Ihr Suchwort? Qualitative Forschung; Kritisches Denken; Denkfähigkeit; Problemlösen; Computer science lessons; Informatikunterricht; Biologie; Programmierung; Auswertung; Cognitive process; Kognitiver Prozess; Visualisation; Visualisierung; Kompetenzentwicklung; Qualifikationsentwicklung; Interviewing; Interviewtechnik; Codierung; Organisation; Organisationsstruktur
Abstract	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. (As Provided).
Anmerkungen	Association for Computing Machinery. 2 Penn Plaza Suite 701, New York, NY 10121. Tel: 800-342-6626; Tel: 212-626-0500; Fax: 212-944-1318; e-mail: acmhelp@acm.org; Web site: http://toce.acm.org/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01