Result: Discovering Computational Thinking in Everyday Problem Solving: A Multiple Case Study of Route Planning

Title:
Discovering Computational Thinking in Everyday Problem Solving: A Multiple Case Study of Route Planning
Language:
English
Authors:
Ezeamuzie, Ndudi O. (ORCID 0000-0001-8946-5709), Leung, Jessica S. C. (ORCID 0000-0002-6299-8158), Garcia, Raycelle C. C. (ORCID 0000-0001-9400-6566), Ting, Fridolin S. T. (ORCID 0000-0001-7432-0187)
Source:
Journal of Computer Assisted Learning. Dec 2022 38(6):1779-1796.
Availability:
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed:
Y
Page Count:
18
Publication Date:
2022
Document Type:
Academic journal Journal Articles<br />Reports - Research
DOI:
10.1111/jcal.12720
ISSN:
0266-4909
1365-2729
Entry Date:
2022
Accession Number:
EJ1356800
Database:
ERIC

Further Information

Background: The idea of computational thinking is underpinned by the belief that anyone can learn and use the underlying concepts of computer science to solve everyday problems. However, most studies on the topic have investigated the development of computational thinking through programming activities, which are cognitively demanding. There is a dearth of evidence on how computational thinking augments everyday problem solving when it is decontextualized from programming. Objectives: In this study, we examined how computational thinking, when untangled from the haze of programming, is demonstrated in everyday problem solving, and investigated the features of such solvable problems. Methods: Using a multiple case study approach, we tracked how seven university students used computational thinking to solve the everyday problem of a route planning task as part of an 8-week-long Python programming course. Results and Conclusions: Computational thinking practices are latent in everyday problems, and intentionally structuring everyday problems is valuable for discovering the applicability of computational thinking. Decomposition and abstraction are prominent computational thinking components used to simplify everyday problem solving. Implications: It is important to strike a balance between the correctness of algorithms and simplification of the process of everyday problem solving.

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