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Assessing Computational Thinking beyond Programming: A Scoping Review of Non-Programming-Based Computational Thinking Assessments for K-12 Education

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Title: Assessing Computational Thinking beyond Programming: A Scoping Review of Non-Programming-Based Computational Thinking Assessments for K-12 Education
Language: English
Authors: Chenyue Wang, Chang Lu, Fu Chen, Xueliang Liu, Qin Wang
Source: Journal of Computer Assisted Learning. 2026 42(1).
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: 30
Publication Date: 2026
Document Type: Journal Articles
Information Analyses
Education Level: Elementary Secondary Education
Descriptors: Computation, Thinking Skills, Programming, Elementary Secondary Education, Evaluation Methods, Educational Research
DOI: 10.1002/jcal.70191
ISSN: 0266-4909
1365-2729
Abstract: Background: Computational thinking (CT) is an essential 21st-century competency, which has already been embedded into K-12 education globally and is regarded as a fundamental competency that applies to multiple domains. It is important to adopt non-programming-based instruments to assess CT in various domains, but few studies systematically examine non-programming-based CT assessments. Objective: This study aims to conduct a scoping review of non-programming-based CT assessments to provide guidance for future research on CT assessments. The summary of non-programming-based CT assessments could reveal their state and gaps, and provide insights for choosing, implementing, or developing appropriate CT assessments. Method: Following a scoping review approach, this study examined 39 empirical studies published on journal articles between 2006 and 2022. The landscapes, audiences, contexts, and measures of non-programming-based CT assessments are summarised and discussed. Results and Conclusions: Non-programming-based CT assessments have covered all K-12 grade levels except for kindergarten, with most studies conducted in China and the United States of America. However, research is limited in Africa, Western Asia, South America, and Oceania. Most reviewed studies were conducted in formal education settings using online platforms and were integrated into various subjects--primarily STEM-related. While many assessments were conducted together with interventions, most of these were programming-related, and corresponding assessments were often misaligned. Problem-test method and self-reported scales were the most frequently used measures. Moreover, single-assessment tools were more commonly adopted than multi-method assessment tools. Future research could focus on informal education settings, leverage online assessments, implement CT assessments in non-STEM subjects, and develop effective non-programming-based CT interventions and aligned assessments.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1495848
Database: ERIC
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  Data: Assessing Computational Thinking beyond Programming: A Scoping Review of Non-Programming-Based Computational Thinking Assessments for K-12 Education
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  Data: <searchLink fieldCode="AR" term="%22Chenyue+Wang%22">Chenyue Wang</searchLink><br /><searchLink fieldCode="AR" term="%22Chang+Lu%22">Chang Lu</searchLink><br /><searchLink fieldCode="AR" term="%22Fu+Chen%22">Fu Chen</searchLink><br /><searchLink fieldCode="AR" term="%22Xueliang+Liu%22">Xueliang Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Qin+Wang%22">Qin Wang</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Computer+Assisted+Learning%22"><i>Journal of Computer Assisted Learning</i></searchLink>. 2026 42(1).
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  Data: 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
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  Data: 30
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  Data: Journal Articles<br />Information Analyses
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  Data: <searchLink fieldCode="EL" term="%22Elementary+Secondary+Education%22">Elementary Secondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Computation%22">Computation</searchLink><br /><searchLink fieldCode="DE" term="%22Thinking+Skills%22">Thinking Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Programming%22">Programming</searchLink><br /><searchLink fieldCode="DE" term="%22Elementary+Secondary+Education%22">Elementary Secondary Education</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+Methods%22">Evaluation Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Research%22">Educational Research</searchLink>
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  Data: 10.1002/jcal.70191
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  Label: Abstract
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  Data: Background: Computational thinking (CT) is an essential 21st-century competency, which has already been embedded into K-12 education globally and is regarded as a fundamental competency that applies to multiple domains. It is important to adopt non-programming-based instruments to assess CT in various domains, but few studies systematically examine non-programming-based CT assessments. Objective: This study aims to conduct a scoping review of non-programming-based CT assessments to provide guidance for future research on CT assessments. The summary of non-programming-based CT assessments could reveal their state and gaps, and provide insights for choosing, implementing, or developing appropriate CT assessments. Method: Following a scoping review approach, this study examined 39 empirical studies published on journal articles between 2006 and 2022. The landscapes, audiences, contexts, and measures of non-programming-based CT assessments are summarised and discussed. Results and Conclusions: Non-programming-based CT assessments have covered all K-12 grade levels except for kindergarten, with most studies conducted in China and the United States of America. However, research is limited in Africa, Western Asia, South America, and Oceania. Most reviewed studies were conducted in formal education settings using online platforms and were integrated into various subjects--primarily STEM-related. While many assessments were conducted together with interventions, most of these were programming-related, and corresponding assessments were often misaligned. Problem-test method and self-reported scales were the most frequently used measures. Moreover, single-assessment tools were more commonly adopted than multi-method assessment tools. Future research could focus on informal education settings, leverage online assessments, implement CT assessments in non-STEM subjects, and develop effective non-programming-based CT interventions and aligned assessments.
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