Assessing Computational Thinking Beyond Programming: A Scoping Review of Non‐Programming‐Based Computational Thinking Assessments for K‐12 Education.
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 vario...
| Publicado en: | Journal of Computer Assisted Learning Vol. 42; no. 1; pp. 1 - 31 |
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| Autores principales: | , , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Feb2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191181643&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191181643 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Feb2026 vid: 42 iid: 1 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 191181643 191181643 191181643 10.1002/jcal.70191 191181643 ppf: 1 ppct: 30 formats: tig: atl: Assessing Computational Thinking Beyond Programming: A Scoping Review of Non‐Programming‐Based Computational Thinking Assessments for K‐12 Education. aug: au: Wang, Chenyue Lu, Chang Chen, Fu Liu, Xueliang Wang, Qin affil: School of Education, Shanghai Jiao Tong University, Shanghai, China sug: subj: Computer-Assisted Instruction Algorithms Educational Measurement Problem Solving Sociodemographic Factors Students, College Human Male Female Scoping Review Databases, Health Descriptive Statistics Curriculum Educational Technology Learning Environment Funding Source Male Female ab: 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. Practitioner Notes: What is currently known about this topic? ○Computational thinking (CT) is a vital competence which is increasingly emphasised in K‐12 curricula and should be implemented across various educational contexts.○Assessments play a critical role in introducing CT in K‐12 education.○Many existing CT assessments are programming‐based, which may limit the applicability of CT in general domains and disadvantage students who lack programming experience or access to digital tools.○Programming‐based CT assessments may conflate CT with programming skills, obscuring that CT is essentially a problem‐solving competency.What does this paper add? ○This paper conducted a scoping review of non‐programming‐based CT assessments in K‐12 education, contributing to a clearer understanding of how non‐programming‐based CT assessments are implemented and used across contexts for various educational purposes.○This study summarised the landscapes, audiences, contexts, and measures of non‐programming‐based CT assessments to inform the selection or design of appropriate CT assessments.○This study examined the status quo of the field and identified future directions for non‐programming‐based CT assessment research.Implications for practice or policy ○Non‐programming‐based CT assessments in kindergarten, as well as in regions such as Africa, Western Asia, South America, and Oceania, require further research. When selecting or designing CT assessments, factors including students' grade, countries, and sample sizes should be carefully considered.○To evaluate the effectiveness of these CT interventions in informal educational settings, the development of non‐programming‐based CT assessments in informal educational contexts is necessary.○Future studies should leverage the advantages of online platforms to enhance the accessibility, interactivity, and scalability of non‐programming‐based CT assessments.○Most studies implemented CT assessments alongside, whereas few ensured alignment between the assessment tools and the specific intervention goals. Non‐programming‐based CT assessments could be integrated into more non‐STEM subjects and aligned with non‐programming‐based interventions.○Future research on non‐programming‐based CT assessments could adopt measures such as behaviour analysis, open‐ended questionnaires or interviews, and artefact or project analysis. For comprehensive assessments, a combination of various methods is recommended. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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