Computational Thinking Assessment in Primary and Secondary Education: A Meta-synthesis of tools, Methods and Pedagogical Approaches
Keywords:
Assessment, Computational Thinking, Review of reviews, Meta-synthesisAbstract
Despite the widespread adoption of computational thinking (CT) across educational levels, challenges persist in its assessment due to diverse definitions, frameworks, and its practical application in classroom settings. This meta-synthesis investigates the assessment of computational thinking (CT) in primary and secondary education, synthesizing evidence from 12 reviews across five international databases, focusing on tools, methods, and pedagogical practices employed in assessing CT, with the aim to outline practical approaches for evaluating CT components. The review delves into the primary focuses of these syntheses, the CT skills and components assessed, and the methods and tools utilized, identifying gaps in current practices. The findings highlight a prevalent focus on programming skills, with less emphasis on cognitive processes and collaborative aspects of CT. The synthesis also points to the need for developing assessment tools and methods that encompass the broader spectrum of CT skills, suggesting avenues for future research and practical application in educational settings.
Downloads
References
* Araujo, A. L. S. O. de, Andrade, W. L., & Guerrero, D. D. S. (2016). A systematic mapping study on assessing computational thinking abilities. https://doi.org/10.1109/FIE.2016.7757419 DOI: https://doi.org/10.1109/FIE.2016.7757678
* Babazadeh, M., & Negrini, L. (2022). How is computational thinking assessed in European K-12 education? A systematic review. International Journal of Computer Science Education in Schools, 5(4). https://doi.org/10.21585/ijcses.v5i4.138 DOI: https://doi.org/10.21585/ijcses.v5i4.138
Balanskat, A., & Engelhardt, K. (2015). Computing our future: Computer programming and coding - priorities, school curricula and initiatives across Europe. Brussel European Schoolnet.
Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Chong, S. W., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics collaboration and rigour. International Journal of Educational Technology in Higher Education, 21(4). https://doi.org/10.1186/s41239-023-00436-z
Booth, A., Sutton A., Clowes, M., Martyn-St James, M. (2022). Systematic Approaches to a Successful Literature Review. SAGE
Buntins, K., Bedenlier, S., Marín, V., Händel, M., & Bond, M. (2023). Methodological approaches to evidence synthesis in educational technology: A tertiary systematic mapping review. MedienPädagogik, 54, 167–191. https://doi.org/10. 21240/mpaed/54/2023.12.20.X
* da Cruz Alves, N., Gresse von Wangenheim, C., & Hauck, J. C. R. (2019). Approaches to Assess Computational Thinking Competences Based on Code Analysis in K-12 Education: A Systematic Mapping Study. Informatics in Education, 18(1), 17-39. https://doi.org/10.15388/infedu.2019.02
* Fagerlund, J., Häkkinen, P., Vesisenaho, M., & Viiri, J. (2021). Computational thinking in programming with Scratch in primary schools: A systematic review. Computer Applications in Engineering Education, 29(1), 12–28. https://doi.org/10.1002/cae.22255
González-Pérez, L. I. & Ramírez-Montoya, M, S. (2022). Components of Education 4.0 in 21st Century Skills Frameworks: Systematic Review. Sustainability 14 (3). https://doi.org/10.3390/su14031493
* Haseski, H. İ., & Ilic, U. (2019). An Investigation of the Data Collection Instruments Developed to Measure Computational Thinking. Informatics in Education, 18(2), 297–319. https://doi.org/10.15388/infedu.2019.14
Higgins, S., Xiao, Z., & Katsipataki, M. (2012). The impact of digital technology on learning: A summary for the Education Endowment Foundation. Education Endowment Foundation. https://eric.ed.gov/?id=ED612174
Kitchenham, B., Pearl Brereton, O., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009). Systematic literature reviews in software engineering—A systematic literature review. Information and Software Technology, 51(1), 7–15. https://doi.org/10.1016/j.infsof.2008.09.009 DOI: https://doi.org/10.1016/j.infsof.2008.09.009
* Liu, R., Luo, F., & Israel, M. (2021). What Do We Know about Assessing Computational Thinking? A New Methodological Perspective from the Literature. In Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2021), June 26-July 1, Virtual Event, Germany. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3430665.3456380
Lodi, M. (2020). Informatical Thinking. Olympiads in Informatics, 14, 113–132. https://doi.org/10.15388/ioi.2020.09
Lodi, M., & Martini, S. (2021). Computational thinking between Papert and Wing. Science & Education, 30, 883–908. https://doi.org/10.1007/s11191-021-00202-5
* Muñoz, R. F. Z., Hurtado Alegría, J. A., & Robles, G. (2023). Assessment of Computational Thinking Skills: A Systematic Review of the Literature. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 18(4), 319-330. https://doi.org/10.1109/RITA.2023.3323762
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hofmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaf, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ (clinical Research Ed.), 372, n71. https://doi.org/10.1136/bmj.n71
* Pan, Z., Cui, Y., Leighton, J. P., & Cutumisu, M. (2023). Insights into computational thinking from think-aloud interviews: A systematic review. Applied Cognitive Psychology, 37(1), 71–95. https://doi.org/10.1002/acp.4029
Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Badic Books, Inc.
Priem, J., Piwowar, H., & Orr, R. (2022). OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts. ArXiv. https://arxiv.org/abs/2205.01833
Sutton, A., Clowes, M., Preston, L., & Booth, A. (2019). Meeting the review family: Exploring review types and associated information retrieval requirements. Health Information and Libraries Journal, 36(3), 202–222. https://doi.org/10. 1111/hir.12276
* Tan, B., Jin, H.-Y., & Cutumisu, M. (2023). The applications of machine learning in computational thinking assessments: A scoping review. Computer Science Education. https://doi.org/10.1080/08993408.2023.2245687
* Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148, 103798. https://doi.org/10.1016/j.compedu.2019.103798
Thomas, J., Graziosi, S., Brunton, J., Ghouze, Z., O’Driscoll, P., Bond, M., & Koryakina, A. (2023). EPPI Reviewer: Advanced software for systematic reviews, maps and evidence synthesis [Computer software]. EPPI Centre Software. UCL Social Research Institute. London. https://eppi.ioe.ac.uk/cms/Default.aspx?alias=eppi.ioe.ac.uk/cms/er4
* Tikva, C., & Tambouris, E. (2021). Mapping computational thinking through programming in K-12 education: A conceptual model based on a systematic literature review. Computers & Education, 162, 104083. https://doi.org/10.1016/j.compedu.2020.104083
Varghese, V. V., & Renumol, V. G. (2023). Video games for assessing computational thinking: A systematic literature review. Journal of Computers in Education. https://doi.org/10.1007/s40692-023-00284-w
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. DOI: https://doi.org/10.1145/1118178.1118215
Ye, J., Lai, X., & Wong, G. K. W. (2022). The transfer effects of computational thinking: A systematic review with meta‐analysis and qualitative synthesis. Journal of Computer Assisted Learning, 38(6), 1620–1638. https://doi.org/10.1111/jcal.12723
Published
How to Cite
Issue
Section
Copyright (c) 2024 Sanna Forsström, Melissa Bond
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
