Review on teaching and learning of computational thinking through programming: What is next for K-12?
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The complex and abstract nature of coding often leads to a decline in motivation as students progress through their coursework.
“The complex and abstract nature of coding often leads to a decline in motivation as students’ progress through their coursework (Lye & Koh, 2014).”
Cites
Three Approaches to Qualitative Content Analysis
Hsieh, H.-F., & Shannon, S. E. (2005) · Qualitative Health Research · doi:10.1177/1049732305276687 · Cited by 44,601 · see citing works
THE ROLE OF TUTORING IN PROBLEM SOLVING <sup>*</sup>
Wood, D., Bruner, J. S., & Ross, G. (1976) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.1976.tb00381.x · Cited by 8,851 · cited 1× · see citing works
“Role of teacher in scaffolding process (Wood et al., 1976).”
Flagged first, then by citations
Cited by
Sorted by citations
Demystifying computational thinking
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017) · Educational Research Review · doi:10.1016/j.edurev.2017.09.003 · Cited by 1,466 · see citing works
Hsu, T.-C., Chang, S.-C., & Hung, Y.-T. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.07.004 · Cited by 788 · see citing works
Yilmaz, R., & Karaoglan Yilmaz, F. G. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100147 · Cited by 745 · see citing works
Assessing computational thinking: A systematic review of empirical studies
Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020) · Computers & Education · doi:10.1016/j.compedu.2019.103798 · Cited by 647 · see citing works
Big Data in Public Health: Terminology, Machine Learning, and Privacy
Mooney, S. J., & Pejaver, V. (2018) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040617-014208 · Cited by 325 · see citing works
Computational thinking and mathematics using Scratch: an experiment with sixth-grade students
Rodríguez-Martínez, J. A., González-Calero, J. A., & Sáez-López, J. M. (2020) · Interactive Learning Environments · doi:10.1080/10494820.2019.1612448 · Cited by 214 · see citing works
Noh, J., & Lee, J. (2020) · Educational Technology Research and Development · doi:10.1007/s11423-019-09708-w · Cited by 207 · see citing works
The cognitive benefits of learning computer programming: A meta-analysis of transfer effects.
Scherer, R., Siddiq, F., & Sánchez Viveros, B. (2019) · Journal of Educational Psychology · doi:10.1037/edu0000314 · Cited by 205 · see citing works
A systematic review of integrating computational thinking in early childhood education
Su, J., & Yang, W. (2023) · Computers and Education Open · doi:10.1016/j.caeo.2023.100122 · Cited by 174 · see citing works
From Gaming to Computational Thinking: An Adaptive Educational Computer Game-Based Learning Approach
Hooshyar, D., Pedaste, M., Yang, Y., Malva, L., Hwang, G.-J., Wang, M., Lim, H., & Delev, D. (2021) · Journal of Educational Computing Research · doi:10.1177/0735633120965919 · Cited by 132 · see citing works
Fan, G., Liu, D., Zhang, R., & Pan, L. (2025) · International Journal of STEM Education · doi:10.1186/s40594-025-00537-3 · Cited by 109 · see citing works
“The complex and abstract nature of coding often leads to a decline in motivation as students’ progress through their coursework (Lye & Koh, 2014).”
Yang, T.-C., Hsu, Y.-C., & Wu, J.-Y. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2450659 · Cited by 80 · see citing works
Hsu, T.-C., Abelson, H., & Van Brummelen, J. (2022) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v22i4.5474 · Cited by 65 · see citing works
Chen, L., Xiao, S., Chen, Y., Song, Y., Wu, R., & Sun, L. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642229 · Cited by 60 · see citing works
Sadik, O., Leftwich, A.-O., & Nadiruzzaman, H. (2017) · Emerging Research, Practice, and Policy on Computational Thinking · doi:10.1007/978-3-319-52691-1_14 · Cited by 40 · see citing works
Exploring AR and VR Tools in Mathematics Education Through Culturally Responsive Pedagogies
Bertrand, M. G., Sezer, H. B., & Namukasa, I. K. (2024) · Digital Experiences in Mathematics Education · doi:10.1007/s40751-024-00152-x · Cited by 28 · see citing works
Zhao, G., Yang, L., Hu, B., & Wang, J. (2025) · Journal of Educational Computing Research · doi:10.1177/07356331251336154 · Cited by 27 · see citing works
The wicked and the logical: Facilitating integrative learning among introductory computing students
Stone, J., & Cruz, L. (2021) · Teaching & Learning Inquiry · doi:10.20343/teachlearninqu.9.1.13 · Cited by 5 · see citing works
- Authors
- Lye, S. Y., & Koh, J. H. L.
- Affiliations
- Nanyang Technological University (SG)
- Corresponding author
- Lye, Sze Yee
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2014-12
- Volume
- 41
- Pages
- 51-61
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W1970953601
- Cited by
- 1,421
- References
- 2
- Citations by year
- 2026: 137 · 2025: 134 · 2024: 132 · 2023: 159 · 2022: 146 · 2021: 183 · 2020: 154 · 2019: 148 · 2018: 112 · 2017: 60 · 2016: 37 · 2015: 18
- FWCI
- 53.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers in Human Behavior (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- computational thinking, programming education, K-12 education, computational practice, computational concepts, abstraction, decomposition, think-aloud, constructionism, scaffolding, reflection, intervention research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review