Mapping the development of computational thinking in mathematics education: A bibliometric analysis

Year 2025, Volume: 6 Issue: 2, 105 - 123, 26.12.2025

Elfi Rahmadhani

Abstract

This study analyzes the development of research related to computational thinking (CT) skills, with a particular focus on their integration into mathematics education. As CT has become an essential competency in 21st-century learning, understanding the evolution of research in this field is crucial for informing educational practice and policy. To map patterns, dynamics, and research trends, a bibliometric analysis was conducted using 886 publications indexed in the Scopus database from 2003 to 2023. The analysis employed VOSviewer and Biblioshiny to examine publication growth, authorship networks, keyword co-occurrence, and thematic development. The findings indicate that studies on CT skills—especially in the context of mathematics learning—experienced a substantial upward trend over two decades, although a slight decline occurred in 2023. Calculus, algebra, and general mathematics learning emerged as the most frequently explored subject areas. Research dominance was observed at the basic education and higher education levels, with the United States and Spain identified as the most active contributors to the field. The results further highlight that integrating CT into mathematics instruction requires considerable time and careful instructional design. Therefore, selecting appropriate computational approaches, pedagogical strategies, and learning media is essential to ensure effective implementation. Overall, this study provides a comprehensive overview of global research trajectories in CT-based mathematics education and offers insights for researchers, educators, and policymakers seeking to strengthen the role of computational thinking in mathematics learning.

Keywords

bibliometrics , computational thinking , mathematics education , vosviewer

Ethical Statement

No ethics committee approval required.

Supporting Institution

No funding

References

• Abdul Hanid, M. F., Mohamad Said, M. N. H., Yahaya, N., & Abdullah, Z. (2022). Effects of augmented reality application integration with computational thinking in geometry topics. Education and Information Technologies, 27(7). Springer US. https://doi.org/10.1007/s10639-022-10994-w
• Abdullah, A. H., Othman, M. A., Ismail, N., Rahman, S. N. S. A., Mokhtar, M., & Zaid, N. M. (2019). Development of mobile application for the concept of pattern recognition in computational thinking for mathematics subject. In TALE 2019 – 2019 IEEE International Conference on Engineering, Technology and Education. IEEE. https://doi.org/10.1109/TALE48000.2019.9225910
• Akcaoglu, M. (2014). Learning problem-solving through making games at the game design and learning summer program. Educational Technology Research and Development, 62(5), 583–600. https://doi.org/10.1007/s11423-014-9347-4
• Andayani, A., Saputra, A. H., Irianto, E., & Setiawan, B. (2022). GESAMSU (Gedrik Saruk Memang Seru) based environmental: Effectiveness of games on mathematics communication ability of elementary school students. Al-Ishlah: Jurnal Pendidikan (Al-Ishlah: Journal of Education), 14(2), 2359–2368. https://doi.org/10.35445/alishlah.v14i2.1745
• Arroyo, I., Micciollo, M., Casano, J., Ottmar, E., Hulse, T., & Rodrigo, M. M. (2017). Wearable learning: Multiplayer embodied games for math. In CHI PLAY 2017 – Proceedings of the Annual Symposium on Computer-Human Interaction in Play (pp. 205–216). ACM. https://doi.org/10.1145/3116595.3116637
• 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), 3–19. https://doi.org/10.21585/ijcses.v5i4.138
• Bagley, S., & Rabin, J. M. (2016). Students’ use of computational thinking in linear algebra. International Journal of Research in Undergraduate Mathematics Education, 2(1), 83–104. https://doi.org/10.1007/s40753-015-0022-x
• Barcelos, T. S., Munoz, R., Villarroel, R., Merino, E., & Silveira, I. F. (2018). Mathematics learning through computational thinking activities: A systematic literature review. Journal of Universal Computer Science, 24(7), 815–845.
• Bayrak, A., & Aslanci, S. (2022). Realistic mathematics education: A bibliometric analysis. Shanlax International Journal of Education, 10(4), 52–62. https://doi.org/10.34293/education.v10i4.5174
• Benakli, N., Kostadinov, B., Satyanarayana, A., & Singh, S. (2017). Introducing computational thinking through hands-on projects using R with applications to calculus, probability and data analysis. International Journal of Mathematical Education in Science and Technology, 48(3), 393–427. https://doi.org/10.1080/0020739X.2016.1254296
• Benton, L., Saunders, P., Kalas, I., Hoyles, C., & Noss, R. (2018). Designing for learning mathematics through programming: A case study of pupils engaging with place value. International Journal of Child-Computer Interaction, 16, 68–76. https://doi.org/10.1016/j.ijcci.2017.12.004
• Bers, M. U., González-González, C., & Armas-Torres, M. B. (2019). Coding as a playground: Promoting positive learning experiences in childhood classrooms. Computers and Education, 138, 130–145. https://doi.org/10.1016/j.compedu.2019.04.013
• Bers, M. U. (2018). Coding and computational thinking in early childhood: The impact of ScratchJr in Europe. European Journal of STEM Education, 3(3). https://doi.org/10.20897/ejsteme/3868
• Bers, M. U., Strawhacker, A., & Sullivan, A. (2022). The state of the field of computational thinking in early childhood education. OECD Education Working Papers, 274, 1–62. https://doi.org/10.1787/3354387a-en
• Bocconi, S., Chioccariello, A., Dettori, G., Ferrari, A., & Engelhardt, K. (2016). Developing computational thinking in compulsory education: Implications for policy and practice. Joint Research Centre (JRC). https://doi.org/10.2791/792158
• Çakir, R., Rosaline, S., & Korkmaz, Ö. (2021). Computational thinking skills of Turkish and Indian teacher candidates: A comparative study. International Journal of Psychology and Educational Studies, 8(1), 24–37. https://doi.org/10.17220/ijpes.2021.8.1.226
• Calder, N. (2018). Using Scratch to facilitate mathematical thinking. Waikato Journal of Education, 23(2), 43–58. https://doi.org/10.15663/wje.v23i2.654
• Catlin, D., & Woollard, J. (2014). Educational robots and computational thinking. In Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics & 5th International Conference Robotics in Education (pp. 144–151).
• Chan, S. W., Looi, C. K., Ho, W. K., Huang, W., Seow, P., & Wu, L. (2021). Learning number patterns through computational thinking activities: A Rasch model analysis. Heliyon, 7(9), e07922. https://doi.org/10.1016/j.heliyon.2021.e07922
• Ching, Y. H., & Hsu, Y. C. (2023). Educational robotics for developing computational thinking in young learners: A systematic review. TechTrends. https://doi.org/10.1007/s11528-023-00841-1
• Clarke-Midura, J., Lee, V. R., Shumway, J. F., Silvis, D., Kozlowski, J. S., & Peterson, R. (2023). Designing formative assessments of early childhood computational thinking. Early Childhood Research Quarterly, 65, 68–80. https://doi.org/10.1016/j.ecresq.2023.05.013
• Clements, E. (2020). Investigating an approach to integrating computational thinking into an undergraduate calculus course. Electronic Thesis and Dissertation Repository. https://ir.lib.uwo.ca/etd/7043/
• Costabile, F. A., & Serpe, A. (2012). Computer-based mathematics instructions with MATCOS: A pedagogical experiment. In Handbook of Research on Didactic Strategies and Technologies for Education: Incorporating Advancements (Vol. 2, pp. 724–738). IGI Global. https://doi.org/10.4018/978-1-4666-2122-0.ch063
• Critten, V., Hagon, H., & Messer, D. (2022). Can pre-school children learn programming and coding through guided play activities? A case study in computational thinking. Early Childhood Education Journal, 50(6), 969– 981. https://doi.org/10.1007/s10643-021-01236-8
• Csizmadia, A., Curzon, P., Dorling, M., Humphreys, S., Ng, T., Selby, C., & Woollard, J. (2015). Computational thinking: A guide for teachers. Computing At School.
• Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
• Ersozlu, Z., Swartz, M., & Skourdoumbis, A. (2023). Developing computational thinking through mathematics: An evaluative scientific mapping. Education Sciences, 13(4). https://doi.org/10.3390/educsci13040422
• Fofang, J., Weintrop, D., Walton, M., Elby, A., & Walkoe, J. (2020). Mutually supportive mathematics and computational thinking in a fourth-grade classroom. In Computer-Supported Collaborative Learning Conference (CSCL) (Vol. 3, pp. 1389–1396).
• Frassia, M. G., & Serpe, A. (2018). Maths and programming project: Developing mathematical knowledge with programming in middle school. The Turkish Online Journal of Educational Technology, 2(November).
• Gadanidis, G., Cendros, R., Floyd, L., & Namukasa, I. (2017). Computational thinking in mathematics teacher education. Contemporary Issues in Technology & Teacher Education, 17(4), 458–477.
• Gadanidis, G., Scucuglia, R., Hughes, J. M., Floyd, S., & Namukasa, I. (2023). Computational literacy & mathematics education. International Journal for Research in Mathematics Education, 12(4), 1–23.
• Gerosa, A., Koleszar, V., Tejera, G., Gómez-Sena, L., & Carboni, A. (2021). Cognitive abilities and computational thinking at age 5: Evidence for associations to sequencing and symbolic number comparison. Computers and Education Open, 2, 100043. https://doi.org/10.1016/j.caeo.2021.100043
• Gong, D., Yang, H. H., & Cai, J. (2020). Exploring the key influencing factors on college students’ computational thinking skills through flipped-classroom instruction. International Journal of Educational Technology in Higher Education, 17(1), 1–13. https://doi.org/10.1186/s41239-020-00196-0
• Grover, S., & Pea, R. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher, 42(1), 38–43. https://doi.org/10.3102/0013189X12463051
• Harrison, A., Hulse, T., Manzo, D., Micciolo, M., Ottmar, E., & Arroyo, I. (2018). Computational thinking through game creation in STEM classrooms. In L. R., P.-P. K., du B. B., M. M., P. R. C., M. B., M.-M. R., & H. H. U. (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Vol. 10948 LNAI (pp. 134–138). Springer. https://doi.org/10.1007/978-3-319-93846-2_24
• Huang, W., Chan, S. W., & Looi, C. K. (2021). Frame shifting as a challenge to integrating computational thinking in secondary mathematics education. In SIGCSE 2021 – Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (pp. 390–396). ACM. https://doi.org/10.1145/3408877.3432400
• Isharyadi, R., & Juandi, D. (2023). A systematics literature review of computational thinking in mathematics education: Benefits and challenges. Formatif: Jurnal Ilmiah Pendidikan (Formatif: Scientific Journal of Education). https://journal.lppmunindra.ac.id/index.php/Formatif/article/view/15922
• Isnaini, R., Budiyanto, C., & Widiastuti, I. (2019). Robotics-based learning to support computational thinking skills in early childhood. In AIP Conference Proceedings, 2194. https://doi.org/10.1063/1.5139776
• Israel, M., & Lash, T. (2020). From classroom lessons to exploratory learning progressions: Mathematics + computational thinking. Interactive Learning Environments, 28(3), 362–382. https://doi.org/10.1080/10494820.2019.1674879
• Jeng, Y., Lai, C., Huang, S., Chiu, P., & Zhong, H. (2020). To cultivate creativity and a maker mindset through an Internet-of-Things programming course. Frontiers in Psychology, 11, 1572. https://doi.org/10.3389/fpsyg.2020.01572
• Kaup, C. F. (2022). Mapping the relations between computational thinking and mathematics in terms of problem-solving. Acta Didactica Norden, 16(4), 1–17. https://doi.org/10.5617/adno.9185
• Kaup, C. F., Pedersen, P. L., & Tvedebrink, T. (2023). Integrating computational thinking to enhance students’ mathematical understanding. Journal of Pedagogical Research, 7(2), 127–142. https://doi.org/10.33902/JPR.202318531
• Klunnikova, M. M., Bazhenova, I. V., Pak, N. I., & Kirgizova, E. V. (2020). Developing students’ computational thinking with a recursive polydisciplinary approach. Journal of Physics: Conference Series, 1691(1). https://doi.org/10.1088/1742-6596/1691/1/012190
• Korkmaz, Ö., Cakir, R., & Ozden, M. Y. (2017). Computational thinking scales. Computers in Human Behavior, 72, 558–569. https://doi.org/10.1002/9781118660584.ese0548
• Kukul, V., & Çakir, R. (2020). Exploring the development of primary school students’ computational thinking and 21st century skills through scaffolding: Voices from the stakeholders. International Journal of Computer Science Education in Schools, 4(2), 36–57. https://doi.org/10.21585/ijcses.v4i1.84
• Kukul, V., & Karataş, S. (2019). Computational thinking self-efficacy scale: Development, validity and reliability. Informatics in Education, 18(1), 151–164. https://doi.org/10.15388/infedu.2019.07
• Kusnendar, J., & Prabawa, H. W. (2018). Using NCLab-Karel to improve computational thinking skill of junior high school students. Journal of Physics: Conference Series, 1013(1). https://doi.org/10.1088/1742-6596/1013/1/012104
• Kusnendar, J., Prabawa, H. W., & Rahmanda. (2019). Bajo’s adventure: An effort to develop students’ computational thinking skills through mobile application. Journal of Physics: Conference Series, 1280(3). https://doi.org/10.1088/1742-6596/1280/3/032035
• Liao, C. H., Chiang, C. T., Chen, I. C., & Parker, K. R. (2022). Exploring the relationship between computational thinking and learning satisfaction for non-STEM college students. International Journal of Educational Technology in Higher Education, 19(1), 1–21. https://doi.org/10.1186/s41239-022-00347-5
• Lin, Y. S., Chen, S. Y., Tsai, C. W., & Lai, Y. H. (2021). Exploring computational thinking skills training through augmented reality and AIoT learning. Frontiers in Psychology, 12, 640115. https://doi.org/10.3389/fpsyg.2021.640115
• Lu, K., Yang, H. H., Shi, Y., & Wang, X. (2021). Examining the key influencing factors on college students’ higher- order thinking skills in the smart classroom environment. International Journal of Educational Technology in Higher Education, 18(1), 1–13. https://doi.org/10.1186/s41239-020-00238-7
• Massaty, M. H., Budiyanto, C. W., & Tamrin, A. G. (2020). Revisiting the roles of educational robotics in improving learners’ computational thinking skills and their positive behaviour. Journal of Physics: Conference Series, 1511(1). https://doi.org/10.1088/1742-6596/1511/1/012088
• Matere, I. M., Weng, C., Astatke, M., Hsia, C. H., & Fan, C. G. (2023). Effect of design-based learning on elementary students’ computational thinking skills in visual programming maker course. Interactive Learning Environments, 31(6), 3633–3646. https://doi.org/10.1080/10494820.2021.1938612
• Miller, J. (2019). STEM education in the primary years to support mathematical thinking: Using coding to identify mathematical structures and patterns. ZDM – Mathematics Education, 51(6), 915–927. https://doi.org/10.1007/s11858-019-01096-y
• Misirli, A., & Komis, V. (2023). Computational thinking in early childhood education: The impact of programming a tangible robot on developing debugging knowledge. Early Childhood Research Quarterly, 65, 139–158. https://doi.org/10.1016/j.ecresq.2023.05.014
• Møller, A. K., & Kaup, C. F. (2023). Parents’ and children’s learning when collaborating on inquiry-based mathematics and computational thinking tasks. Journal of Pedagogical Research, 7(2), 108–126. https://doi.org/10.33902/JPR.202319033
• Mouza, C., Yang, H., Pan, Y. C., Yilmaz Ozden, S., & Pollock, L. (2017). Resetting educational technology coursework for pre-service teachers: A computational thinking approach to the development of technological pedagogical content knowledge (TPACK). Australasian Journal of Educational Technology, 33(3), 61–76. https://doi.org/10.14742/ajet.3521
• Muñoz-Repiso, A. G. V., & Caballero-González, Y. A. (2019). Robotics to develop computational thinking in early childhood education. Comunicar, 27(59), 63–72. https://doi.org/10.3916/C59-2019-06
• Navarro, E. R., & de Sousa, M. do C. (2023). The concept of computational thinking in mathematics education. Journal of Mathematics and Science Teacher, 3(4). https://www.mathsciteacher.com/download/the-concept- of-computational-thinking-in-mathematics-education-13630.pdf
• Nobanee, H. (2021). A bibliometric review of big data in finance. Big Data, 9(2). https://doi.org/10.1089/big.2021.29044.edi
• Nordby, S. K., Bjerke, A. H., & Mifsud, L. (2022). Primary mathematics teachers’ understanding of computational thinking. KI – Künstliche Intelligenz, 36(1), 35–46. https://doi.org/10.1007/s13218-021-00750-6
• Öztürk, H. T., & Calingasan, L. (2018). Robotics in early childhood education. In Early Childhood Development (pp. 892–910). IGI Global. https://doi.org/10.4018/978-1-5225-7507-8.ch044
• Papadakis, S., Kalogiannakis, M., & Zaranis, N. (2021). Teaching mathematics with mobile devices and the realistic mathematical education (RME) approach in kindergarten. Advances in Mobile Learning Educational Research, 1(1), 5–18. https://doi.org/10.25082/amler.2021.01.002
• Papadakis, S. (2021). The impact of coding apps to support young children in computational thinking and computational fluency: A literature review. Frontiers in Education, 6, 657895. https://doi.org/10.3389/feduc.2021.657895
• Pei, C. (Yu), Weintrop, D., & Wilensky, U. (2018). Cultivating computational thinking practices and mathematical habits of mind in Lattice Land. Mathematical Thinking and Learning, 20(1), 75–89. https://doi.org/10.1080/10986065.2018.1403543
• Piedade, J. M. N. (2021). Pre-service and in-service teachers’ interest, knowledge, and self-confidence in using educational robotics in learning activities. Educ. Form., 6(1), e3345. https://doi.org/10.25053/redufor.v6i1.3345
• Pijls, H., & Quan, L. P. (2023). A computational method with Maple for finding the maximum curvature of a Bézier- spline curve. Mathematical and Computational Applications, 28(2). https://doi.org/10.3390/mca28020056
• Pörn, R., Hemmi, K., & Kallio-Kujala, P. (2021). Inspiring or confusing – A study of Finnish 1–6 teachers’ relation to teaching programming. LUMAT: International Journal on Math, Science and Technology Education, 9(1), 366– 396. https://doi.org/10.31129/LUMAT.9.1.1355
• Pujiastuti, H., & Haryadi, R. (2023). Higher-order thinking skills profile of Islamic boarding school students on geometry through the STEM-based video approach. International Journal of STEM Education for Sustainability, 3(1), 156–174.
• Quan, L. P. (2018). A computational method with Maple for a piecewise polynomial approximation to the trigonometric functions. Mathematical and Computational Applications, 23(4), 63. https://doi.org/10.3390/mca23040063
• Rafiepour, A., & Farsani, D. (2021). Cultural historical analysis of Iranian school mathematics curriculum: The role of computational thinking. Journal on Mathematics Education, 12(3), 411–426. https://doi.org/10.22342/JME.12.3.14296.411-426
• Relkin, E., & Bers, M. (2021). TechCheck-K: A measure of computational thinking for kindergarten children. In IEEE Global Engineering Education Conference (EDUCON) (pp. 1696–1702). IEEE. https://doi.org/10.1109/EDUCON46332.2021.9453926
• Reskianissa, A., Wibawa Sakti, A., & Azizah, N. N. (2022). TikTok platform to train middle school students’ computational thinking skills in distance learning. Indonesian Journal of Educational Research and Technology, 1(1), 79–86.
• Rich, K. M., Yadav, A., & Fessler, C. J. (2022). Computational thinking practices as tools for creating high cognitive demand mathematics instruction. Journal of Mathematics Teacher Education. https://doi.org/10.1007/s10857- 022-09562-3
• Rich, P. J., Mason, S. L., & O’Leary, J. (2021). Measuring the effect of continuous professional development on elementary teachers’ self-efficacy to teach coding and computational thinking. Computers and Education, 168, 104196. https://doi.org/10.1016/j.compedu.2021.104196
• Rodríguez-Martínez, J. A., & Saez-Lopez, J.-M. (2020). Computational thinking and mathematics using Scratch: An experiment with sixth-grade students. Interactive Learning Environments, 28(3), 316–327. https://doi.org/10.1080/10494820.2019.1612448
• Sáez-López, J. M., Sevillano-García, M. L., & Vazquez-Cano, E. (2019). The effect of programming on primary school students’ mathematical and scientific understanding: Educational use of mBot. Educational Technology Research and Development, 67(6), 1405–1425. https://doi.org/10.1007/s11423-019-09648-5
• Sala-Sebastià, G., Breda, A., Seckel, M. J., Farsani, D., & Alsina, À. (2023). Didactic–mathematical–computational knowledge of future teachers when solving and designing robotics problems. Axioms, 12(2), 1–24. https://doi.org/10.3390/axioms12020119
• Sanford, J. (2018). Introducing computational thinking through spreadsheets. In Computational Thinking in the STEM Disciplines: Foundations and Research Highlights (pp. 99–124). Springer. https://doi.org/10.1007/978-3- 319-93566-9_6
• Saritepeci, M. (2022). Modelling the effect of TPACK and computational thinking on classroom management in technology enriched courses. Technology, Knowledge and Learning, 27(4), 1155–1169. https://doi.org/10.1007/s10758-021-09529-y
• Seckel, M. J., Breda, A., Farsani, D., & Parra, J. (2022). Reflections of future kindergarten teachers on the design of a mathematical instruction process didactic sequences with the use of robots. EURASIA Journal of Mathematics, Science and Technology Education, 18(10). https://doi.org/10.29333/ejmste/12442
• Semirhan Gökçe, P. G. (2021). Forty years of mathematics education: 1980–2019. International Journal of Education in Mathematics, Science and Technology, 9(3), 514–539.
• Sinclair, N. (2018). The dynamic geometrisation of computer programming. Mathematical Thinking and Learning, 20(1), 54–74. https://doi.org/10.1080/10986065.2018.1403541
• Smith, H., Closser, A. H., Ottmar, E., & Arroyo, I. (2020). Developing math knowledge and computational thinking through game play and design: A professional development program. Contemporary Issues in Technology and Teacher Education, 20(4), 660–686.
• Sondakh, D. E., Osman, K., & Zainudin, S. (2020). A pilot study of an instrument to assess undergraduates’ computational thinking proficiency. International Journal of Advanced Computer Science and Applications, 11(11), 263–273. https://doi.org/10.14569/IJACSA.2020.0111134
• Subramaniam, S., Maat, S. M., & Mahmud, M. S. (2022). Computational thinking in mathematics education: A systematic review. Cypriot Journal of Educational Sciences, 17(6), 2029–2044.
• Sung, W., Ahn, J., & Black, J. B. (2017). Introducing computational thinking to young learners: Practicing computational perspectives through embodiment in mathematics education. Educational Researcher, 22, 443–463. https://doi.org/10.1007/s10758-017-9328-x
• Tsortanidou, X., Daradoumis, T., & Barberá, E. (2019). Connecting moments of creativity, computational thinking, collaboration and new media literacy skills. Information and Learning Science, 120(11–12), 704–722. https://doi.org/10.1108/ILS-05-2019-0042
• Van Borkulo, S., Chytas, C., Drijvers, P., Barendsen, E., & Tolboom, J. (2021). Computational thinking in the mathematics classroom: Fostering algorithmic thinking and generalization skills using dynamic mathematics software. In ACM International Conference Proceeding Series. ACM. https://doi.org/10.1145/3481312.3481319
• Vanhala, M., Lu, C., Peltonen, J., Sundqvist, S., Nummenmaa, J., & Järvelin, K. (2020). The usage of large data sets in online consumer behaviour: A bibliometric and computational text-mining–driven analysis of previous research. Journal of Business Research, 106, 46–59. https://doi.org/10.1016/j.jbusres.2019.09.009
• Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25(1), 127–147. https://doi.org/10.1007/s10956-015-9581-5
• Welch, L. E., Shumway, J. F., Clarke-Midura, J., & Lee, V. R. (2022). Exploring measurement through coding: Children’s conceptions of a dynamic linear unit with robot coding toys. Education Sciences, 12(2). https://doi.org/10.3390/educsci12020143
• Wilensky, U., Brady, C. E., & Horn, M. S. (2014). Fostering computational literacy in science classrooms. Communications of the ACM, 57(8), 24–28. https://doi.org/10.1145/2633031
• Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215