Computational Thinking in Teacher Education: A Systematic Review of Integration Strategies
- Authors
-
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Dr. Selira M. Tavenbrook
Faculty of Education, University of Helsinki, FinlandAuthor -
Dr. Jornic L. Redwythe
School of Education, University of British Columbia, Vancouver, CanadaAuthor
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- Keywords:
- Computational thinking, teacher education, systematic review, pre-service teachers
- Abstract
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Computational thinking (CT) is increasingly recognized as a vital 21st-century skill, necessitating its integration into K-12 education and, consequently, into teacher preparation. This systematic literature review synthesizes existing research on strategies for integrating CT into both pre-service and in-service teacher education programs. Employing a systematic review methodology with thematic synthesis, this study analyzed a diverse range of 43 empirical articles published between January 2010 and June 2024. The findings reveal various effective approaches, including direct instruction, programming-based activities (block-based and text-based), robotics and physical computing, unplugged activities, integrated STEM frameworks, and project-based learning. Interventions consistently demonstrated positive outcomes, enhancing teachers' personal CT skills, developing their pedagogical content knowledge (PCK) for CT, and improving their attitudes and self-efficacy toward teaching CT. The review also identifies common assessment methods, challenges such as lack of familiarity and time constraints, and facilitators like hands-on engagement and curriculum connections. This study provides important and evidence-based insights for researchers in teacher education and development so that they can design more effective teaching strategies in integrating CT into in-service and pre-service teacher education. This review offers significant implications for curriculum redesign in teacher education, emphasizing experiential learning, PCK development, and continuous professional development to foster a computationally literate teaching workforce. Future research should focus on longitudinal studies, the direct impact on student learning, and exploration across diverse subject areas and global contexts.
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- References
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1. Abouelenein, Y. A. M., & Nagy Elmaadaway, M. A. (2023). Impact of teaching a neuro-computerized course through VLE to develop computational thinking among mathematics pre-service teachers. Journal of Educational Computing Research, 61(6), 1175–1206. https://doi.org/10.1177/07356331231165099
2. Adler, R. F., & Kim, H. (2018). Enhancing future K-8 teachers’ computational thinking skills through modeling and simulations. Education and Information Technologies, 23(4), 1501–1514. https://doi.org/10.1007/s10639-017-9675-1
3. Aminah, N., Sukestiyarno, Y. L., Wardono, W., & Cahyono, A. N. (2022). Computational thinking process of prospective mathematics teacher in solving diophantine linear equation problems. European Journal of Educational Research, 11(3), 1495–1507. https://doi.org/10.12973/eu-jer.11.3.1495
4. Angeli, C. (2022). The effects of scaffolded programming scripts on pre-service teachers’ computational thinking: developing algorithmic thinking through programming robots. International Journal of Child-Computer Interaction, 31, 1–20. https://doi.org/10.1016/j.ijcci.2021.100329
5. Aristiz´abal Zapata, J. H., Guti´errez Posada, J. E., & Diago, P. D (2024). Design and validation of a computational thinking test for children in the first grades of elementary education. Multimodal Technologies and Interaction, 8(5), 39. https://doi.org/10.3390/mti8050039
6. Atmaja, J. F. T., Sari, M. W., & Ciptadi, P. W. (2021). Developing application of automatic lamp control and monitoring system using internet of things. Journal of Physics: Conference Series, 1823(1), Article 012002. https://doi.org/10.1088/1742-6596/1823/1/012002
7. Bai, H., Bosch, C., Goosen, L., & Chetty, J. (2024). Introducing computational thinking and coding to teacher education students. Navigating computer science education in the 21st century (pp. 170–186). IGI Global. https://doi.org/10.4018/979-8-3693-1066-3.ch009
8. Bal, I. A., Alvarado–Albertorio, F., Marcelle, P., & Oaks–Garcia, C. T (2022). Pre–service teachers computational thinking (CT) and pedagogical growth in a micro–credential: a mixed methods study. TechTrends, 66(3), 468–482. https://doi.org/10.1007/s11528-022-00732-x
9. Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: what is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48–54. https://doi.org/10.1145/1929887.1929905
10. Bati, K. (2022). Integration of python into science teacher education, developing computational problem solving and using information and communication technologies competencies of pre-service science teachers. Informatics In Education, 21(2), 235–251. https://doi.org/10.15388/infedu.2022.12
11. Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Proceedings of the American Educational Research Association (AERA). Vancouver, Canada.
12. Budiyanto, C. W., Fenyvesi, K., Lathifah, A., & Yuana, R. A. (2022). Computational thinking development: benefiting from educational robotics in stem teaching. European Journal of Educational Research, 11(4), 1997–2012. https://doi.org/10.12973/eu-jer.11.4.1997
13. Çakiroglu, Ü., & Kiliç, S. (2023). Assessing teachers’ PCK to teach computational thinking via robotic programming. Interactive Learning Environments, 31(2), 818–835. https://doi.org/10.1080/10494820.2020.1811734
14. Chen, G., Shen, J., Barth-Cohen, L., Jiang, S., Huang, X., & Eltoukhy, M. (2017). Assessing elementary students’ computational thinking in everyday reasoning and robotics programming. Computers & Education, 109, 162–175. https://doi.org/10.1016/j.compedu.2017.03.001
15. Çiftçi, A., & Topçu, M. (2023). Improving early childhood pre-service teachers’ computational thinking skills through the unplugged computational thinking integrated STEM approach. Thinking Skills and Creativity, 49, 1–14. https://doi.org/10.1016/j.tsc.2023.101337
16. Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education (8th ed.). Routledge.
17. Cooper, H. (2017). Research synthesis and meta-analysis. SAGE Publications, Inc. https://doi.org/10.4135/9781071878644
18. Czerkawski, B.C., Lyman, E.W. (2015) Exploring issues about computational thinking in higher education. TechTrends, 59, 57–65. https://doi.org/10.1007/s11528-015-0840-3.
19. Daungjun, S. (2018). Effects of using stem education in physics on computational thinking ability of upper secondary school students. Bangkok: Chulalongkorn University.
20. de Jong, I., & Jeuring, J. (2020). Computational thinking interventions in higher education: A scoping literature review of interventions used to teach computational thinking. In Proceedings of the 20th Koli Calling International Conference on Computing Education Research (pp. 1–10). ACM. https://doi.org/10.1145/3428029.3428055.
21. Demchuk, E., Ruiz, P., Wilson, J. D., Scinicariello, F., Pohl, H. R., Fay, M., Mumtaz, M. M., Hansen, H., & De Rosa, C. T. (2008). Computational toxicology methods in public health practice. Toxicology Mechanisms and Methods, 18(2–3), 119–135. https://doi.org/10.1080/15376510701857148
22. El-Hamamsy, L., Chessel-Lazzarotto, F., Bruno, B., Roy, D., Cahlikova, T., Chevalier, M., Parriaux, G., Pellet, J., Lanar`es, J., Zufferey, J., & Mondada, F. (2021). A computer science and robotics integration model for primary school: evaluation of a large-scale in-service K-4 teacher-training program. Education and Information Technologies, 26(3), 2445–2475. https://doi.org/10.1007/s10639-020-10355-5
23. Fessakis, G., & Prantsoudi, S. (2019). Computer science teachers’ perceptions, beliefs and attitudes on computational thinking in Greece. Informatics in Education, 18(2), 227–258. https://doi.org/10.15388/infedu.2019.11
24. Gabriele, L., Bertacchini, F., Tavernise, A., Vaca-Cardenas, ´ L., Pantano, P., & Bilotta, E. (2019). Lesson planning by computational thinking skills in Italian pre-service teachers. Informatics In Education, 18(1), 69–104. https://doi.org/10.15388/infedu.2019.04
25. Gandotra, E., Bansal, D., & Sofat, S. (2015). Computational techniques for predicting cyber threats. In S. C. Satapathy, B. Mandal, & R. R. Mohanty (Eds.), Intelligent computing, communication and devices (pp. 247–253). Springer. https://doi.org/10.1007/978-81-322-2012-1_26.
26. 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
27. Haslaman, T., Mumcu, F., & Uslu, N. (2024). Fostering computational thinking through digital storytelling: A distinctive approach to promoting computational thinking skills of pre-service teachers. Education And Information Technologies, 29(14), 18121–18147. https://doi.org/10.1007/s10639-024-12583-5
28. Helsa, Y., & Juandi, D. (2023). TPACK-based hybrid learning model design for computational thinking skills achievement in mathematics. Journal on Mathematics Education, 14(2), 225–252. https://doi.org/10.22342/jme.v14i2.pp225-252
29. Hickmott, D., Prieto-Rodriguez, E., & Holmes, K. (2018). A scoping review of studies on computational thinking in K–12 mathematics classrooms. Digital Experiences in Mathematics Education, 4(1), 48–69. https://doi.org/10.1007/s40751-017-0038-8
30. Hunsaker, E., & West, R. E. (2020). Designing computational thinking and coding badges for early childhood educators. TechTrends, 64(1), 7–16. https://doi.org/10.1007/s11528-019-00420-3
31. ISTE. (2011). Computational thinking. https://iste.org/computational-thinking.
32. Jaipal-Jamani, K., & Angeli, C. (2017). Effect of robotics on elementary preservice teachers’ self-efficacy, science learning, and computational thinking. Journal of Science Education and Technology, 26(2), 175–192. https://doi.org/10.1007/s10956-016-9663-z
33. Kakavas, P., & Ugolini, F. C. (2019). Computational thinking in primary education: A systematic literature review. Research on Education and Media, 11(2), 64–94. https://doi.org/10.2478/rem-2019-0023
34. Kampylis, P., Dagiene, ˙ V., Bocconi, S., Chioccariello, A., Engelhardt, K., Stupuriene, ˙ G., & Earp, J. (2023). Integrating computational thinking into primary and lower secondary education. Educational Technology & Society, 26(2), 99–117. [suspicious link removed].
35. Keen, B., Blaszczynski, A., & Anjoul, F. (2017). Systematic review of empirically evaluated school-based gambling education programs. Journal of Gambling Studies, 33(1), 301–325. https://doi.org/10.1007/s10899-016-9641-7
36. Kilic, S., & Çakiroglu, Ü. (2023). Design, implementation, and evaluation of a professional development program for teachers to teach computational thinking via robotics. Technology Knowledge And Learning, 28(4), 1539–1569. https://doi.org/10.1007/s10758-022-09629-3
37. Kite, V., & Park, S. (2022). Preparing inservice science teachers to bring unplugged computational thinking to their students. Teaching and Teacher Education, 120, Article 103904. https://doi.org/10.1016/j.tate.2022.103904
38. Kong, S., Lai, M., & Li, Y. (2023). Scaling up a teacher development programme for sustainable computational thinking education: TPACK surveys, concept tests and primary school visits. Computers & Education, 194, 1–17. https://doi.org/10.1016/j.compedu.2022.104707
39. Kong, S., Lai, M., & Sun, D. (2020). Teacher development in computational thinking: design and learning outcomes of programming concepts, practices and pedagogy. Computers & Education, 151, 1–19. https://doi.org/10.1016/j.compedu.2020.103872
40. Kong, S.-C., & Lai, M. (2022). A proposed computational thinking teacher development framework for K-12 guided by the TPACK model. Journal of Computers in Education, 9(3), 379–402. https://doi.org/10.1007/s40692-021-00207-7
41. Kong, S. C., & Lao, A. C. C. (2019). Assessing in-service teachers’ development of computational thinking practices in teacher development courses (pp. 976–982). Association for Computing Machinery. https://doi.org/10.1145/3287324.3287415
42. Korkmaz, O., ¨ Çakir, R., & Ozden, ¨ M. Y. (2017). A validity and reliability study of the computational thinking scales (CTS). Computers in Human Behavior, 72, 558–569. https://doi.org/10.1016/j.chb.2017.01.005
43. Lee, S. J., Francom, G. M., & Nuatomue, J. (2022). Computer science education and K-12 students’ computational thinking: A systematic review. International Journal of Educational Research, 114, Article 102008. https://doi.org/10.1016/j.ijer.2022.102008
44. Looi, C. K., How, M. L., Longkai, W., Seow, P., & Liu, L. (2018). Analysis of linkages between an unplugged activity and the development of computational thinking. Computer Science Education, 28(3), 255–279.
45. Lu, C., Macdonald, R., Odell, B., Kokhan, V., Demmans Epp, C., & Cutumisu, M. (2022). A scoping review of computational thinking assessments in higher education. Journal of Computing in Higher Education, 34(2), 416–461. https://doi.org/10.1007/s12528-021-09305-y
46. Lyon, J. A., & J Magana, A. (2020). Computational thinking in higher education: A review of the literature. Computer Applications in Engineering Education, 28(5), 1174–1189. https://doi.org/10.1002/cae.22295
47. Molina-Ayuso, A., Adamuz-Povedano, N., Bracho-Lopez, ´ R., & Torralbo-Rodríguez, M. (2022). Introduction to computational thinking with scratch for teacher training for spanish primary school teachers in mathematics. Education Sciences, (12), 12. https://doi.org/10.3390/educsci12120899
48. Monjelat, N., & Lantz-Andersson, A. (2020). Teachers’ narrative of learning to program in a professional development effort and the relation to the rhetoric of computational thinking. Education and Information Technologies, 25(3), 2175–2200. https://doi.org/10.1007/s10639-019-10048-8
49. Moreno-Leon, ´ J., Roman-Gonz ´ alez, ´ M., Harteveld, C., & Robles, G. (2017). On the automatic assessment of computational thinking skills: a comparison with human experts. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 2788–2795). https://doi.org/10.1145/3027063.3053216
50. Mouza, C., Yang, H., Pan, Y., 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
51. Mumcu, F., Kıdıman, E., & Ozdinç, ¨ F. (2023a). Integrating computational thinking into mathematics education through an unplugged computer science activity. Journal of Pedagogical Research, 7(2), 72–92. https://doi.org/10.33902/JPR.202318528
52. Mumcu, F., Uslu, N., & Yildiz, B. (2023b). Teacher development in integrated STEM education: design of lesson plans through the lens of computational thinking. Education And Information Technologies, 28(3), 3443–3474. https://doi.org/10.1007/s10639-022-11342-8
53. Nannim, F. A., Ibezim, N. E., Oguguo, B. C. E., & Nwangwu, E. C. (2024). Effect of project-based Arduino robot application on trainee teachers computational thinking in robotics programming course. Education and Information Technologies, 29(10), 13155–13170. https://doi.org/10.1007/s10639-023-12380-6
54. National Research Council. (2010). Report of a workshop on the scope and nature of computational thinking. National Academies Press. https://doi.org/10.17226/12840, 12840.
55. National Research Council. (2012). A framework for K-12 science education: practices, crosscutting concepts, and core ideas. National Academies Press. https://doi.org/10.17226/13165, 13165.
56. Navarro, E., Costa, N., & Pereira, A. (2020). A systematic review of iot solutions for smart farming. Sensors, 20(15), 4231. https://doi.org/10.3390/s20154231
57. Ogegbo, A. A., & Ramnarain, U. (2022). A systematic review of computational thinking in science classrooms. Studies in Science Education, 58(2), 203–230. https://doi.org/10.1080/03057267.2021.1963580
58. Ozdinç, ¨ F., Kayab, G., Mumcu, F., & Yildiz, B. (2022). Integration of computational thinking into STEM activities: an example of an interdisciplinary unplugged programming activity. Science Activities-Projects and Curriculum Ideas in Stem Classrooms, 59(3), 151–159. https://doi.org/10.1080/00368121.2022.2071817
59. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hrobjartsson, ´ A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical research ed.), 372. https://doi.org/10.1136/bmj.n71. n71.
60. Pala, F. K., & Mıhcı Türker, P. (2021). The effects of different programming trainings on the computational thinking skills. Interactive Learning Environments, 29(7), 1090–1100. https://doi.org/10.1080/10494820.2019.1635495
61. Palts, T., & Pedaste, M. (2020). A model for developing computational thinking skills. Informatics in Education, 19(1), 113–128. https://doi.org/10.15388/infedu.2020.06
62. Peracaula-Bosch, M., & Gonz´alez-Martínez, J. (2022). Developing computational thinking among pre-service teachers. Qwerty, 17(1), 28–44. https://doi.org/10.30557/QW000049
63. Pewkam, W., & Chamrat, S. (2022). Pre-service teacher training program of stem-based activities in computing science to develop computational thinking. Informatics In Education, 21(2), 311–329. https://doi.org/10.15388/infedu.2022.09
64. Pimdee, P., & Pipitgool, S. (2023). Promoting undergraduate pre-service teacher computational thinking. TEM Journal-Technology Education Management Informatics, 12(1), 540–549. https://doi.org/10.18421/TEM121-64
65. Ragonis, N., Rosenberg-Kima, R., & Hazzan, O. (2024). A computational thinking course for all preservice K-12 teachers: implementing the four pedagogies for developing computational thinking (4P4CT) framework. Educational Technology Research and Development. https://doi.org/10.1007/s11423-024-10406-5
66. Rich, P. J., Larsen, R. A., & Mason, S. L. (2021). Measuring teacher beliefs about coding and computational thinking. Journal of Research on Technology in Education, 53(3), 296–316. https://doi.org/10.1080/15391523.2020.1771232
67. Rom´an-Gonz´alez, M., P´erez-Gonz´alez, J. C., Moreno-Leon, ´ J., & Robles, G. (2018). Can computational talent be detected? Predictive validity of the Computational Thinking Test. International Journal of Child-Computer Interaction, 18, 47–58.
68. S´aez-Lopez, ´ J. M., Del Olmo-Munoz, ˜ J., Gonz´alez-Calero, J. A., & Cozar-Guti ´ ´errez, R. (2020). Exploring the effect of training in visual block programming for preservice teachers. Multimodal Technologies and Interaction, 4(3), 65. https://doi.org/10.3390/mti4030065
69. Schafer, ¨ M. S., & Hase, V. (2023). Computational methods for the analysis of climate change communication: towards an integrative and reflexive approach. WIREs Climate Change, 14(2), e806. https://doi.org/10.1002/wcc.806
70. Schuch, F. B., Vancampfort, D., Richards, J., Rosenbaum, S., Ward, P. B., & Stubbs, B. (2016). Exercise as a treatment for depression: A meta-analysis adjusting for publication bias. Journal of Psychiatric Research, 77, 42–51. https://doi.org/10.1016/j.jpsychires.2016.02.023
71. Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158. https://doi.org/10.1016/j.edurev.2017.09.003
72. Sovey, S., Osman, K., & Mohd-Matore, M. E. E. (2022). Exploratory and confirmatory factor analysis for disposition levels of computational thinking instrument among secondary school students. European Journal of Educational Research, 11(2), 639–652. https://doi.org/10.12973/eu-jer.11.2.639
73. Sun, L., Guo, Z., & Zhou, D. (2022). Developing K-12 students’ programming ability: A systematic literature review. Education and Information Technologies, 27(5), 7059–7097. https://doi.org/10.1007/s10639-022-10891-2
74. Sun, L., & Liu, J. (2024a). A gender differential analysis of educational robots’ effects on primary teachers’ computational thinking: mediating effect of programming attitudes. Education and Information Technologies, 29(15), 19753–19782. https://doi.org/10.1007/s10639-024-12655-6
75. Sun, L., & Liu, J. (2024b). Micro: bit programming effects on elementary STEM teachers’ computational thinking and programming attitudes: A moderated mediation model. Journal of Research on Technology in Education, 1–23. https://doi.org/10.1080/15391523.2024.2402357
76. Sun, L., You, X., & Zhou, D. (2023). Evaluation and development of STEAM teachers’ computational thinking skills: analysis of multiple influential factors. Education and Information Technologies, 28(11), 14493–14527. https://doi.org/10.1007/s10639-023-11777–7
77. Sung, Y.-H., & Jeong, Y.-S. (2019). Development and application of programming education model based on visual thinking strategy for pre-service teachers. Universal Journal of Educational Research, 7(5), 42–53. https://doi.org/10.13189/ujer.2019.071507
78. Tankiz, E., & Atman Uslu, N. (2023). Preparing pre-service teachers for computational thinking skills and its teaching: a convergent mixed-method study. Technology, Knowledge and Learning, 28(4), 1515–1537. https://doi.org/10.1007/s10758-022-09593-y
79. Tripon, C. (2022). Supporting future teachers to promote computational thinking skills in teaching stem-a case study. Sustainability, 14(19). https://doi.org/10.3390/su141912663
80. Tsai, F. (2023). Using a physical computing project to prepare preservice primary teachers for teaching programming. Sage Open, 13(4). https://doi.org/10.1177/21582440231205409
81. Tsai, F. (2024). Development and evaluation of an internet of things project for preservice elementary school teachers. Sustainability, (17), 16. https://doi.org/10.3390/su16177632
82. Tsai, M.-J., Liang, J.-C., Lee, S. W.-Y., & Hsu, C.-Y. (2022). Structural validation for the developmental model of computational thinking. Journal of Educational Computing Research, 60(1), 56–73. https://doi.org/10.1177/07356331211017794
83. Umutlu, D. (2022). An exploratory study of pre-service teachers’ computational thinking and programming skills. Journal of Research on Technology in Education, 54(5), 754–768. https://doi.org/10.1080/15391523.2021.1922105
84. Uzumcu, O., & Bay, E. (2020). The effect of computational thinking skill program design developed according to interest driven creator theory on prospective teachers. Education and Information Technologies, 26, 565–583. https://doi.org/10.1007/s10639-020-10268-3
85. Voon, X. P., Wong, S. L., Wong, L. H., Khambari, M. N. M., & Syed-Abdullah, S. I. S. (2023). Developing pre-service teachers’ computational thinking through experiential learning: hybridisation of plugged and unplugged approaches. Research and Practice in Technology Enhanced Learning, 18. https://doi.org/10.58459/rptel.2023.18006
86. Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
87. Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 366(1881), 3717–3725. https://doi.org/10.1098/rsta.2008.0118
88. Yadav, A., & Berges, M. (2019). Computer science pedagogical content knowledge: characterizing teacher performance. ACM Transactions on Computing Education, 19(3), 1–24. https://doi.org/10.1145/3303770
89. Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. TechTrends, 60(6), 565–568. https://doi.org/10.1007/s11528-016-0087-7
90. Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education, 14(1). https://doi.org/10.1145/2576872
91. Yun, M., & Crippen, K. J. (2024). Computational thinking integration into Pre-service science teacher education: A systematic review. Journal of Science Teacher Education, 36(2), 1–30. https://doi.org/10.1080/1046560X.2024.2390758
92. Zha, S., Jin, Y., Moore, P., & Gaston, J. (2020a). A cross-institutional investigation of a flipped module on preservice teachers’ interest in teaching computational thinking. Journal of Digital Learning in Teacher Education, 36(1), 32–45. https://doi.org/10.1080/21532974.2019.1693941
93. Zha, S., Jin, Y., Moore, P., & Gaston, J. (2020b). Hopscotch into coding: introducing pre-service teachers computational thinking. TechTrends, 64(1), 17–28. https://doi.org/10.1007/s11528-019-00423-0
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