Abstract
Computational thinking (CT) has become the basic foothold of STEAM education. The role of teachers as an essential element of CT education cannot be ignored. Therefore, measuring teachers’ ability to integrate CT into classroom is necessary. There were two sub-studies in this study, the one was to develop a specialized scale for the evaluation of teachers’ CT skills. The other was to take K-12 STEAM teachers as sample to measure their CT levels and analyze the impact of the influential factors of personal attributes, occupational attributes, and environmental support on teachers’ CT skills. The results showed that the Computational Thinking Scale for Teachers (TCTS) has good reliability and validity. The CT skills of 925 STEAM teachers from China were at an upper-middle level. Further analysis revealed significant differences in teachers’ CT skills in terms of gender, age, teaching experience, grade, subjects, and nature of school. Firstly, by contrast, male teachers’ CT skills were slightly higher than female teachers’; 30–40-year-old teachers possessed the highest level of CT skills; Second, the longer the teaching experience, the higher the teachers’ CT skills; primary school teachers’ CT skills were higher than those of middle school and high school teachers; Interdisciplinary comprehensive courses and teaching methods may be more conducive to the improvement of teachers’ CT skills, which acted elementary science teachers’ CT skills were higher than those of teachers of other subjects. Third, the nature of the school also affected the CT skills of STEAM teachers. The CT of teachers in private schools was higher than those in public schools. Therefore, the regional differences and educational equity in teacher’ CT training should also be concerned. Concerning the questions, this study carried out an in-depth discussion and put forward inspiration and suggestions. The research findings revealed the mechanism that affects teachers’ CT skills and provided meaningful evidence support for the training and evaluation of K-12 STEAM in-service teachers.
Similar content being viewed by others
Data availability
The data are available from the corresponding author on reasonable request.
References
Alfayez, A. A., & Lambert, J. (2019). Exploring Saudi computer science teachers’ conceptual mastery level of computational thinking skills. Computers in the Schools, 36(3), 143–166. https://doi.org/10.1080/07380569.2019.1639593.
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, 100329. https://doi.org/10.1016/j.ijcci.2021.100329.
Angeli, C., & Valanides, N.(2009). Epistemological and methodological issues for the conceptualization, development, and assessment of ICT-TPCK: Advances in technological pedagogical content knowledge (TPCK). Computers & Education, 52(1), 154–168. https://doi.org/10.1016/j.compedu.2008.07.006.
Angeli, C., & Valanides, N.(2005). Preservice teachers as ICT designers: an instructional design model based on an expanded view of pedagogical content knowledge. Journal of Computer Assisted Learning, 21(4), 292–302.
Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661–670. https://doi.org/10.1016/j.robot.2015.10.008.
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.
Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: a digital age skill for everyone. Learning & Leading with Technology, 38(6), 20–23. http://files.eric.ed.gov/fulltext/EJ918910.
Bati, K., & Yetişir, M. (2021). Examination of Turkish Middle School STEM Teachers’ Knowledge about Computational Thinking and Views Regarding Information and Communications Technology. Computers in the Schools, 38(1), 57–73. https://doi.org/10.1080/07380569.2021.1882206.
Bebras-Ireland. (2020). Bebras-Ireland Online reference included in article [Internet document] (2020) https://bebras.techweek.ie/, Accessed 11th May 2020.
Brennan, K., Monroyhernandez, A., & Resnick, M. (2010). Making projects, making friends: Online community as catalyst for interactive media creation. New Directions for Youth Development, 2010(128), 75–83. https://doi.org/10.1002/yd.377
Brennan, K., & Resnick, M. (2012, July). New frameworks for studying and assessing the development of computational thinking. Annual Meeting of the American Educational Research Association (pp. 1–25), Vancouver.
Boulden, D. C., Rachmatullah, A., Oliver, K. M., et al. (2021). Measuring in-service teacher self-efficacy for teaching computational thinking: Development and validation of the T-STEM CT. Education and Information Technologies, 26, 4663–4689. https://doi.org/10.1007/s10639-021-10487-2.
Bower, M., Wood, L. N., & Lai, J. W., et al.(2017). Improving the computational thinking pedagogical capabilities of school teachers. Australian Journal of Teacher Education, 42(3), 53–72.
Butler, D., & Leahy, M. (2021). Developing preservice teachers’ understanding of computational thinking: A constructionist approach. British Journal of Educational Technology, 52, 1060–1077. https://doi.org/10.1111/bjet.13090.
Cabrera, L. (2019). Teacher preconceptions of computational thinking: A systematic literature review. Journal of Technology and Teacher Education, 27(3), 305–333. https://www.learntechlib.org/primary/p/210234/.
Carmines, E. G., & Zeller, R. A. (1982). Reliability and validity assessment (5th ed.). Sage Publications Inc.
Chen, X.(1989). Curriculum Theory. People’s Education Press.
Cheung, S., & Lai, M.(2022). Effects of a teacher development program on teachers’ knowledge and collaborative engagement, and students’ achievement in computational thinking concepts. British journal of educational technology. https://doi.org/10.1111/bjet.13256.
Çoban, E., & Korkmaz, Ö. (2021). An alternative approach for measuring computational thinking: Performance-based platform. Thinking Skills and Creativity, 42, 100929. https://doi.org/10.1016/j.tsc.2021.100929.
Corradini, I., Lodi, M., & Nardelli, E. (2017, August). Conceptions and misconceptions about computational thinking among Italian primary school teachers. In Proceedings of the 2017 ACM Conference on International Computing Education Research (pp.136–144). Washington.
DeVellis, R. (2007). Scale development (4th ed.). Sage.
del Olmo-Muñoz, J., Cózar-Gutiérrez, R., González-Calero, J. A. (2020). Computational thinking through unplugged activities in early years of Primary Education. Computers & Education, 150,103832. https://doi.org/10.1016/j.compedu.2020.103832.
Efecan, C. F., Sendag, S., Gedik, N.(2020). Pioneers on the Case for Promoting Motivation to Teach Text-Based Programming. Journal of Educational Computing, 59(3), 453–469. https://doi.org/10.1177/0735633120966048.
Esteve, F., Adell, J., Llopis, Á., & Valdeolivas, G. (2019). The Development of Computational Thinking in Student Teachers through an Intervention with Educational Robotics. Journal of Information Technology Education: Innovations in Practice, 18, 139–152.
Fabrigar, L. R., Wegener, D. T., & Maccallum, R. C., et al.(1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. https://doi.org/10.1037/1082-989X.4.3.272.
Fatima, R., Chouhan, A. Y., Liu, L., et al. (2019). How persuasive is a phishing email? A phishing game for phishing awareness. Journal of Computer Security, 27(6), 581–612.
Fessakis, G., & Prantsoudi, S. (2019). Computer Science Teachers’ Perceptions, Beliefs, and Attitudes on Computational Thinking in Greece. Informatics in Education, 18(2), 227–258.
Freina, L., Bottino, R. M., & Ferlino, L. (2019). Fostering Computational Thinking skills in the Last Years of Primary School. International Journal of Serious Games, 6(3), 101–115.
Garvin, M., Killen, H., & Plane, J., et al. (2019, February). Primary School Teachers’ Conceptions of Computational Thinking. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (pp. 899–905). Minneapolis.
Gignac, G. E., & Szodorai, E. T. (2016). Effect size guidelines for individual differences researchers. Personality and Individual Differences, 102, 74–78. https://doi.org/10.1016/j.paid.2016.06.069.
Günbatar, M. S., & Bakırcı, H. (2019). STEM teaching intention and computational thinking skills of pre-service teachers. Education and Information Technologies, 24, 1615–1629. https://doi.org/10.1007/s10639-018-9849-5.
ISTE. (2015). CT leadership toolkit. http://www.iste.org/docs/ctdocuments/ct-leadershipt-toolkit.pdf?sfvrsn=4. Accessed 3 Sept 2015.
ISTE. (2018a). ISTE announces new CT standards for all educators. https://www.iste.org/explore/Press-Releases/ISTE-Announces-New-Computational-Thinking-Standards-for-All-Educators. Accessed 9 Oct 2018.
ISTE. (2018b). ISTE Standards for Educators: Computational Thinking Competencies. https://www.iste.org/standards/iste-standards-for-computational-thinking. Accessed 9 Oct 2018.
Juskeviciene, A. (2020). STEAM Teacher for a Day: A Case Study of Teachers’ Perspectives on Computational Thinking. Informatics in Education, 19(1), 33–50.
Kalayci, S.(2010). SPSS applied multivariate statistical techniques (5th ed.).Asil Publication.
Kalelio˘glu, F., Gülbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4(3), 583-596.
Kennedy,P.(1986). Interpreting dummy variable. Review of Economics and Statistics, 68(4), 174–175.
Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). The Guilford Press.
Koehler, M. J., Mishra, P., & Yahya, K. (2007). Tracing the development of teacher knowledge in a design seminar: Integrating content, pedagogy, and technology. Computers & Education, 49(3), 740–762. https://doi.org/10.1016/j.compedu.2005.11.012.
Korkmaz, Ö., Çakir, R., & Özden, 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.
Lai, R. P. (2021). Teachers’ ontological perspectives of computational thinking and assessment: A text mining approach. Journal of Educational Computing Research, 60(3), 661–695. https://doi.org/10.1177/07356331211043547.
Ministry of Education of the People’s Republic of China. (2022). Curriculum Standards for Compulsory Education Science (2022 Edition). https://www.liuxue86.com/a/4254994.html. Accessed 9 Dec 2022.
Mozelius, P., Öberg, L.-M. (2017, October). Play-based learning for programming education in primary school: The Östersund model. 16th European Conference on e-Learning, (pp. 1–14). Porto.
Nouri, J., Zhang, L., Mannila, L., & Norén, E. (2020). Development of computational thinking, digital competence and 21st century skills when learning programming in K-9. Education Inquiry, 11(1), 1–17. https://doi.org/10.1080/20004508.2019.1627844.
Ouyang, Y., Hayden, K. L., & Remold, J. (2018, February). Introducing computational thinking through non-programming science activities. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education, (pp. 308–313). Baltimore.
Papadakis, S. J., Kalogiannakis, M., & Zaranis, N.(2016). Developing fundamental programming concepts and computational thinking with ScratchJr in preschool education: A case study. International Journal of Mobile Learning and Organisation, 10(3), 187–202.
Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Basic Books, Inc.
Pérez-Calderón, E., Prieto-Ballester, J.-M., Miguel-Barrado, V.(2021). Analysis of Digital Competence for Spanish Teachers at Pre-University Educational Key Stages during COVID-19. International Journal of Environmental Research and Public Health, 18(15), 8093.
Piedade, J., Dorotea, N., Pedro, A., & Matos, J. F. L.(2020). On Teaching Programming Fundamentals and Computational Thinking with Educational Robotics: A Didactic Experience with Pre-Service Teachers. Education Sciences, 10(214), 1–15.
Putnam, R. T., & Borko, H.(2000). What Do New Views of Knowledge and Thinking Have to Say About Research on Teacher Learning? Educational Researcher, 29(1), 4–15. https://doi.org/10.3102/0013189X029001004.
Qu, J. R., & Fok, P. K. (2021). Cultivating students’ computational thinking through student-robot interactions in robotics education. International Journal of Technology and Design Education, 32, 1983–2002. https://doi.org/10.1007/s10798-021-09677-3.
Repenning, A., Webb, D., Ioannidou, A. (2010, March). Scalable game design and the development of a checklist for getting computational thinking into public schools. Proceedings of the 41st ACM technical symposium on Computer science education, (pp. 265–269). Milwaukee. https://doi.org/10.1145/1734263.1734357.
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 & Education (3), 104196. https://doi.org/10.1016/j.compedu.2021.10419.
Rich, K. M., Yadav, A., & Larimore, R. A. (2020). Teacher implementation profiles for integrating computational thinking into elementary mathematics and science instruction. Education and Information Technologies, 25(4), 3161–3188. https://doi.org/10.1007/s10639-020-10115-5.
Rich, K. M., Yadav, A., & Schwarz, C. V. (2019). Computational thinking, mathematics, and science: elementary teachers’ perspectives on integration. Journal of Technology and Teacher Education, 27(2), 165–205. https://par.nsf.gov/servlets/purl/10183080.
Reichert, J. T., Barone, D. A. C., & Kist, M. (2020). Computational Thinking in K-12: An Analysis with Mathematics Teachers. Eurasia Journal of Mathematics, Science and Technology Education, 16(6), em1847.
Selby, C., & Woollard, J. (2013, January). Computational thinking: The developing definition. In Proceedings of the special interest group on computer science education (SIGCSE) (pp. 1–6). Canterbury.
Simmonds, J., Gutierrez, F. J., Casanova, C., Sotomayor, C., & Hitschfeld, N. (2019, February). A teacher workshop for introducing computational thinking in rural and vulnerable environments. Proceedings of the 50th ACM Technical Symposium on Computer Science Education (pp. 1143–1149). Minneapolis. https://doi.org/10.1145/3287324.3287456.
Sousa, D. A., & Tomlinson, C. A. (2010). Differentiation and the Brain: How Neuroscience Supports the Learner-Friendly Classroom (2nd ed.). Solution Tree Press.
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.
Sun, L., Guo, Z., & Zhou, D. (2022). Developing K-12 students’ programming ability: A systematic literature review. Education and Information Technologies, 27, 7059–7097. https://doi.org/10.1007/s10639-022-10891-2.
Sun, L., Hu, L., Yang, W., Zhou, D., & Wang, X.(2021). STEM learning attitude predicts computational thinking skills among primary school students. Journal of computer assisted learning, 37(2), 346–358. https://doi.org/10.1111/jcal.12493.
Valanides, N., & Angeli, C.(2008a). Learning and teaching about scientific models with a computer-modeling tool. Computers in Human Behavior, 242(2), 220–233.
Valanides, N., & Angeli, C.(2008b). Distributed Cognition in a Sixth-Grade Classroom. Journal of Research on Technology in Education, 40(3), 309–336. https://doi.org/10.1080/15391523.2008.10782510.
Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education: Towards an agenda for research and practice. Education and Information Technologies, 20(4), 715–728. https://doi.org/10.1016/j.chb.2007.01.005.
Wu, L., Looi, C.-K., Liu, L., & How, M. L. (2018, November). Understanding and developing in-service teachers’ perceptions towards teaching in computational thinking: Two studies. In J. C. Yang, M. Chang, L.-H. Wong, & M. M. T. Rodrigo (Eds.), Proceedings of the 26th International Conference on Computers in Education (ICCE). (pp. 735–742). Manila. https://apsce.net/icce/icce2018/wp-content/uploads/2018/12/C7-05.pdf.
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215.
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.
Yadav, A., Gretter, S., Good, J., & McLean, T. (2017). Computational thinking in teacher education. In P. J. Rich & C. B. Hodges (Eds.), Emerging research, practice, and policy on computational thinking (pp. 205–220). Springer.
Acknowledgements
This work was supported by the financial supports by the National Social Science Foundation Youth Project in Pedagogy of China [grant numbers CCA190261].
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Ethics statement
The participants were protected by hiding their personal information during the research process. They knew that their participation was voluntary and they could withdraw at any time.
Conflicting interest
The author declared no potential conflicts of interest concerning the research, authorship, and/or publication of this article.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Lihui Sun, Xinxin You and Danhua Zhou share the first authorship.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Sun, L., You, X. & Zhou, D. Evaluation and development of STEAM teachers’ computational thinking skills: Analysis of multiple influential factors. Educ Inf Technol 28, 14493–14527 (2023). https://doi.org/10.1007/s10639-023-11777-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10639-023-11777-7