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Teachers’ narrative of learning to program in a professional development effort and the relation to the rhetoric of computational thinking

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Abstract

In recent years, there has been a renewed interest in the introduction of programming in teacher education and professional development, highlighting its importance for the development of so-called computational thinking. This study explored primary education teachers’ participation in programming practices. By focusing on their views of creating a computational artefact with Scratch, the difficulties encountered, and resources to overcome them in the context of a professional development effort in computer science at the primary education level, was analysed. Employing Thematic Analysis, 17 group documentations (drafts, Scratch projects and final reports) were examined. Findings revealed that projects that had educational content involved more elaborate descriptions, while recreational projects presented a shorter and less elaborate account of the programming process. In terms of difficulties, teachers described initial concerns regarding how to achieve what they had planned, imagined or expected, and they expressed difficulties related to the edition of imported images for objects and scenarios and related to the block-based programming practices. Participants resorted to a great variety of resources to overcome them, which highlights the importance of making testing and debugging practices more explicit. These findings could be relevant for the design of future learning scenarios, highlighting the importance of providing opportunities to develop a critical approach towards expressed commercial promises as well as opportunities to challenge the rhetoric of computational thinking.

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  • 08 January 2020

    Acknowledgements was not included in the original article and is now provided to this article.

References

  • Adams, J. C., & Webster, A. R. (2012). What do students learn about programming from game, music video, and storytelling projects? In SIGCSE’12 proceedings of the 43rd ACM technical symposium on computer science education (pp. 643–648). North Carolina: ACM.

    Google Scholar 

  • Apiola, M., & Tedre, M. (2012). New perspectives on the pedagogy of programming in a developing country context. Computer Science Education, 22(3), 285–313. https://doi.org/10.1080/08993408.2012.726871.

    Article  Google Scholar 

  • Armoni, M. (2011). The nature of CS in K-12 curricula: The roots of confusion. ACM Inroads, 2(4), 18. https://doi.org/10.1145/2038876.2038882.

    Article  Google Scholar 

  • Balanskat, A., & Engelhardt, K. (2015). Computing our future. Computer programming and coding. Priorities, school curricula and iniciatives across Europe. Brussels, Belgium.

  • 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.

    Article  Google Scholar 

  • Baytak, A., & Land, S. M. (2011). An investigation of the artifacts and process of constructing computers games about environmental science in a fifth grade classroom. Educational Technology Research and Development, 59(6), 765–782. https://doi.org/10.1007/s11423-010-9184-z.

    Article  Google Scholar 

  • Borchardt, M., & Roggi, I. (2017). Ciencias de la Computación en los Sistemas Educativos De América Latina. Cuaderno SIeTEAL: Ciencias de la Computación en los sistemas educativos de América Latina. Retrieved from http://www.tic.siteal.iipe.unesco.org/sites/default/files/stic_publicacion_files/tic_cuaderno_ciencias_computacion.pdf. Accessed 04-12-2019.

  • Brackmann, C., Barone, D., Casali, A., Boucinha, R., & Muñoz-Hernandez, S. (2016). Computational thinking: Panorama of the Americas. In 2016 international symposium on computers in education, SIIE 2016: Learning analytics technologies (pp. 1–6). Salamanca: IEEE. https://doi.org/10.1109/SIIE.2016.7751839.

    Chapter  Google Scholar 

  • Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology using thematic analysis in psychology. Qualitative Research in Psychology, 0887(January), 77–101. https://doi.org/10.1191/1478088706qp063oa.

    Article  Google Scholar 

  • Brennan, K. (2013). Best of both worlds: Issues of structure and agency in computational creation, in and out of the school. Massachussets Institute of Technology.

  • Brennan, K. (2015). Beyond technocentrism: Supporting constructionism in the classroom. Constructivist Foundations, 10(3), 289–296.

    Google Scholar 

  • Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Annual American Educational Research Association Meeting, Vancouver, BC, Canada, 1–25. 10.1.1.296.6602.

  • Buitrago Flórez, F., Casallas, R., Hernández, M., Reyes, A., Restrepo, S., & Danies, G. (2017). Changing a Generation’s way of thinking: Teaching computational thinking through programming. Review of Educational Research, 87(4), 834–860. https://doi.org/10.3102/0034654317710096.

    Article  Google Scholar 

  • Casali, A., Zanarini, D., San Martín, P. S., & Monjelat, N. (2018a). Pensamiento Computacional y Programación en la Formación de Docentes del Nivel Primario. In G. Dapozo (Ed.), XX Workshop de Investigadores en Ciencias de la Computación (pp. 451–455). Corrientes, Argentina: Universidad Nacional del Nordeste. Facultad de Ciencias Exactas.

  • Casali, A., Zanarini, D., Monjelat, N., & San Martín, P. (2018b). Teaching and Learning Computer Science for Primary School Teachers : an Argentine Experience. In Proceedings XIII Latin American Conference on Learning Technologies LACLO 2018 (pp. 349–355). São Paulo – Brazil: IEEE. https://doi.org/10.1109/LACLO.2018.00067

  • CSTA. (2017). K-12 standards. https://www.csteachers.org/page/standards. Accessed 04-12-2019.

  • Feng, C.-Y., & Chen, M.-P. (2014). The effects of goal specificity and scaffolding on programming performance and self-regulation in game design. British Journal of Educational Technology, 45(2), 285–302.

    Article  Google Scholar 

  • Fitzgerald, S., Lewandowski, G., McCauley, R., Murphy, L., Simon, B., Thomas, L., & Zander, C. (2008). Debugging: Finding, fixing and flailing, a multi-institutional study of novice debuggers. Computer Science Education, 18(2), 93–116.

    Article  Google Scholar 

  • Gal-Ezer, J., & Stephenson, C. (2014). A tale of two countries: Successes and challenges in K-12 computer science education in Israel and the United States. ACM Transactions on Computing Education, 14(2).

  • Godhe, A-L., Lilja, P., & Selwyn, N. (2019). Making sense of making: Critical issues in the integration of maker education into schools. Technology, Pedagogy and Education, 28(3), 317–328.

  • Grover, S., & Pea, R. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher, 42(1), 38–43.

    Article  Google Scholar 

  • Grover, S., Lundh, P., & Jackiw, N. (2019). Non-programming activities for engagement with foundational concepts in introductory programming. In SIGCSE ‘19 (pp. 1136–1142). Minneapolis: ACM. https://doi.org/10.1145/3287324.3287468.

    Chapter  Google Scholar 

  • Heintz, F., Mannila, L., Nygårds, K., Parnes, P., & Regnell, B. (2015). Computing at School in Sweden – Experiences from introducing computer science within existing subjects. In A. Brodnik & J. Vahrenhold (Eds.), Informatics in Schools. Curricula, competences, and competitions (Vol. 9378, pp. 69–81). Cham: Springer. https://doi.org/10.1007/978-3-319-25396-1_11.

    Chapter  Google Scholar 

  • Heintz, F., Mannila, L., & Farnqvist, T. (2016). A review of models for introducing computational thinking, computer science and computing in K-12 education. In Proceedings – Frontiers in education conference, FIE. Erie, Pennsylvania, USA: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/FIE.2016.7757410.

  • Hubwieser, P., Giannakos, M. N., Berges, M., Brinda, T., Diethelm, I., Magenheim, J., et al. (2015). A global snapshot of computer science education in K-12 schools. In Proceedings of the 2015 ITiCSE on working group reports – ITICSE-WGR ‘15. https://doi.org/10.1145/2858796.2858799.

  • Imberman, S., Sturm, D., & Azhar, M. (2014). Computational thinking: Expanding the toolkit. Journal of Computing Sciences in Colleges, 29(6), 39–46.

    Google Scholar 

  • Kafai, Y. B., Proctor, C., & Lui, D. (2019). Framing computational thinking for computational literacies in K-12 education. In Proceedings of the Weizenbaum conference 2019 “Challenges of Digital Inequality – Digital Education, Digital Work, Digital Life” (pp. 1–6). Berlín. https://doi.org/10.34669/wi.cp/2.21

  • Kelleher, C., & Pausch, R. (2005). Lowering the barriers to programming: A survey of programming environments and languages for novice programmers. ACM Computing Surveys, 37(2), 83–137.

    Article  Google Scholar 

  • Kim, C., Yuan, J., Vasconcelos, L., Shin, M., & Hill, R. B. (2018). Debugging during block-based programming. Instructional Science, 46(5), 767–787.

    Article  Google Scholar 

  • Kong, S. C., & Abelson, H. (2019). Computational thinking education. Singapore: Springer Open.

    Book  Google Scholar 

  • Kong, S.-C., & Lao, A. C.-C. (2019). Assessing in-service teachers’ development of computational thinking practices in teacher development courses. In Proceedings of 50th ACM technical symposium on computer science education (SIGCSE ‘19) (pp. 976–982). Minneapolis: ACM. https://doi.org/10.1145/3287324.3287470.

    Chapter  Google Scholar 

  • Lantz-Andersson, A., Lundin, M., & Selwyn, N. (2018). Twenty years of online teacher communities: A systematic review of formally-organized and informally developed professional learning groups. Teaching and Teacher Education, 75, 302–315.

  • Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Lazarinis, F., Karachristos, C. V., & Stavropoulos, E. C. (2018). A blended learning course for playfully teaching programming concepts to school teachers. Education and Information Technologies, 24(2), 1237–1249.

    Article  Google Scholar 

  • Lieberman, A., & Pointer-Mace, D. (2010). Making practice public: Teacher learning in the 21st century. Journal of Teacher Education, 61(1–2), 77–88.

    Article  Google Scholar 

  • Liu, Z., Zhi, R., Hicks, A., & Barnes, T. (2017). Understanding problem solving behavior of 6–8 graders in a debugging game. Computer Science Education, 27(1), 1–29.

    Article  Google Scholar 

  • Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51–61.

    Article  Google Scholar 

  • Lye, S. Y., & Koh, J. H. L. (2018). Case studies of elementary Children’s engagement in computational thinking through scratch programming. In M. S. Khine (Ed.), Computational thinking in the STEM disciplines (pp. 227–251). Switzerland: Springer.

    Chapter  Google Scholar 

  • Maloney, J., Peppler, K., Kafai, Y. B., Resnick, M., & Rusk, N. (2008). Programming by choice: Urban youth learning programming with scratch. In SIGSE ‘08 (pp. 367–371). Portland: ACM. https://doi.org/10.1145/1352135.1352260.

    Chapter  Google Scholar 

  • Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational thinking in K-9 education. In Proceedings of the working group reports of the 2014 on innovation 38; technology in computer science education conference, (June), 1–29. https://doi.org/10.1145/2713609.2713610.

  • Martínez, M. C., Gómez, M. J., Moresi, M., & Benotti, L. (2016). Lessons learned on computer science teachers professional development. In ITICSE (pp. 77–82).

  • McCauley, R., Fitzgerald, S., Lewandowski, G., Murphy, L., Simon, B., Thomas, L., & Zander, C. (2008). Debugging: A review of the literature from an educational perspective. Computer Science Education, 18(2), 67–92.

    Article  Google Scholar 

  • Menekse, M. (2015). Computer science teacher professional development in the United States: A review of studies published between 2004 and 2014. Computer Science Education, 25(4), 325–350.

    Article  Google Scholar 

  • Michaeli, T., & Romeike, R. (2017). Addressing teaching practices regarding software Qualit: Testing and debugging in the classroom. In WiPSCE 2017. Proceedings of the 12th workshop in primary and secondary computing education (pp. 105–106). Nijmegen: ACM.

    Google Scholar 

  • Moallem, M., Morge, S. P., Narayan, S., & Tagliarini, G. A. (2016). The power of computational modeling and simulation for learning STEM content in middle and high schools. In D. Falvo & M. Urban (Eds.), Improving K-12 STEM education outcomes through technological integration. IGI Global: Hershey.

    Google Scholar 

  • Monjelat, N., & San Martín, P. (2016). Programar con Scratch en contextos educativos: ¿Asimilar directrices o co-construir Tecnologías para la Inclusión Social? Praxis Educativa, 20(1), 61–71.

  • Monjelat, N. (2017). Programming technologies for social Inclusion: An experience in professional development with elementary teachers. In 12th Latin American Conference on Learning Objects and Technologies, LACLO, 9-13 October 2017 La Plata. Buenos Aires: IEEE, 1-7.

  • Monjelat, N. (2019). Programming Technologies for Social Inclusion With Scratch: Computational Practices in a Teacher’s Professional Development Course. Educare, 23(3), 1–25.

  • Mouza, C., & Ottenbreit-Lcasaeftwich, A. (2018). Developing computationally literate teachers: Current perspectives and future directions for teacher preparation in computing education. Journal of Technology and Teacher Education, 26(3), 333–352.

    Google Scholar 

  • NGSS Lead States. (2013). Next generation science standards: For states, by states. Washington, DC: National Academies Press.

    Google Scholar 

  • Ohashi, Y. (2017). Preparedness of Japan’s elementary school teachers for the introduction of computer programming education. In V. Dagiene & A. Hellas (Eds.), Informatics in Schools: Focus on Learning Programming. ISSEP 2017. Lecture notes in computer science (Vol. 10696, pp. 129–140). Helsinki: Springer International Publishing AG. https://doi.org/10.1007/978-3-319-71483-7.

    Chapter  Google Scholar 

  • O’Shea, T., & Koschmann, T. (1997). The Children’s machine: Rethinking School in the age of the computer (book). The Journal of the Learning Sciences, 6(4), 401–415.

    Article  Google Scholar 

  • Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books.

    Google Scholar 

  • Papert, S. (1993). The children’s machine: Rethinking school in the age of the computer. New York: Basic Books.

    Google Scholar 

  • Parding, K., Berg-Jansson, A., Sehlstedt, T., McGrath-Champ, S., & Fitzgerald, S. (2017). Differentiation as a consequence of choice and decentralization reforms: Conditions for teachers’ competence development. Professions and Professionalism, 7(2), e1855.

    Google Scholar 

  • Pea, R., & Kurland, D. M. (1984). On the cognitive effects of learning computer programming. New Ideas in Psychology, 2, 137–168.

    Article  Google Scholar 

  • Pettersson, F. (2018). On the issues of digital competence in educational contexts – A review of literature. Education and Information, 23(3), 1005–1021.

    Google Scholar 

  • Petty, T., Heafner, T., Farinde, A., & Plaisance, M. (2015). Windows into teaching and learning: Professional growth of classroom teachers in an online environment. Technology, Pedagogy and Education, 24(3), 375–388.

    Article  Google Scholar 

  • Reding, T. E., & Dorn, B. (2017). Understanding the “teacher experience” in primary and secondary CS professional development. In Proceedings of the 2017 ACM conference on international computing education research (pp. 155–163). Tacoma: ACM Press. https://doi.org/10.1145/3105726.3106185.

    Chapter  Google Scholar 

  • Resnick, M. (2007). All I really need to know (about creative thinking) I learned (by studying how children learn) in kindergarten. In Proceedings of the 6th ACM SIGCHI conference on creativity & cognition – C&C ‘07, 1–6. https://doi.org/10.1145/1254960.1254961.

  • Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., et al. (2009). Scratch: Programming for all. Communications of the ACM, 52(11), 60.

    Article  Google Scholar 

  • Rich, P. J., & Langton, M. B. (2016). Computational thinking: Toward a unifying definition. In J. Spector, D. Ifenthaler, D. Sampson, & P. Isaias (Eds.), Competencies in teaching, learning and educational leadership in the digital age (pp. 229–242). Springer Cham. https://doi.org/10.1007/978-3-319-30295-9.

  • Roque, R., Rusk, N., & Resnick, M. (2016). Mass collaboration and education. In U. Cress, J. Moskaliuk, & H. Jeong (Eds.), Mass collaboration and education (pp. 241–256). Berlin: Springer. https://doi.org/10.1007/978-3-319-13536-6.

    Chapter  Google Scholar 

  • Selwyn, N., Nemorin, S., & Johnson, N. (2017). High-tech, hard work: An investigation of teachers’ work in the digital age. Learning, Media and Technology, 42(4), 390–405.

    Article  Google Scholar 

  • Sentance, S., & Humphreys, S. (2015). Online vs face-to-face engagement of computing teachers for their professional development needs. In A. Brodnik & J. Vahrenhold (Eds.), Informatics in schools. Curricula, competences, and competitions. Lecture notes in computer science (pp. 69–81). Cham: Springer. https://doi.org/10.1007/978-3-319-25396-1_7.

    Chapter  Google Scholar 

  • Tófalo, A. (2016). Aprender 2016: Acceso y uso de TIC en estudiantes y docentes. Buenos Aires: Secretaría de Evaluación Educativa del Ministerio de Educación de la Nación.

    Google Scholar 

  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. London: Harvard University Press.

    Google Scholar 

  • Wertsch, J. (1991). Voices of the mind. A sociocultural approach to mediated action. Cambridge: Harvard University Press.

    Google Scholar 

  • Williamson, B. (2016). Political computational thinking: Policy networks, digital governance and ‘learning to code’. Critical Policy Studies, 10(1), 39–58.

    Article  MathSciNet  Google Scholar 

  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.

    Article  Google Scholar 

  • Wing, J. M. (2011). Research notebook: Computational thinking – What and why? The link. The magazine of the Carnegie Mellon University School of Computer Science.

  • Yadav, A. (2017). Computer science teacher professional development: Towards a research agenda on teacher thinking and learning. In WiPSCE ‘17 (pp. 1–2). Nijmegen: ACM Press.

    Google Scholar 

  • Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. TechTrends, (May), 10–13. https://doi.org/10.1007/s11528-016-0087-7.

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Monjelat, N., Lantz-Andersson, A. Teachers’ narrative of learning to program in a professional development effort and the relation to the rhetoric of computational thinking. Educ Inf Technol 25, 2175–2200 (2020). https://doi.org/10.1007/s10639-019-10048-8

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