Métricas alternativas
Métrica
Palabras clave
coding
education
scientific productivity
SCOPUS Pensamiento computacional
codificación
educación
productividad científica
SCOPUS
Cómo citar
Resumen
En los últimos decenios, el pensamiento computacional ha desempeñado un papel fundamental en la educación y en los procesos legislativos de muchos países, recibiendo también gran atención por parte de diversas organizaciones internacionales que han pedido expresamente que se promueva a partir de la educación escolar. El presente estudio analiza la productividad científica en SCOPUS sobre el pensamiento computacional y su difusión en las escuelas, con referencia específica al contexto K-12 (desde la educación infantil hasta el duodécimo curso). El estudio se ha extendido hasta 2006, cuando Jeannette Wing publicó el artículo principal sobre el pensamiento computacional, iniciando un conjunto de investigaciones y proyectos sobre esta temática, de tal manera que, hasta la fecha, en mayo de 2020, encontramos 1.850 citas de su publicación en SCOPUS. Los datos ofrecen un panorama global sobre la evolución del fenómeno, mostrando un aumento del interés, los principales países promotores; las fuentes, los autores y las obras más citadas, proporcionando así una buena referencia para el sector de la investigación científica acerca del fenómeno del pensamiento computacional en la educación, un tema que hoy es más relevante y significativo que nunca. El presente estudio también representa una herramienta para la reflexión sobre la necesidad de educar a los jóvenes del siglo XXI en el pensamiento computacional con el fin de que adquieran las habilidades específicas que requiere el mercado laboral actual.
Citas
Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074
Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Journal of Educational Technology & Society, 19(3), 47-57.
Ariza, T., Granados, M. R., Ramiro, M. T., & Gómez-García, A. (2011a). Una década de la revista española de orientación y psicopedagogía: Un análisis bibliométrico de su evolución. Revista Española De Orientación Y Psicopedagogía, 22(1), 38-57. https://doi.org/10.5944/reop.vol.22.num.1.2011.76
Ávalos, C., Pérez-Escoda, A., & Monge, L. (2019). Lean Startup as a Learning Methodology for Developing Digital and Research Competencies. Journal of New Approaches in Educational Research, 8(2) 227-242, https://doi.org/10.7821/naer.2019.7.438
Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning & Leading with Technology, 38(6), 20-23.
Bocconi, S., Chioccariello, A., Dettori, G., Ferrari, A., & Engelhardt, K. (2016). Developing Computational Thinking in Compulsory Education-Implications for Policy and Practice, Sevilla: Joint Research Centre. http://doi. org/10.2791/792158.
Bracho, R., Jiménez-Fanjul, N., Maz-Machado, A., Torralbo-Rodríguez, M., & Fernández-Cano, A. (2014). Producción científica sobre narrativa en educación matemática en la Web of Science. Bolema: Boletim De Educación Matemática, 28(49), 744-761. https://doi.org/10.1590/1980-4415v28n49a14
Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Paper presented at the Proceedings of the 2012 Annual Meeting of the American Educational Research Association, Vancouver, Canada,1-25.
Burkle, M., & Cobo, C. (2018). Redefining Knowledge in the Digital Age. Journal of New Approaches in Educational Research, 7(2), 79-80. http://dx.doi.org/10.7821/naer.2018.7.294
Caballero-Gonzalez, Y., Muñoz-Repiso, A. G., & García-Holgado, A. (2019). Learning computational thinking and social skills development in young children through problem solving with educational robotics. Paper presented at the Proceedings of the Seventh International Conference on Technological Ecosystems for Enhancing Multiculturality, 19-23. https://doi.org/10.1145/3362789.3362874
Calao, L. A., Moreno-León, J., Correa, H. E., & Robles, G. (2015). Developing mathematical thinking with scratch. Design for teaching and learning in a networked world, 17-27) Springer. Cham. https:// doi.org/10.1007/978-3-319-24258-3_2
Denner, J., Werner, L., & Ortiz, E. (2012). Computer games created by middle school girls: Can they be used to measure understanding of computer science concepts? Computers & Education,58(1), 240- 249. https://doi.org/10.1016/j.compedu.2011.08.006
Durak, H. Y., & Saritepeci, M. (2018). Analysis of the relation between computational thinking skills and various variables with the structural equation model. Computers & Education, 116, 191-202. https://doi.org/10.1016/j.compedu.2017.09.004
García-Peñalvo, F. J., & Mendes, A. J. (2018). Exploring the Computational Thinking Effects in Pre-University Education, Computers in Human Behavior 80, 407-411. https://doi.org/10.1016/j. chb.2017.12.005
Gómez, I. A., Vázquez-Cano, E., & López-Meneses, E. (2016). El impacto bibliométrico del movimiento MOOC en la comunidad científica española. Educación XX1,19(2), 77-103. https://doi.org/10.5944/ educXX1.13217
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%2F0013189X12463051
Infante-Moro, A., Infante-Moro, J., & Gallardo-Pérez, J. (2019). The Importance of ICTs for Students as a Competence for their Future Professional Performance: the Case of the Faculty of Business Studies and Tourism of the University of Huelva. Journal of New Approaches in Educational Research, 8(2), 201-213. http://dx.doi.org/10.7821/naer.2019.7.434
Kafai, Y. B., & Burke, Q. (2015). Constructionist gaming: Understanding the benefits of making games for learning. Educational Psychologist,50(4), 313-334. https://doi.org/10.1080/00461520.2015.1124 022
Kafai, Y. B., Lee, E., Searle, K., Fields, D., Kaplan, E., & Lui, D. (2014). A crafts-oriented approach to computing in high school: Introducing computational concepts, practices, and perspectives with electronic textiles. ACM Transactions on Computing Education (TOCE),14(1), 1-20. https://doi. org/10.1145/2576874
Kalelioglu, F., Gulbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing,4(3), 583.
Lockwood, J., & Mooney, A. (2017). Computational thinking in education: Where does it fit? A systematic literary review. ArXiv Preprint arXiv:1703.07659, (under review).
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. https://doi. org/10.1016/j.chb.2014.09.012
Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational thinking in K-9 education. Paper presented at the Proceedings of the Working Group Reports of the 2014 on Innovation & Technology in Computer Science Education Conference, 1-29. https://doi.org/10.1145/2713609.2713610
Mengual-Andrés, S., Vázquez-Cano, E., & Meneses, E. L. (2017). La productividad científica sobre MOOC: Aproximación bibliométrica 2012-2016 a través de SCOPUS. RIED. Revista Iberoamericana De Educación a Distancia,20(1), 39-58. http://dx.doi.org/10.5944/ried.20.1.16662
Miller, J. (2019). STEM education in the primary years to support mathematical thinking: Using coding to identify mathematical structures and patterns. Zdm,51(6), 915-927. https://doi.org/10.1007/ s11858-019-01096-y
Papavlasopoulou, S., Giannakos, M. N., & Jaccheri, L. (2017). Empirical studies on the maker movement, a promising approach to learning: A literature review. Entertainment Computing,18, 57- 78. https://doi.org/10.1016/j.entcom.2016.09.002
Peritz, B., & Bar-Ilan, J. (2002). The sources used by bibliometrics-scientometrics as reflected in references. Scientometrics, 54(2), 269-284.
Pugnali, A., Sullivan, A., & Bers, M. U. (2017). The impact of user interface on young children’s computational thinking. Journal of Information Technology Education: Innovations in Practice, 16, 171- 193. Informing Science Institute. Retrieved from https://www.learntechlib.org/p/180753/
Recommendation of the European Parliament and of the council of 18 December 2006 on key competences for lifelong learning (2006, 18 December) Retrieved from https://eur-lex.europa.eu/ legal-content/EN/TXT/?uri=celex%3A32006H0962
Rees, A., García-Peñalvo, F. J., Jormanainen, I., Tuul, M., & Reimann, D. (2016). An overview of the most relevant literature on coding and computational thinking with emphasis on the relevant issues for teachers.
Reinking, A., & Martin, B. (2018). The gender gap in STEM fields: Theories, movements, and ideas to engage girls in STEM. Journal of New Approaches in Educational Research, 7(2), 148-153. https://doi. org/10.7821/naer.2018.7.271
Resnick, M. (2013). Learn to code, code to learn. EdSurge, May.
Rodríguez-García, A.-M., Cáceres Reche, M. P., & Alonso García, S. (2018). The digital competence of the future teacher: bibliometric analysis of scientific productivity indexed in Scopus. IJERI: International Journal of Educational Research and Innovation, (10), 317-333. Retrieved from https:// www.upo.es/revistas/index.php/IJERI/article/view/2960
Roig-Vila, R., & Moreno-Isac, V. (2020). El pensamiento computacional en Educación. Análisis bibliométrico y temático. Revista De Educación a Distancia (RED), 20(63). https://doi.org/10.6018/ red.402621
Sáez-López, J., Román-González, M., &Vázquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two-year case study using “Scratch” in five schools. Computers & Education, 97, 129-141. https://doi.org/10.1016/j.compedu.2016.03.003
Salcines-Talledo, I., González-Fernández, N., & Briones, E. (2020). The Smartphone as a Pedagogic Tool. Student Profiles as related to its Use and Knowledge. Journal of New Approaches in Educational Research, 9(1), 91-109. http://dx.doi.org/10.7821/naer.2020.1.454
Sengupta, P., Dickes, A., & Farris, A. (2018). Toward a phenomenology of computational thinking in STEM education. arXiv Preprint arXiv:1801.09258, en M. S. Khine (Ed.), Computational Thinking in STEM: Foundations and Research Highlights. Springer, Cham. https://doi.org/10.1007/978-3- 319-93566-9_4
Sentance, S., & Csizmadia, A. (2017). Computing in the curriculum: Challenges and strategies from a teacher’s perspective. Education and Information Technologies, 22(2), 469-495. https://doi. org/10.1007/s10639-016-9482-0
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
Tang, X., Yin, Y., Lin, Q., & Hadad, R. (2018). Assessing computational thinking: A systematic review of the literature. Paper presented at the Poster Presented at the 2018 Annual Meeting of the American Educational Research Association (AERA), New York.
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: Mathematical, Physical and Engineering Sciences, 366(1881), 3717-3725. https://doi.org/10.1098/ rsta.2008.0118
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
Yadav, A., Krist, C., Good, J., & Caeli, E. N. (2018). Computational thinking in elementary classrooms: Measuring teacher understanding of computational ideas for teaching science. Computer Science Education, 28(4), 371-400. https://doi.org/10.1080/08993408.2018.1560550
Zhang, L., & Nouri, J. (2019). A systematic review of learning computational thinking through scratch in K-9. Computers & Education, 141, 103607. https://doi.org/10.1016/j.compedu.2019.103607