Effets du codage robotique sur les compétences de pensée computationnelle des élèves du secondaire
DOI :
https://doi.org/10.21432/cjlt28607Mots-clés :
pensée computationnelle, perception, codage robotique, auto efficacitéRésumé
Ces dernières années, la pensée computationnelle a fait l’objet d’une attention accrue en tant que compétence essentielle pour la résolution de problèmes. L’une des méthodes pour développer les compétences des élèves en matière de pensée computationnelle est le codage robotique. Cette étude visait à examiner l’impact des activités de codage robotique sur les perceptions d’auto‑efficacité des compétences de pensée computationnelle des élèves du secondaire. Un modèle quasi expérimental prétest-post-test à groupe unique a été utilisé, impliquant 32 élèves du secondaire. Ces élèves, organisés en groupes de quatre, ont participé à des activités pratiques de codage robotique en utilisant des robots Lego Mindstorms EV3 Education pendant un total de 20 heures. Les données ont été collectées avant et après les activités de codage robotique à l’aide de l’instrument Self-Efficacy Perception Scale for Computational Thinking Skills (SEPSCTS pour ses sigles en anglais), qui comprend 36 éléments répartis en cinq facteurs. Les données ont été analysées à l’aide de tests t pour échantillons appariés et d’analyses de covariance (ANCOVA). Les résultats ont démontré une augmentation significative des perceptions d’auto‑efficacité des élèves en matière de compétences de pensée computationnelle à la suite des activités, cette augmentation étant observée de manière cohérente entre les genres. Finalement, les défis rencontrés au cours de la recherche et de la pratique ont été rapportés, ainsi que les limites de l’étude, afin d’informer les recherches futures.
Références
Ackermann, E. (2001). Piaget’s constructivism, Papert’s constructionism: What’s the difference? Massachusetts Institute of Technology: Future of Learning Group publication, 5(3), 438–448. https://learning.media.mit.edu/content/publications/EA.Piaget%20_%20Papert.pdf
Afari, E., & Khine, M. S. (2017). Robotics as an educational tool: Impact of Lego Mindstorms. International Journal of Information and Education Technology, 7(6), 437–442. https://doi.org/10.18178/ijiet.2017.7.6.908
Akpınar, Y., & Altun, A. (2014). Bilgi toplumu okullarında programlama eğitimi gereksinimi [The need for programming education in schools of the information society]. Elementary Education Online, 13(1), 1–4. https://ilkogretim-online.org/index.php/pub/article/view/6168
Alimisis, D. (2013). Educational robotics: Open questions and new challenges. Themes in Science and Technology Education, 6(1), 63–71. https://files.eric.ed.gov/fulltext/EJ1130924.pdf
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. http://www.jstor.org/stable/jeductechsoci.19.3.47
Apostolellis, P., Stewart, M., Frisina, C., & Kafura, D. (2014). RaBit EscAPE: A board game for computational thinking. In O. S. Iversen, P. Markopoulos, C. Dindler, F. Garzotto, C. Frauenberger, & A. Zeising (Eds.), Proceedings of the 2014 Conference on Interaction Design and Children (pp. 349–352). ACM. https://doi.org/10.1145/2593968.2610489
Atmatzidou, S., & Demetriadis, S. (2014). How to support students’ computational thinking skills in educational robotics activities. In D. Alimisis, G. Granosik, & M. Moro (Eds.), Proceedings of 4th International Workshop Teaching Robotics, Teaching With Robotics & 5th International Conference Robotics in Education (pp. 43–50). University of Padova. https://www.terecop.eu/TRTWR-RIE2014/files/00_WFr1/00_WFr1_06.pdf
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
Atmatzidou, S., Markelis, I., & Demetriadis, S. (2008). The use of LEGO Mindstorms in elementary and secondary education: Game as a way of triggering learning. In S. Carpin, I. Noda, E. Pagello, M. Reggiani, & O. Stryk (Eds.), International Conference of Simulation, Modeling and Programming for Autonomous Robots (SIMPAR) (pp. 22–30). Springer. http://www.dei.unipd.it/~emg/downloads/SIMPAR08-WorkshopProceedings/TeachingWithRobotics/atmatzidou_et_al.pdf
Avello, R., Lavonen, J., & Zapata-Ros, M. (2020). Codificación y robótica educativa y su relación con el pensamientocomputacional y creativo. Una revisión compresiva [Coding and educational robotics and their relationship with computational and creative thinking. A comprehensive review]. Revista de Educación a Distancia (RED), 20(63). https://doi.org/10.6018/red.413021
Baek, Y., Yang, D., & Fan, Y. (2019). Understanding second grader’s computational thinking skills in robotics through their individual traits. Information Discovery and Delivery, 47(4), 218–228. https://doi.org/10.1108/IDD-09-2019-0065
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
Basawapatna, A. R., Repenning, A., & Lewis, C. H. (2013). The simulation creation toolkit: An initial exploration into making programming accessible while preserving computational thinking. In T. Camp & P. Tymann (Chairs), Proceedings of the 44th ACM Technical Symposium on Computer Science Education (pp. 501–506). ACM. https://doi.org/10.1145/2445196.2445346
Benitti, F. B. V., & Spolaôr, N. (2017). How have robots supported STEM teaching?. In M. Khine (Ed.), Robotics in STEM education (pp. 103–129). Springer. https://doi.org/10.1007/978-3-319-57786-9_5
Berikan, B. (2018). Formative evaluation of "problem solving data sets" learning experience designed to improve computational thinking skills [Unpublished doctoral dissertation]. Gazi University.
Berland, M., & Wilensky, U. (2015). Comparing virtual and physical robotics environments for supporting complex systems and computational thinking. Journal of Science Education and Technology, 24(5), 628–647. https://doi.org/10.1007/s10956-015-9552-x
Bers, M. U. (2008). Blocks to robots: Learning with technology in the early childhood classroom. Teachers College Press.
Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145–157. https://doi.org/10.1016/j.compedu.2013.10.020
Blanchard, S., Freiman, V., & Lirrete-Pitre, N. (2010). Strategies used by elementary schoolchildren solving robotics-based complex tasks: Innovative potential of technology. Procedia-Social and Behavioral Sciences, 2(2), 2851–2857. https://doi.org/10.1016/j.sbspro.2010.03.427
Bower, M., Wood, L., Lai, J., Howe, C., Lister, R., Mason, R., Highfield, K., & Veal, J. (2017). Improving the computational thinking pedagogical capabilities of school teachers. Australian Journal of Teacher Education, 42(3), 53–72. http://dx.doi.org/10.14221/ajte.2017v42n3.4
Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Proceedings of the 2012 Annual Meeting of the American Educational Research Association, Canada, 1–25. https://scratched.gse.harvard.edu/ct/files/AERA2012.pdf
Büyüköztürk, Ş., Çakmak, E. K., Akgün, Ö. E., Karadeniz, Ş., & Demirel, F. (2017). Bilimsel araştırma yöntemleri [Scientific research methods]. Pegem Atıf İndeksi.
Chalmers, C. (2018). Robotics and computational thinking in primary school. International Journal of Child-Computer Interaction, 17, 93–100. https://doi.org/10.1016/j.ijcci.2018.06.005
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
Ching, Y.-H., & Hsu, Y.-C. (2024). Educational robotics for developing computational thinking in young learners: A systematic review. TechTrends, 68(3), 423–434. https://doi.org/10.1007/s11528-023-00841-1
Ching, Y.-H., Hsu, Y.-C., & Baldwin, S. (2018). Developing computational thinking with educational technologies for young learners. TechTrends, 62(6), 563–573. https://doi.org/10.1007/s11528-018-0292-7
Cohen, L., Manion, L., & Morrison, K. (2017). Research methods in education (8th Edition). Routledge. https://doi.org/10.4324/9781315456539
Constantinou, V., & Ioannou, A. (2018). Development of computational thinking skills through educational robotics. In V. Dimitrova, S. Praharaj, M. Fominykh, & H. Drachsler (Eds.), EC-TEL Practitioner Proceedings 2018: 13th European Conference on Technology Enhanced Learning (pp. 1–11). CEUR-WS. http://ceur-ws.org/Vol-2193/paper9.pdf
Curzon, P., McOwan, P. W., Plant, N., & Meagher, L. R. (2014, November). Introducing teachers to computational thinking using unplugged storytelling. In C. Schulte, M. E. Caspersen, & J. Gal-Ezer (Chairs), Proceedings of the 9th Workshop in Primary and Secondary Computing Education (pp. 89–92). ACM. https://doi.org/10.1145/2670757.2670767
Eguchi, A. (2012). Educational robotics theories and practice: Tips for how to do it right. In B. Barker, G. Nugent, N. Grandgenett, & V. Adamchuk (Eds.), Robots in K-12 education: A new technology for learning (pp. 1–30). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-4666-0182-6.ch001
Eguchi, A. (2014a). Educational robotics for promoting 21st century skills. Journal of Automation, Mobile Robotics and Intelligent Systems, 8(1), 5–11.
Eguchi, A. (2014b). Learning experience through RoboCupJunior: Promoting engineering and computational thinking skills through robotics competition. In 2014 ASEE Annual Conference & Exposition (pp. 24.852.1–24.852.18). https://www.doi.org/10.18260/1-2--20743
Eguchi, A. (2016, March). Computational thinking with educational robotics. In G. Chamblee & L. Langub (Eds.), Society for Information Technology & Teacher Education 27th International Conference (pp. 79–84). Association for the Advancement of Computing in Education. https://www.learntechlib.org/p/172306
Eguchi, A. (2017). Bringing robotics in classrooms. In M. Khine (Ed.), Robotics in STEM education (pp. 3–31). Springer. https://doi.org/10.1007/978-3-319-57786-9_1
Fesakis, G., & Serafeim, K. (2009). Influence of the familiarization with “scratch” on future teachers’ opinions and attitudes about programming and ICT in education. ACM SIGCSE Bulletin, 41(3), 258–262. https://doi.org/10.1145/1595496.1562957
Fraenkel, J., Wallen, N., & Hyun, H. (2011). How to design and evaluate research in education (8th ed.). McGraw-Hill Education.
Furber, S. (2012). Shut down or restart? The way forward for computing in UK schools. Royal Society. https://royalsociety.org/~/media/education/computing-in-schools/2012-01-12-computing-in-schools.pdf
Futschek, G., & Moschitz, J. (2011). Learning Algorithmic Thinking with Tangible Objects Eases Transition to Computer Programming. In Lecture notes in computer science (pp. 155–164). https://doi.org/10.1007/978-3-642-24722-4_14
George, D., & Mallery, P. (2019). IBM SPSS statistics 26 step by step: A simple guide and reference (16th ed.). Routledge. https://doi.org/10.4324/9780429056765
Grover, S., & Pea, R. (2018). Computational thinking: A competency whose time has come. In S. Sentance, E. Barendsen, & C. Schulte (Eds.), Computer science education: Perspectives on teaching and learning in school (pp. 19–38). Bloomsbury Academic. https://www.doi.org/10.5040/9781350057142.ch-003
Gülbahar, Y., Kert, S. B., & Kalelioğlu, F. (2019). Bilgi işlemsel düşünme becerisine yönelik özYeterlik algısı ölçeği: Geçerlik ve güvenirlik çalışması [The self-efficacy perception scale for computational thinking skill: Validity and reliability study]. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 10(1), 1–29. https://turcomat.org/index.php/turkbilmat/article/view/194
Harel, I. E., & Papert, S. E. (1991). Constructionism. Ablex Publishing.
Hsu, T.-C., Chang, S.-C., & Hung, Y.-T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126, 296–310. http://doi.org/10.1016/j.compedu.2018.07.004
Ioannou, A., & Makridou, E. (2018). Exploring the potentials of educational robotics in the development of computational thinking: A summary of current research and practical proposal for future work. Education and Information Technologies, 23(6), 2531–2544. https://doi.org/10.1007/s10639-018-9729-z
Israel, M., Pearson, J. N., Tapia, T., Wherfel, Q. M., & Reese, G. (2015). Supporting all learners in school-wide computational thinking: A cross-case qualitative analysis. Computers & Education, 82, 263–279. https://doi.org/10.1016/j.compedu.2014.11.022
International Society for Technology in Education [ISTE] & Computer Science Teachers Association [CSTA]. (2011). Computational Thinking in K–12 Education: Leadership Toolkit. https://cdn.iste.org/www-root/ct-documents/ct-leadershipt-toolkit.pdf?sfvrsn=4
Karaahmetoglu, K., & Korkmaz, Ö. (2019). The effect of project-based Arduino educational robot applications on students’ computational thinking skills and their perception of basic STEM skill levels. Participatory Educational Research, 6(2), 1–14. https://doi.org/10.17275/per.19.8.6.2
Karp, T., & Maloney, P. (2013). Exciting young students in grades K–8 about STEM through an afterschool robotics challenge. American Journal of Engineering Education, 4(1), 39–54. https://files.eric.ed.gov/fulltext/EJ1057112.pdf
Kazakoff, E. R., Sullivan, A., & Bers, M. U. (2013). The effect of a classroom-based intensive robotics and programming workshop on sequencing ability in early childhood. Early Childhood Education Journal, 41(4), 245–255. https://doi.org/10.1007/s10643-012-0554-5
Kert, S. B., Erkoç, M. F., & Yeni, S. (2020). The effect of robotics on six graders’ academic achievement, computational thinking skills and conceptual knowledge levels. Thinking Skills and Creativity, 38, Article 100714. https://doi.org/10.1016/j.tsc.2020.100714
Koh, K. H., Basawapatna, A., Bennett, V., & Repenning, A. (2010). Towards the automatic recognition of computational thinking for adaptive visual language learning. In C. Hundhausen, E. Pietriga, P. Díaz, & M. B. Rosson (Eds.), Proceedings: 2010 IEEE symposium on visual languages and human-centric computing (pp. 59–66). IEEE. https://doi.org/10.1109/VLHCC.2010.17
Lee, I., Martin, F., Denner, J., Coulter, B., Allan, W., Erickson, J., Malyn-Smith, J., & Werner, L. (2011). Computational thinking for youth in practice. ACM Inroads, 2(1), 32–37. https://users.soe.ucsc.edu/~linda/pubs/ACMInroads.pdf
Leonard, J., Buss, A., Gamboa, R., Mitchell, M., Fashola, O. S., Hubert, T., & Almughyirah, S. (2016). Using robotics and game design to enhance children’s self-efficacy, STEM attitudes, and computational thinking skills. Journal of Science Education and Technology, 25(6), 860–876. https://doi.org/10.1007/s10956-016-9628-2
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://psycnet.apa.org/doi/10.1016/j.chb.2014.09.012
McMillan, J. H., & Schumacher, S. (2013). Research in education: Evidence-based inquiry (7th ed.). Pearson.
Mingo, W. D. (2013). The effects of applying authentic learning strategies to develop computational thinking skills in computer literacy students [Doctoral dissertation, Wayne State University]. Digital Commons @ Wayne State. https://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=1673&context=oa_dissertations
Mitnik, R., Nussbaum, M., & Soto, A. (2008). An autonomous educational mobile robot mediator. Autonomous Robots, 25(4), 367–382. https://doi.org/10.1007/s10514-008-9101-z
Morelli, R., De Lanerolle, T., Lake, P., Limardo, N., Tamotsu, E., & Uche, C. (2011, March). Can android app inventor bring computational thinking to K-12. In T. J. Cortina, E. L. Walker, L. Smith King, D. R. Musicant, & L. I. McCann (Eds.), Proceedings of the 42nd ACM technical symposium on computer science education (SIGCSE’11) (pp. 1–6). ACM. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=dcc775e72f78e102b611bc3f5561933711bd1fad
Noh, J., & Lee, J. (2020). Effects of robotics programming on the computational thinking and creativity of elementary school students. Educational Technology Research and Development, 68(1), 463–484. https://doi.org/10.1007/s11423-019-09708-w
Nugent, G., Barker, B., Grandgenett, N., & Welch, G. (2016). Robotics camps, clubs, and competitions: Results from a US robotics project. Robotics and Autonomous Systems, 75, 686–691. https://doi.org/10.1016/j.robot.2015.07.011
Pala, F. K., & Mıhçı 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
Papert, S. A. (1980). Mindstorms: Children, computers, and powerful ideas. Basic Books. https://dl.acm.org/doi/pdf/10.5555/1095592
Pedhazur, E. J., & Schmelkin, L. P. (2013). Measurement, design, and analysis: An integrated approach. Psychology Press. https://doi.org/10.4324/9780203726389
Perlis, A. (1962). The computer in the university. In M. Greenberger (Ed.), Computers and the world of the future (pp. 180–219). MIT Press.
Petre, M., & Price, B. (2004). Using robotics to motivate “back door” learning. Education and Information Technologies, 9(2), 147–158. https://doi.org/10.1023/B:EAIT.0000027927.78380.60
Piaget, J. (1936). Origins of intelligence in the child. London: Routledge & Kegan Paul.
Psycharis, S., & Kallia, M. (2017). The effects of computer programming on high school students’ reasoning skills and mathematical self-efficacy and problem solving. Instructional Science, 45(5), 583–602. https://doi.org/10.1007/s11251-017-9421-5
Rubinstein, A., & Chor, B. (2014). Computational thinking in life science education. PLoS computational biology, 10(11), Article e1003897. https://doi.org/10.1371/journal.pcbi.1003897
Selby, C., & Woollard, J. (2013). Computational thinking: The developing definition (356481). University of Southampton Institutional Repository. https://eprints.soton.ac.uk/356481/
Sullivan, F. R., & Heffernan, J. (2016). Robotic construction kits as computational manipulatives for learning in the STEM disciplines. Journal of Research on Technology in Education, 48(2), 105–128. https://doi.org/10.1080/15391523.2016.1146563
Sun, L., Hu, L., & Zhou, D. (2022). Programming attitudes predict computational thinking: Analysis of differences in gender and programming experience. Computers & Education, 181, Article 104457. https://doi.org/10.1016/j.compedu.2022.104457
Sysło, M. M., & Kwiatkowska, A. B. (2013, February). Informatics for all high school students. In I. Diethelm & R. T. Mittermeir (Eds.), Informatics in schools. Sustainable informatics education for pupils of all ages: 6th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (pp. 43–56). Springer. https://doi.org/10.1007/978-3-642-36617-8_4
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
Wing, J. M. (2011). Research notebook: Computational thinking—What and why. The Link Magazine, 6, 20–23. https://www.cs.cmu.edu/~CompThink/resources/TheLinkWing.pdf
Witherspoon, E. B., Higashi, R. M., Schunn, C. D., Baehr, E. C., & Shoop, R. (2017). Developing computational thinking through a virtual robotics programming curriculum. ACM Transactions on Computing Education (TOCE), 18(1), Article 4, 1–20. https://doi.org/10.1145/3104982
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
Yilmaz Ince, E., & Koc, M. (2021). The consequences of robotics programming education on computational thinking skills: An intervention of the Young Engineer’s Workshop (YEW). Computer Applications in Engineering Education, 29(1), 191–208. https://doi.org/10.1002/cae.22321
Téléchargements
Publié-e
Numéro
Rubrique
Licence
© Serhat Altıok, Memet Üçgül 2024
Cette œuvre est sous licence Creative Commons Attribution - Pas d'Utilisation Commerciale 4.0 International.
Droits d’auteur
Les auteurs conservent le droit d'auteur et accordent le droit de la première publication de la revue avec le travail simultanément sous une licence Creative Commons Attribution - Pas d’Utilisation Commerciale 4.0 International (CC-BY-NC 4.0) qui permet aux autres de partager le travail avec une reconnaissance de la paternité de l'œuvre et la publication initiale dans ce journal.