Résumés
Abstract
In recent years, computational thinking has garnered increased attention as an essential problem-solving skill. One of the methods to develop students’ computational thinking skills is robotic coding activities. This study sought to investigate the impact of robotic coding activities on the self-efficacy perceptions of secondary school students’ computational thinking skills. A one-group pretest-posttest quasi-experimental design was employed, involving 32 secondary school students. These students, organized in groups of four, engaged in hands-on robotic coding activities using Lego Mindstorms EV3 Education robots over a total of 20 hours. Data were collected before and after the robotic coding activities using the Self-Efficacy Perception Scale for Computational Thinking Skills (SEPSCTS) instrument, comprising 36 items categorized into five factors. The data were analyzed using paired samples t-tests and analysis of covariance (ANCOVA). The results demonstrated a significant increase in students’ self-efficacy perceptions of computational thinking skills following the activities, with this increase observed consistently across genders. Finally, the challenges encountered during research and practice were reported, along with the study’s limitations, to inform future research endeavours.
Keywords:
- computational thinking,
- perception,
- robotic coding,
- self-efficacy
Résumé
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.
Mots-clés :
- pensée computationnelle,
- perception,
- codage robotique,
- auto efficacité
Parties annexes
Bibliography
- 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