Development and Evaluation of Unplugged Algorithmic Thinking Activities Training Program for In-Service Primary School Teachers

Year 2022, Volume: 7 Issue: 2, 222 - 234, 06.07.2022

Hasan Çakır , Ömer Faruk İslim , Ebru Solmaz , Burcu Berikan , Fahri Yılmaz

https://doi.org/10.53850/joltida.1036460

Cited By: 1

Abstract

The aim of this study is to evaluate a professional development program applied to primary school teachers for unplugged algorithmic thinking activities and to improve it based on this evaluation. In this context, data were collected for the improvement of the program by consulting the opinions of the teachers. The professional development program was implemented in 3 different groups, respectively and improved in each group. Teachers' opinions were collected for each group in line with the Kirkpatrick Level 1 assessment approach. The reactions and likes of the teachers participating in the training courses towards the training program are included. In this way, it is aimed that the data obtained will guide the development of the training program. The measurement tool consists of 6 parts and includes closed-ended questions designed for the purposes of evaluating the educators, course components, implementation, physical environment, and teaching materials. The Kruskal-Wallis non-parametric test was used as an analysis method to determine whether there was a significant difference between the groups. In the study, the components in which significant differences emerged between the groups in the scores given by the participants were discovered, and the training program was improved after the first and second trainings in line with these findings.

Keywords

unplugged algorithmic thinking, professional development programs, primary school teachers, Kirkpatrick educational evaluation model

References

• Ah-Nam, L., & Osman, K. (2017). Developing 21st century skills through a constructivist-constructionist learning environment. K-12 STEM Education, 3(2), 205-216.
• Ananiadou, K. and M. Claro (2009), “21st Century Skills and Competences for New Millennium Learners in OECD Countries”, OECD Education Working Papers, No. 41, OECD Publishing. http://dx.doi.org/10.1787/218525261154
• Bey, A., & Bensebaa, T. (2011, April). Algo+, an assessment tool for algorithmic competencies. In 2011 IEEE Global Engineering Education Conference (EDUCON) (pp. 941-946). IEEE.
• Brackmann, C. P., Román-González, M., Robles, G., Moreno-León, J., Casali, A., & Barone, D. (2017, November). Development of computational thinking skills through unplugged activities in primary school. In Proceedings of the 12th Workshop on Primary and Secondary Computing Education (pp. 65-72).
• Conde, M. Á., Fernández-Llamas, C., Rodríguez-Sedano, F. J., Guerrero-Higueras, Á. M., Matellán-Olivera, V., & García-Peñalvo, F. J. (2017, October). Promoting Computational Thinking in K-12 students by applying unplugged methods and robotics. In Proceedings of the 5th International Conference on Technological Ecosystems for Enhancing Multiculturality (pp. 1-6).
• Curzon, P., Dorling, M., Ng, T., Selby, C., & Woollard, J. (2014). Developing computational thinking in the classroom: A framework. https://eprints.soton.ac.uk/369594/1/DevelopingComputationalThinkingInTheClassroomaFramework.pdf
• Curzon, P., McOwan, P. W., Plant, N., & Meagher, L. R. (2014, November). Introducing teachers to computational thinking using unplugged storytelling. In Proceedings Of The 9th Workshop İn Primary And Secondary Computing Education (pp. 89-92).
• Dede, C. (2010). Comparing frameworks for 21st century skills. 21st century skills: Rethinking how students learn, 20(2010), 51-76.
• Demirel, Ö. (1992). Türkiye'de program geliştirme uygulamaları. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 7, 27-43.
• Dochy, F., Segers, M., Van den Bossche, P., & Gijbels, D. (2003). Effects of problem-based learning: A meta-analysis. Learning and Instruction, 13(5), 533-568.
• Dolmans, D. H., Loyens, S. M., Marcq, H., & Gijbels, D. (2016). Deep and surface learning in problem-based learning: A review of the literature. Advances in Health Sciences Education, 21(5), 1087-1112.
• Finegold, D., & Notabartolo, A. S. (2010). 21st century competencies and their impact: An interdisciplinary literature review. https://hewlett.org/library/21st-century-competencies-impact-interdisciplinary-literature-review/
• Futschek, G. (2006, November). Algorithmic thinking: the key for understanding computer science. In International Conference on Informatics in Secondary Schools-Evolution and Perspectives (pp. 159-168). Berlin, Heidelberg: Springer,.
• Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235-266.
• 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.
• Hunkins, F. P. & Hammill, P. A. (1994). Beyond Tyler and Taba: Reconceptualizing the curriculum process. Peabody Journal of Education, 69(3), 4-18.
• Frick, T. W. & Reigeluth, C. M. (1999). Formative research: A methodology for creating and improving design theories. In C.M. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory, (pp, 633-652). Mahwah, NJ: Lawrence Erlbaum Associates.
• Jagušt, T., Krzic, A. S., Gledec, G., Grgić, M., & Bojic, I. (2018, October). Exploring different unplugged game-like activities for teaching computational thinking. In 2018 IEEE Frontiers in Education Conference (FIE) (pp. 1-5). IEEE.
• Kirkpatrick, D., & Kirkpatrick, J. (2006). Evaluating training programs: The four levels. Berrett-Koehler Publishers.
• Kivunja, C. (2014). Do you want your students to be job-ready with 21st century skills? Change pedagogies: A pedagogical paradigm shift from Vygotskyian social constructivism to critical thinking, problem solving and Siemens' digital connectivism. International Journal of Higher Education, 3(3), 81-91.
• Lombardi, M. M. (2007). Authentic learning for the 21st century: An overview. Educause Learning Initiative, 1(2007), 1-12.
• Looi, C. K., How, M. L., Longkai, W., Seow, P., & Liu, L. (2018). Analysis of linkages between an unplugged activity and the development of computational thinking. Computer Science Education, 28(3), 255-279.
• Luna Scott, C. (2015). The Futures of Learning 3: What kind of pedagogies for the 21st century? UNESCO Education Research and Foresight, Paris. [ERF Working Papers Series, No. 15].
• Martin, J.P. (2018). Skills for the 21st Century: Funding and Policy Lessons from the OECD Survey of Adult Skills. OECD Education Working Papers, no. 166. Paris: OECD.
• Milli Eğitim Bakanlığı (MEB) (2018). Güçlü Yarınlar İçin 2023 Eğitim Vizyonu. Ankara: MEB.
• Moylan, W. A. (2008). Learning by project: Developing essential 21st century skills using student team projects. International Journal of Learning, 15(9), 287-292.
• National Research Council, (2013). Nonresponse in social science surveys: A research agenda: National Academies Press.
• Norman, G. T., & Schmidt, H. G. (1992). The psychological basis of problem-based learning: A review of the evidence. Academic Medicine, 67(9), 557-565.
• OECD. (2018). The future of education and skills: Education 2030. https://www.oecd.org/education/2030/E2030%20Position%20Paper%20(05.04.2018).pdf
• Ozcinar, H. (2018). A brief discussion on incentives and barriers to computational thinking education. In H. Ozcinar, G. Wong, & H. T. Ozturk (Eds.). Teaching Computational Thinking in Primary Education (pp. 1-17). IGI Global.
• Saavedra, A. R., & Opfer, V. D. (2012). Learning 21st-century skills requires 21st-century teaching. Phi Delta Kappan, 94(2), 8–13.
• Savery, J. R. (2006). Overview of problem-based learning: Definition and discussion. The Interdisciplinary Journal of Problem-based Learning, 1 (1), 9-20.
• Savery, J. R. (2015). Overview of problem-based learning: Definitions and distinctions. Essential readings in problem-based learning: Exploring and extending the legacy of Howard S. Barrows, 9, 5-15.
• Savery, J. R., & Duffy, T. M. (1995). Problem based learning: An instructional model and its constructivist framework. Educational Technology, 35(5), 31-38.
• Schmidt, H. G., Rotgans, J. I., & Yew, E. H. (2011). The process of problem‐based learning: what works and why. Medical Education, 45(8), 792-806.
• Shelton, C. (2016). Time to plug back in? The role of “unplugged” computing in primary schools. ITTE Newsletter, (2016).
• Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142-158.
• Tabesh, Y. (2017). Computational thinking: A 21st century skill. Olympiads in Informatics, 11, 65-70.
• Tuparova, D. (2019). Possibilities for development of algorithmic thinking through game based learning and unplugged activities in primary school. Computer Science and Education in Computer Science, 15(1), 80-84.
• Vernon, D. T. & Blake, R. L. (1993). Does problem-based learning work? A meta-analysis of evaluative research. Academic Medicine, 68(7), 550-563.
• Voogt, J., & Roblin, N. P. (2012). A comparative analysis of international frameworks for 21st century competences: Implications for national curriculum policies. Journal of Curriculum Studies, 44(3), 299-321.
• Voskoglou, M. G., & Buckley, S. (2012). Problem solving and computational thinking in a learning environment. Egyptian Computer Science Journal, 36(4), 28-46.
• Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
• Wong, G. K. & Jiang, S. (2018, December). Computational thinking education for children: Algorithmic thinking and debugging. In 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE) (pp. 328-334). IEEE.
• Yadav, A., Stephenson, C., & Hong, H. (2017). Computational thinking for teacher education. Communications of the ACM, 60(4), 55-62.