Unplugged Coding Activities for Early Childhood Problem-Solving Skills

Problem solving skills are very important in supporting social development. Children with problem solving skills can build healthy relationships with their friends, understand the emotions of those around them, and see events with other people's perspectives. The purpose of this study was to determine the implementation of playing unplugged coding programs in improving early childhood problem solving skills. This study used a classroom action research design, using the Kemmis and Taggart cycle models. The subjects of this study were children aged 5-6 years in Shafa Marwah Kindergarten. Research can achieve the target results of increasing children's problem-solving abilities after going through two cycles. In the first cycle, the child's initial problem-solving skills was 67.5% and in the second cycle it increased to 80.5%. The initial skills of children's problem-solving increases because children tend to be enthusiastic and excited about the various play activities prepared by the teacher. The stimulation and motivation of the teacher enables children to find solutions to problems faced when carrying out play activities. So, it can be concluded that learning unplugged coding is an activity that can attract children's interest and become a solution to bring up children's initial problem-solving abilities. Keywords: Early Childhood, Unplugged Coding, Problem solving skills References: Akyol-Altun, C. (2018). Algorithm and coding education in pre-school teaching program integration the efectiveness of problem-solving skills in students. Angeli, C., Smith, J., Zagami, J., Cox, M., Webb, M., Fluck, A., & Voogt, J. (2016). A K-6 Computational Thinking Curriculum Framework: Implications for Teacher Knowledge. Educational Technology & Society, 12. Anlıak, Ş., & Dinçer, Ç. (2005). Farklı eğitim yaklaşımları uygulayan okul öncesi eğitim kurumlarına devam eden çocukların kişilerarası problem çözme becerilerinin değerlendirilmesi. Ankara Üniversitesi Eğitim Bilimleri Fakülte Dergis. Aranda, G., & Ferguson, J. P. (2018). Unplugged Programming: The future of teaching computational thinking? Pedagogika, 68(3). https://doi.org/10.14712/23362189.2018.859 Arinchaya Threekunprapa. (2020). Patterns of Computational Thinking Development while Solving Unplugged Coding Activities Coupled with the 3S Approach for Self_Directed Learning. European Journal of Educational Research, 9(3), 1025–1045. Arı, M. (2003). Türkiye’de erken çocukluk eğitimi ve kalitenin önemiNo Title. Erken Çocuklukta Gelişim ve Eğitimde Yeni Yaklaşımlar. Armoni, M. (2012). Teaching CS in kindergarten: How early can the pipeline begin? ACM Inroads, 3(4), 18–19. https://doi.org/10.1145/2381083.2381091 Aydoğan, Y. (2004). İlköğretim ikinci ve dördüncü sınıf öğrencilerine genel problem çözme becerilerinin kazandırılmasında eğitimin etkisinin incelenmesi. Bell, T., Alexander, J., Freeman, I., & Grimley, M. (2009). Computer Science Unplugged: School students doing real computing without computers. 10. Berk, L. E. (2013). Bebekler ve çocuklar: Doğum öncesinden orta çocukluğa. N. Işıkoğlu Erdoğan, Çev. Bers, M. U. (2018). Coding, playgrounds, and literacy in early childhood education: The devel_opment of KIBO robotics and Scratch Jr. IEEE. Brackmann, C. P., Moreno-León, J., Román-González, M., Casali, A., Robles, G., & Barone, D. (2017). Development of computational thinking skills through unplugged activities in primary school. ACM International Conference Proceeding Series, 65–72. https://doi.org/10.1145/3137065.3137069 Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. 25. Deek, F. P. (1999). The software process: A parallel approach through problem solving and program development. Computer Science Education. Demi̇Rer, V., & Sak, N. (2016). Programming Education and New Approaches Around the World and in Turkey. 26. Dereli-İman. (2014). Değerler eğitimi programının 5-6 yaş çocukların sosyal gelişimine etkisi: Sosyal beceri, psiko-sosyal gelişim ve sosyal problem çözme becerisi. Kuram ve Uygulamada Eğitim Bilimleri. Doğru, M., Arslan, A., & Şeker, F. (2011). Okul öncesinde uygulanan fen etkinliklerinin 5-6 yaş çocukların problem çözme becerilerine etkisi. Uluslararası Türkiye Eğiti Araştırmaları Kongresi. Erickson, A. S. G., Noonan, P., Zheng, C., & Brussow, J. A. (2015). The relationship between self-determination and academic achievement for adolescents with intellectual disabilities. Research in Developmental Disabilities, 36, 45–54. Fee, S. B., & Holland-Minkley, A. M. (2010). Teaching computer science through problems, not solutions. Computer Science Education, 20(2), 129–144. https://doi.org/10.1080/08993408.2010.486271 Futschek, G., & Moschitz, J. (2010). Developing algorithmic thinking by inventing and playing algo_rithms. Gretter, S., & Yadav, A. (2016). Computational Thinking and Media & Information Literacy: An Integrated Approach to Teaching Twenty-First Century Skills. Grover, S., & Pea, R. (2013). Computational thinking in k-12: A review of the state of the field. Educational Researcher. Harrop, W. (2018). Coding for children and young adults in libraries: A practical guide for librarians. 45. Hazzan, O., Lapidot, T., & Ragonis, N. (2011). Guide to Teaching Computer Science. Springer London. https://doi.org/10.1007/978-0-85729-443-2 Horn, M. S., Crouser, R. J., & Bers, M. U. (2012). Tangible interaction and learning: The case for a hybrid approach. Personal and Ubiquitous Computing, 16(4), 379–389. https://doi.org/10.1007/s00779-011-0404-2 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. https://doi.org/10.1016/j.compedu.2018.07.004 Ismail, M. N., Ngah, N. A., & Umar, I. N. (2010). Instructional strategy in the teaching of computer programming: A need assessment analyses. TOJET: The Turkish Online Journal of Educational Technology. Ismail, M. N., Ngah, N. A., & Umar, I. N. (2010). Instructional Strategy in The Teaching of Computer Programming: A Need Assessment Analyses. The Turkish Online Journal of Educational Technology, 9(2), 7. Jitendra, A. K., Petersen-Brown, S., Lein, A. E., Zaslofsky, A. F., Kunkel, A. K., Jung, P.-G., & Egan, A. M. (2013). Teaching Mathematical Word Problem Solving: The Quality of Evidence for Strategy Instruction Priming the Problem Structure. Journal of Learning Disabilities, 48(1), 51–72. https://doi.org/10.1177/0022219413487408 Joohi Lee. (2019). Coding in early childhood. Contemporary Issues in Early Childhood. Kalyuga, S., Renkl, A., & Paas, F. (2010). Facilitating flexible problem solving: A cognitive load perspective. Educational Psychology Review. Kemmis, S., McTaggart, R., & Nixon, R. (2014). The Action Research Planner. Springer Singapore. https://doi.org/10.1007/978-981-4560-67-2 Kesicioğlu, O. S. (2015). Okul öncesi dönem çocukların kişilerarası problem çözme becerilerinin incelenmesi. Eğitim ve Bilim. Koksal Akyol, A. ve Didin, E. (2016). Ahlak gelisimi [Moral development]. In Cocuk Gelisimi icinde [In Child Development]. Lazakidou, G., & Retalis, S. (2010). Using computer supported collaborative learning strategies for helping students acquire self-regulated problem-solving skills in mathematics. Computers & Education, 54(1), 3–13. https://doi.org/10.1016/j.compedu.2009.02.020 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. https://doi.org/10.1080/08993408.2018.1533297 McClure, E. R., Guernsey, L., Clements, D. H., Bales, S. N., Nichols, J., Kendall-Taylor, N., & Levine, M. H. (2017). Grounding science, technology, engineering, and math education in early childhood. 68. McLennan, D. P. (2017). Creating coding stories and games. Teaching Young Children. McNerney, TimothyS. (2004). From turtles to Tangible Programming Bricks: Explorations in physical language design. Personal and Ubiquitous Computing, 8(5). https://doi.org/10.1007/s00779-004-0295-6 Mittermeir, R. T. (2013). Algorithmics for preschoolers—A contradiction? Montemayor, J., Druin, A., Chipman, G., Farber, A., & Guha, M. L. (2004). Tools for children to create physical interactive storyrooms. Computers in Entertainment, 2(1), 12–12. https://doi.org/10.1145/973801.973821 Pane, J. F. (2002). A Programming System for Children that is Designed for Usability. 204. Papanastasiou, G., Drigas, A., Skianis, C., Lytras, M., & Papanastasiou, E. (2018). Virtual and augmented reality effects on K-12, higher and tertiary education students’ twenty-29 first century skills. Pellegrino, J. W., & Hilton, M. L. (2012). Education for Life and Work: Developing Transferable Knowledge and Skills in the 21st Century. Pila, S., Aladé, F., Sheehan, K. J., Lauricella, A. R., & Wartella, E. A. (2019). Learning to code via tablet applications: An evaluation of Daisy the Dinosaur and Kodable as learning tools for young children. Computers & Education, 128, 52–62. https://doi.org/10.1016/j.compedu.2018.09.006 Root, J., Saunders, A., Spooner, F., & Brosh, C. (2017). Teaching Personal Finance Mathematical Problem Solving to Individuals with Moderate Intellectual Disability. Career Development and Transition for Exceptional Individuals, 40(1), 5–14. https://doi.org/10.1177/2165143416681288 Scanlan, D. A. (1989). Structured flowcharts outperform pseudocode: An experimental comparison. IEEE Software, 6(5), 28–36. https://doi.org/10.1109/52.35587 Sheehan, K. J., Pila, S., Lauricella, A. R., & Wartella, E. A. (2019). Parent-child interaction and children’s learning from a coding application. Computers & Education, 140, 103601. https://doi.org/10.1016/j.compedu.2019.103601 Shute, V. J., Sun, C., & Asbell-clarke, J. (2017). Demystifying computational thinking. Educational Research Review. Sigelman, C. K., & Rider, E. A. (2012). Life-span Human Development (7th ed.). Cengage Learning. Sullivan, A., & Bers, M. U. (2016). Robotics in the early childhood classroom: Learning outcomes from an 8-week robotics curriculum in pre-kindergarten through second grade. International Journal of Tech_nology and Design Education, 26, 3–20. Sullivan, A. A., Bers, M. U., & Mihm, C. (2017). International conference on com_putational thinking education. Imagining, Playing, and Coding with KIBO: Using Robot_ics to Foster Computational Thinking in Young ChildreImagining, Playing, and Coding with KIBO: Using Robot_ics to Foster Computational Thinking in Young Children. Sullivan, A., Elkin, M., & Bers, M. U. (2015). KIBO robot demo: Engaging young children in programming and engineering. Proceedings of the 14th International Conference on Interaction Design and Children, 418–421. https://doi.org/10.1145/2771839.2771868 Threekunprapa, A., & Yasri, P. (n. d.). (2020). The role of augmented reality based unplugged computer programming approach in the effectiveness of computational thinking. Uysal, A. & Kaya-Balkan, İ. (2015). Sosyal beceri eğitimi alan ve almayan okul öncesi çocukların, sosyal beceri ve benlik kavramı düzeyleri açısından karşılaştırılması. Psikoloji Çalışmaları. Vorderman, C. (2017). Computer coding for kids: A unique step-by-step visual guide, from binary code to building games. Voronina, L. V., Sergeeva, N. N., & Utyumova, E. A. (2016). Development of algorithm skills in preschool children. Procedia-Social and Behavioral Sciences, 233, 155-159. Wang, D., Han, H., Zhan, Z., Xu, J., Liu, Q., & Ren, G. (2015). A problem solving oriented intelligent tutoring system to improve students’ acquisition of basic computer skills. Comput. Educ., 81, 102–112. Wang, D., Zhang, C., & Wang, H. (2010). Proceedings of the 10th international conference on interaction design and children. T-Maze: A Tangible Programming Tool for Children. Wang, Danli, Zhang, C., & Wang, H. (2011). T-Maze: A tangible programming tool for children. Proceedings of the 10th International Conference on Interaction Design and Children - IDC ’11, 127–135. https://doi.org/10.1145/1999030.1999045 Woods, D. R., Hrymak, A. N., Marshall, R. R., Wood, P. E., Crowe, C. M., Hoffman, T. W., Wright, J. D., Taylor, P. A., Woodhouse, K. A., & Bouchard, C. G. K. (1997). Developing Problem Solving Skills: The McMaster Problem Solving Program. Journal of Engineering Education, 86(2), 75–91. https://doi.org/10.1002/j.2168-9830.1997.tb00270.x Yıldırım, A. (2014). Okul öncesinde yaratıcı problem çözme etkinliklerinin yaratıcılığa etkisi (5 yaş örneği). Hacettepe University, Ankara, Turkey. Yohanes. (2018). Mengajarkan Computational Thinking dan Coding Pada Anak-Anak. Amazing Grace. https://blog.compactbyte.com/2018/05/26/mengajarkan-computational-thinking-dan-coding-pada-anak-anak/ Yu, K.-C., Fan, S.-C., & Lin, K.-Y. (2015). Enhancing Students’ Problem-Solving Skills Through Context-Based Learning. International Journal of Science and Mathematics Education, 13(6), 1377–1401. https://doi.org/10.1007/s10763-014-9567-4 Yuksel, H. S. (2019). Experiences of Prospective Physical Education Teachers on Active Gaming within the Context of School-Based Physical Activity. European Journal of Educational Research, 8(1). https://doi.org/10.12973/eu-jer.8.1.199 Zvarych, I., Kalaur, S. M., Prymachenko, N. M., Romashchenko, I. V., & Romanyshyna, O. Ia. (2019). Gamification as a Tool for Stimulating the Educational Activity of Students of Higher Educational Institutions of Ukraine and the United States. European Journal of Educational Research, 8(3). https://doi.org/10.12973/eu-jer.8.3.875 &nbsp

em Where do I begin? A problem solving approach to teaching functional programming

This paper introduces a problem solving method for teaching functional programming, based on Polya's `How To Solve It', an introductory investigation of mathematical method. We first present the language independent version, and then show in particular how it applies to the development of programs in Haskell. The method is illustrated by a sequence of examples and a larger case study

Plan-based delivery composition in intelligent tutoring systems for introductory computer programming

In a shell system for the generation of intelligent tutoring systems, the instructional model that one applies should be variable independent of the content of instruction. In this article, a taxonomy of content elements is presented in order to define a relatively content-independent instructional planner for introductory programming ITS's; the taxonomy is based on the concepts of programming goals and programming plans. Deliveries may be composed by the instantiation of delivery templates with the content elements. Examples from two different instructional models illustrate the flexibility of this approach. All content in the examples is taken from a course in COMAL-80 turtle graphics

Teaching programming with computational and informational thinking

Computers are the dominant technology of the early 21st century: pretty well all aspects of economic, social and personal life are now unthinkable without them. In turn, computer hardware is controlled by software, that is, codes written in programming languages. Programming, the construction of software, is thus a fundamental activity, in which millions of people are engaged worldwide, and the teaching of programming is long established in international secondary and higher education. Yet, going on 70 years after the first computers were built, there is no well-established pedagogy for teaching programming. There has certainly been no shortage of approaches. However, these have often been driven by fashion, an enthusiastic amateurism or a wish to follow best industrial practice, which, while appropriate for mature professionals, is poorly suited to novice programmers. Much of the difficulty lies in the very close relationship between problem solving and programming. Once a problem is well characterised it is relatively straightforward to realise a solution in software. However, teaching problem solving is, if anything, less well understood than teaching programming. Problem solving seems to be a creative, holistic, dialectical, multi-dimensional, iterative process. While there are well established techniques for analysing problems, arbitrary problems cannot be solved by rote, by mechanically applying techniques in some prescribed linear order. Furthermore, historically, approaches to teaching programming have failed to account for this complexity in problem solving, focusing strongly on programming itself and, if at all, only partially and superficially exploring problem solving. Recently, an integrated approach to problem solving and programming called Computational Thinking (CT) (Wing, 2006) has gained considerable currency. CT has the enormous advantage over prior approaches of strongly emphasising problem solving and of making explicit core techniques. Nonetheless, there is still a tendency to view CT as prescriptive rather than creative, engendering scholastic arguments about the nature and status of CT techniques. Programming at heart is concerned with processing information but many accounts of CT emphasise processing over information rather than seeing then as intimately related. In this paper, while acknowledging and building on the strengths of CT, I argue that understanding the form and structure of information should be primary in any pedagogy of programming

Instructional strategies and tactics for the design of introductory computer programming courses in high school

This article offers an examination of instructional strategies and tactics for the design of introductory computer programming courses in high school. We distinguish the Expert, Spiral and Reading approach as groups of instructional strategies that mainly differ in their general design plan to control students' processing load. In order, they emphasize topdown program design, incremental learning, and program modification and amplification. In contrast, tactics are specific design plans that prescribe methods to reach desired learning outcomes under given circumstances. Based on ACT* (Anderson, 1983) and relevant research, we distinguish between declarative and procedural instruction and present six tactics which can be used both to design courses and to evaluate strategies. Three tactics for declarative instruction involve concrete computer models, programming plans and design diagrams; three tactics for procedural instruction involve worked-out examples, practice of basic cognitive skills and task variation. In our evaluation of groups of instructional strategies, the Reading approach has been found to be superior to the Expert and Spiral approaches

inPractice: a practical nursing package for clinical decisions

This paper examines the recent development of a computer-assisted learning program-in Practice-at the School of Health Science, in the University of Wales Swansea. The project, which began in 2001, was developed in close collaboration with The Meningitis Trust, the aim being to produce a software package to increase nursing students knowledge of meningitis-related illnesses, and to enhance their decision-making and problem-solving skills by using lifelike scenarios. It incorporates two multimedia meningitis modules incorporating the use of text, film, and sound, in which students are presented with information about the illness (symptoms, treatment etc.), and are required to use their knowledge to make decisions at various key points. A general discussion of decision-making theories and CAL design principles is presented, which has provided a foundation for the main design aspects of the package. This is followed by an outline of how the program was created to promote students application of knowledge and their decision-making and problem-solving skills. Results from an evaluation questionnaire are presented. Consideration is also given as to how the program can be extended

Hiding in Plain Sight: Identifying Computational Thinking in the Ontario Elementary School Curriculum

Given a growing digital economy with complex problems, demands are being made for education to address computational thinking (CT) – an approach to problem solving that draws on the tenets of computer science. We conducted a comprehensive content analysis of the Ontario elementary school curriculum documents for 44 CT-related terms to examine the extent to which CT may already be considered within the curriculum. The quantitative analysis strategy provided frequencies of terms, and a qualitative analysis provided information about how and where terms were being used. As predicted, results showed that while CT terms appeared mostly in Mathematics, and concepts and perspectives were more frequently cited than practices, related terms appeared across almost all disciplines and grades. Findings suggest that CT is already a relevant consideration for educators in terms of concepts and perspectives; however, CT practices should be more widely incorporated to promote 21st century skills across disciplines. Future research would benefit from continued examination of the implementation and assessment of CT and its related concepts, practices, and perspectives

Automation and schema acquisition in learning elementary computer programming: Implications for the design of practice

Two complementary processes may be distinguished in learning a complex cognitive skill such as computer programming. First, automation offers task-specific procedures that may directly control programming behavior, second, schema acquisition offers cognitive structures that provide analogies in new problem situations. The goal of this paper is to explore what the nature of these processes can teach us for a more effective design of practice. The authors argue that conventional training strategies in elementary programming provide little guidance to the learner and offer little opportunities for mindful abstraction, which results in suboptimal automation and schema acquisition. Practice is considered to be most beneficial to learning outcomes and transfer under strict conditions, in particular, a heavy emphasis on the use of worked examples during practice and the assignment of programming tasks that demand mindful abstraction from these examples