Computational thinking and tinkering : exploration study of primary school students in robotic and graphical programming

Felicia Anna, Sha'rif Sabariah, Wong Wk, Mariappan Muralindran,

Full Text

The study was conducted to analyse the effect of a robotic program to primary school children. In order to succeed in a world increasingly dependent on technology, computational thinking is important. Computational thinking is considered as an important skill for students in 21-st learning century. Computational thinking provides basic knowledge in the design of generalization problem; decomposition, data representation, generalization, modeling, and algorithm. Educational robotics associated much with computational thinking and the subject of computer science through programming module has been emphasized by the education ministry recently and was introduced formally in the primary school curriculum, which focuses on solving technological problems. The instrument used to measure the technological problem solving is Technological Problem Solving Inventory (PSI-TECH). Quasi-experiments was implemented in this study, involved experimental group and control group which were equal in selected characteristics. The robotic and basic visual programming program conducted for 10 weeks, consistent with the school syllabus and activities. Data were collected before and after the program, and quantitative analysis of t-test and ANOVA were used. Result had shown a significance positive value for the experimental group after the program. This study contributes in the field of education, especially teachers in investigating the problem-solving skills among students. In addition, diversification of study in the field of robotics.

References

1. Afari E. & Khine M.S. (2017). Robotics as an educational tool. International Journal of Information and Education Technology. 7 (6):437-442. 2. Alimisis, D. (2013). Educational robotic: Open questions and new challenges. Themes in Science & Technology Education, 6(1): 63-71. 3. Ambrosio, A. P., Almeida,L.D.S., Macedo, J. & Franco, A. (2014). Exploring core cognitive skills of computational thinking, University of Sussex. 4. Atmatzidou, S. & Demetriadis, S. (2014). How to support students’ computational thinking skills in educational robotics activities, Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics & 5th International Conference Robotics in Education, July 18, Padova, Italy. 5. Awang, Z. (2010). Research Methodology for Business and Social Sciences. Kelantan: Universiti Teknologi MARA. 6. Awang, Z. (2012). Research methodology and data analysis. Penerbit Universiti Teknologi MARA Press. 7. Baek, H-G., & An, K-S. (2011). Study of the development of a problem-based model for mind study. Korean Journal of Digital Policy & Management, 9 (3): 249-260. 8. 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. 9. Bilotta, D., Gabriele, D., Servidio, R. & Tavernise, A. (2009). “Edutainment robotics as learning tool”, in Z. Pan, A., Chcok, W. Muller and M. Chand (eds), Transactions on Edutainment III, Lecture Notes in Computer Science 5940, pp.25-35. 10. Brennan K.& Resnick M. (2012). New frameworks for studying and assessing the development of computational thinking, AERA meeting, Canada. 11. Creswell, J.W. (2009). Research Design (Qualitative, Quantitative and Mixed methods Approaches) 3rd edition. London: Sage Publications. 12. Cury, J., Snyder, L., and Wing, J. (2010). Computational Thinking: A Definition. Demystifying Computational Thinking for Non-Computer Scientists (in press). 13. Dede, C., Mishra, P. & Voogt, J. (2013). Working group 6: Advancing computational thinking in 21st century learning. International Summit on ICT in Education. 14. Eguchi, A. (2014). Robotics as a learning tool for educational transformation. In Proceedings of 4th International Workshop Teaching Robotics, Teaching with Robotics & 5th International Conference Robotics in Education, 18 July (pp. 27-34), Padova, Italy. 15. Elkin, M., Sullivan, A., & Bers, M. U. (2014). Implementing a robotics curriculum in an early childhood Mon-tessori classroom. Journal of Information Technology Education: Innovations in Practice, 13, 153-169. Retrieved from http://www.jite.org/documents/Vol13/JITEv13IIPvp153-169Elkin882.pdf 16. Fridin, M. (2014) Storytelling by a kindergarten social assistive robot: A tool for constructive learning in preschool education. Computers & Education, 70 : 53-64. 17. Ghazali Darusalam dan Sufean Hussin. (2016). Metodologi Penyelidikan Dalam Pendidikan. Kuala Lumpur: Universiti Malaya. 18. Grover, S. (2011). Robotics and engineering for middle and high schools students to develop computational thinking, Annual Meeting of the American Educational Research Association, p.p 1-15. 19. Harvey, B. & Monig, J. (2010). Bringing “no ceiling” to Scratch: Can one language serve kids and computer scientists? Constructionism, Paris. 20. Heppner. (1988). The problem solving inventory manual. Palo Alto, CA: CPP, Inc. 21. Hoque, A. S. M. M., & Awang, Z. (2016). The Exploratory Factor Analysis (EFA) of Entrepreneurial Marketing Scale - Development and Validation. Tourism Conference, 20-22 april (p. 22). 22. Jeannette M.Wing. (2006). Computational Thinking Viewpoint. Communications of the ACM. 49 (3), 33-35. 23. 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: 245-255. 24. Kazakoff, E.R. & Bers, M.U. (2011). The impact of computer programming on sequencing ability in early childhood. AERA. 25. Kazakoff, E.R. & Bers, M.U. (2014). Put your robot in, put your robot out: Sequencing through programming robots in early childhood. Journal Educational Computing Research, 50(4) : 553-573. 26. Kazakoff, E.R. & Bers, M.U. (2012). Programming in a robotics context in the kindergarten classroom: The impact on sequencing skills. Journal of Educational Multimedia and Hypermedia, 21(4) : 371-391. 27. MacPherson, R.T. (1998). Factors affecting technological trouble shooting skills. Journal of Industrial Teacher Education, 35(4). 28. Mioduser, D. (2009). Learning technological problem solving – A cognitive/epistemological perspective. In A.T. Jones & M.J. de Vries (ed.). International Handbook of Research and Development in Technology Education., pp.1-19. Sense Publishers. 29. Palinkas, L.A., Horwitz, S.M., Green, C.A., Wisdom, J.P., Duan,N. & Hoagwood, K. (2013). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Adm Policy Ment Health. DOI 10.1007/s10488-013-0528-y. 30. Papert, S. (1993). Mindstroms: Children, computers, and powerful ideas (2nd edition), NY : Basic Books. 31. Papert, S. (1993). The Children's Machine. New York: Basic Books, p. 86. 32. Ranjit Kumar. (1999). Research Methodology: A step-by-step guide to beginners. London: Sage Publications. 33. Trop, L., & Sage, S. (1998). Problems as possibilities: Problem based-learning for K-12. Alexandria, VA: Association for Supervision and Curriculum Development. 34. Varnado, T.E. (2005). The Effects of a Technological Problem Solving Activity on FIRST LEGO League Participants’ Problem Solving Style and Peformance. Phd Thesis. Virginia Polytechnic Institute and State University. 35. Voskoglou, M.G. & Buckley, S. (2012). Problem solving and computers in a learning environment, Egyptian Computer Science Journal (ECS), 36(4), 28-46. 36. Wu, T., Custer, R. L., & Dyrenfurth, M. J. (1996). Technological and personal problem solving styles: Is there a difference? Journal of Technology Education, 7(2):55-71.