Use of Arithmetic Operation Skills in Block Based Programming Environments: A Comparative Case Study

Year 2020, Volume: 8 Issue: 16, 404 - 427, 20.10.2020

Hayal Yavuz Mumcu Suheda Mumcu Ünal Çakıroğlu

https://doi.org/10.18009/jcer.705822

Cited By: 1

Abstract

The purpose of this study is to examine the 7th grade middle school students' processes of creating and calculating arithmetic expressions in the code.org block based coding environments. For this purpose, the reasons of students' behaviors in coding environments are tried to be revealed by comparing them with student behaviors in traditional environments. The participants of the study, which was conducted as a comparative case study, are composed of 10 students studying at a public school. Arithmetic Operation Test developed by the researchers, Student Screen Records taken from the code.org platform, Student Opinion Form consisting of three open-ended questions, Unstructured Interviews held with the students and Field Notes were used as data collection tools in this study. Descriptive analyzes were performed in order to compare the data obtained from different cases and the analysis results were expressed in different categories. In conclusion, it has been observed that the students were not as successful in coding environments as expected and use arithmetical operation skills more successfully in traditional environments than block based coding environments. In particular, it has been revealed that the use of blocks and the way in which code.org handles arithmetic operations cause the students cannot transfer their existing knowledge to the coding environments.

Keywords

Arithmetic operation skill, block based programming, code.org, comparative case study

References

• Bayman, P., & Mayer, R. E. (1983). A diagnosis of beginning programmers' misconceptions of BASIC programming statements. Communications of the ACM, 26(9), 677-679. DOI: 10.1145/358172.358408.
• Baxter, P., & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report, 13(4), 544-559.
• Bostan, M. I. (2010). Negatif sayılara ilişkin zorluklar, kavram yanılgıları ve bu yanılgıların giderilmesine yönelik öneriler [Difficulties and misconceptions regarding negative numbers and suggestions for overcoming these misconceptions]. In E. Bingolbali & M. F. Özmantar (Eds.), İlköğretimde karşılaşılan matematiksel zorluklar ve çözüm önerileri [Mathematical difficulties encountered in primary education and solution suggestions], pp. 155-186, Ankara: Pegem.
• Büyüköztürk, Ş., Çakmak, E. K., Akgün, Ö. E., Karadeniz, Ş., & Demirel, F. (2018). Eğitimde bilimsel araştırma yöntemleri [Scientific research methods (24th ed). Ankara: Pegem.
• Calder, N. (2010). Using Scratch: An integrated problem-solving approach to mathematical thinking. Australian Primary Mathematics Classroom (APMC), 15 (4), 9-14.
• Du Boulay, B. (1986). Some difficulties of learning to program. Journal of Educational Computing Research, 2(1), 57-73. DOI: 10.2190/3LFX-9RRF-67T8-UVK9.
• Esteves, M., & Mendes, A. (2004). A simulation tool to help learning of object oriented programming basics. In Proceedings of the 34th ASEE/IEEE Frontiers in Education Conference, Savannah, GA, USA. Retrieved from https://ieeexplore.ieee.org/document/1408649.
• Fesakis, G., & Serafeim, K. (2009). Influence of the familiarization with scratch on future teachers' opinions and attitudes about programming and ICT in education. In ACM SIGCSE Bulletin, 41 (3), 258-262. New York: ACM. DOI: 10.1145/1595496.1562957.
• Gall, M. D., Gall, J. P., & Borg, W. R. (2007). Education research: An introduction (8th ed.). Boston: Pearson Education.
• Genç, Z., & Karakuş, S. (2011). Learning through design: Using scratch in instructional computer games design. In 5 th International Computer & Instructional Technologies Symposium (ICITS), pp. 22-24, Elazığ, Turkey.
• Hancock, D. R., & Algozzine, B. (2006). Doing case study research: A practical guide for beginning researchers. Columbia University, NY: Teachers College.
• Hayes, B., & Stacey, K. (1990). Teaching negative number using integer tiles. Unpublished doctoral thesis, University of Melbourne, USA.
• Kalelioğlu, F. (2015). A new way of teaching programming skills to K-12 students: Code.org. Computers in Human Behavior, 52, 200-210. DOI: 10.1016/j.chb.2015.05.047.
• Larson, E. (2013). Coding the curriculum: How high schools are reprogramming their classes. Retrieved from http://mashable.com/2013/09/22/coding-curriculum.
• Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational thinking in K-9 education. In Proceedings of the Working Group Reports of the 2014 on Innovation & Technology in Computer Science Education Conference (pp. 1-29). New York: ACM. DOI: 10.1145/2713609.2713610.
• McMillan, J. H. (2000). Educational research: Fundamentals for the consumer. New York: Longman.
• Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: A Sourcebook of new methods (2d Edition). Beverly Hills, CA: Sage Publications.
• Ministry of National Education (2013). Ortaokul matematik dersi (5-6-7-8. sınıflar) öğretim programı [Secondary school mathematics (5-6-7-8. grades) curriculum]. Ankara: MEB.
• Ministry of National Education (2018). Bilişim teknolojileri yazılım dersi öğretim programı [Information technologies and software course curriculum]. Ankara: MEB.
• National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Reston, VA: National Council of Teachers of Mathematics.
• National Research Council (2010). Report of a workshop on the scope and nature of computational thinking. Washington, D.C.: The National Academies Press.
• Ozoran, D., Çağıltay, N. E., & Topallı, D. (2012). Using scratch in introduction to programming course for engineering students. Educational Technologies & Distance Education in Engineering, 2, 125-133.
• Özmen, B., & Altun, A. (2014). Undergraduate students’ experiences in programming: Difficulties and obstacles. Turkish Online Journal of Qualitative Inquiry, 5(3), 9-27.
• Patton, M. Q. (1990). Qualitative evaluation and research methods. US: Sage Publications.
• Pea, R., & Kurland M. (1983). On the cognitive prerequisites of learning computer programming. (Technical Report No. 18). New York: Bank Street College of Education.
• Ruf, A., Muhling, A., & Hubwieser, P. (2014). Scratch vs. Karel: Impact on learning outcomes and motivation. Paper presented at the Proceedings of the 9th Workshop in Primary and Secondary Computing Education, Berlin, Germany. DOI: 10.1145/2670757.2670772.
• Van de Walle, J.A., Karp, K.S., & Bay-Williams, J.M. (2010). Elementary and middle school mathematics: Teaching developmentally (7th ed.). Boston, MA: Allyn & Bacon.
• Wing, J. (2008). Computational thinking and thinking about computing. Phil. Trans. R. Soc. A, 366, 3717-3725. DOI: 10.1098/rsta.2008.0118.
• Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-5. DOI: 10.1145/1118178.1118215.
• Yenilmez, K., & Bagdat, O. (2014). Learning difficulties of year seven students on whole numbers problems. In Abstracts of International EJER Congress 1st Eurasian Educational Research Congress, 631-632.