Investigation of Higher Education Students' Computational Thinking Skill Levels

Year 2024, , 234 - 256, 28.10.2024

Cansu Şahin Kölemen

https://doi.org/10.53047/josse.1524548

Abstract

Computational thinking skill is a skill that has its origins in ancient times but has gained importance today. The competences provided to individuals by computational thinking skills are also of great importance for the education system. Therefore, it is important for students to acquire and develop these skills in order to adapt to the requirements of the modern world. Based on this, in this study, the level of information processing thinking skills of higher education students was examined and the level of this skill was investigated in line with different variables. 'Computational Thinking' scale was used as a data collection tool in the study. Cronbach Alpha internal consistency coefficient of the scale. 96 was calculated as. Demographic characteristics such as gender, department, class and education level were taken into consideration. Quantitative research method was used in the study. The research was conducted with 298 participants studying in higher education. In the analysis of the data, independent t-test and ANOVA analyses were applied to determine the score differences between the groups. As a result of the study, higher education students were found to have high levels of computational thinking skills. Gender was found to be effective on computational thinking skills. As the level of education increased, it was determined that computational thinking skills increased. It was seen that the education given in different departments had an effect on computational thinking skills. Finally, it was found that there were significant changes in students' computational thinking skills as their grade level increased.

Keywords

Computational thinking skills, computerised thinking, higher education students.

References

• Akgün, F. (2020). Evaluation of pre-service teachers' information and communication technology competencies and computational thinking skills in terms of various variables. Trakya University Journal of Social Sciences, 22(1), 629-654.
• Akın, S., & Yıldız, H. (2021). The impact of computational thinking skills on problem-solving abilities: A study on university students. Journal of Educational Technology, 35(2), 123-137.
• Akkoyun, B. (2021, March 29). The effect of information and technology skills and system availability on the efficiency of enterprises over the level of acceptance of new technology.
• Aksit, O. (2018). Enhancing science learning through computational thinking and modeling in middle school classrooms: A mixed methods study [Unpublished doctoral thesis]. North Carolina State University.
• Bakırtaş, F. M., & Lamba, M. (2020). The effect of social knowledge on learning organization structure within the scope of social intelligence: A research on union workplace representatives. Hak İş International Journal of Labor and Society, 9(25), 395-421.
• Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning and Leading with Technology, 38(6), 20-23.
• Barut, E., Tuğtekin, U., & Kuzu, A. (2016). Examining programming education in the context of computational thinking skills. In 4th International Symposium on Instructional Technologies and Teacher Education. Fırat University, Elâzığ.
• Berisha-Namani, M. (2011). Information systems usage in business and management. International Journal of Innovation in the Digital Economy (IJIDE), 2(2), 12-23.
• Bilbao, J., Bravo, E., García, O., Rebollar, C., & Varela, C. (2022). Computational thinking and sustainability to improve the preparation of our students. In INTED2022 Proceedings (pp. 7742-7746). IATED.
• Bocconi, S. (2016). Developing computational thinking in compulsory education: Joint research center (European Commission).
• 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.
• Büyüköztürk, Ş., Kılıç-Çakmak, E., Akgün, Ö., Karadeniz, Ş., & Demirel, F. (2017). Scientific research methods. Pegem Academy.
• Çetin, İ., & Uçar, Z. T. (2017). Definition and scope of computational thinking. Pegem Academy.
• Çınar, M., & Tüzün, H. (2017). A qualitative analysis on the nature of the computational thinking process. In 19th Academic Informatics Conference. Aksaray University, Aksaray, Turkey.
• Demir, K., Demir, E. B. K., Çaka, C., Tuğtekin, U., İslamoğlu, H., & Kuzu, A. (2016). The use of three-dimensional printing technologies in education: Applications in Turkey. Aegean Journal of Education, 17(2), 481-503.
• Demir, Ö., & Seferoğlu, S. S. (2017). New concepts, different uses: An evaluation of computational thinking. Educational Technology Readings, 41, 801-830.
• Einhorn, S. (2012). Microworlds, computational thinking, and 21st century learning. LCSI White Paper, 2, 2-10.
• Esteve-Mon, F. M., Llopis-Nebot, M. Á., & Adell-Segura, J. (2020). Digital teaching competence of university teachers: A systematic review of the literature. IEEE Revista Iberoamericana de Tecnologías del Aprendizaje, 15(4), 399-406.
• Gravetter, F. J., & Forzano, L.-A. B. (2008). Research methods for the behavioral sciences. Wadsworth.
• Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38-43.
• Hidayat, N., Hubeis, M., & Sukmawati, A. (2020). Competency-based human resources management in the industry 4.0 Era. International Journal of Management, 11(9), 953-961.
• İlic, U., Tuğtekin, U., & Haseski, H. İ. (2016). Computational thinking in educational digital games: A measurement tool development study. In 10th International Symposium on Computer and Instructional Technologies (ICITS 2016).
• Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
• Korkmaz, Ö., Çakır, R., Özden, M. Y., Oluk, A., & Sarıoğlu, S. (2015). Investigation of individuals' computer thinking skills in terms of different variables. Ondokuz Mayis University Journal of Education Faculty, 34(2), 68-87.
• Korkmaz, Ö., Çakir, R., & Özden, M. Y. (2017). A validity and reliability study of the computational thinking scales (CTS). Computers in Human Behavior, 72, 558-569.
• Kuleli, S. Ç. (2018). Evaluation of teacher candidates' online learning readiness levels and information processing thinking skills [Unpublished master's thesis]. Düzce University Institute of Social Sciences.
• Kurnaz, H., & Nas, Ş. Ç. (2022). Critical reading self-efficacy scale for middle school students: validity and reliability study. International Journal of Turkish Literature Culture Education (TEKE), 11(2), 793-812.
• Liu, Z., Zhi, R., Hicks, A., & Barnes, T. (2017). Understanding problem solving behavior of 6-8 graders in a debugging game. Computer Science Education, 27(1), 1-29.
• Maden, A., Önal, T., & Maden, F. (2022). The effects of computational thinking skills on middle school students. Journal of Educational Technology Research, 54(3), 256-275.
• Majeed, B. H., Jawad, L. F., & Alrikabi, H. T. (2022). Computational thinking (CT) among university students. International Journal of Interactive Mobile Technologies, 16(10).
• Neuman, W. L., & Robson, K. (2014). Basics of social research. Pearson Canada. Oluk, A. (2017). Investigation of students' computer thinking skills in terms of logical mathematical intelligence and mathematics academic achievement [Unpublished master's thesis]. Amasya University Institute of Science and Technology.
• Oluk, A., & Korkmaz, Ö. (2016). Comparing students' Scratch skills with their computational thinking skills in terms of different variables. Online Submission, 8(11), 1-7.
• Onwuegbuzie, A. J., & Collins, K. M. (2007). A typology of mixed methods sampling designs in social science research. The Qualitative Report, 12(2), 281-316.
• Özden, M. Y. (2015). Computational thinking and its use in education. Journal of Educational Sciences, 40(2), 123-145.
• Paf, M. (2019). The relationship between middle school students' informational thinking skills and creative problem solving skills [Unpublished master's thesis]. Adnan Menderes University Institute of Social Sciences.
• Pérez-Suasnavas, A. L., Salgado-Proaño, B. F., Hasperué, W., Cela, K. L., & Santamaría, J. L. (2023). Evolución de las técnicas de minería de datos para extraer datos provenientes de Twitter aplicadas a la educación superior: Una revisión sistemática. South Florida Journal of Development, 4(1), 33-55.
• Pratiwi, I. R., Josi, A., & Silalahi, P. (2022). Pengenalan computational thinking dan Bebras task sebagai keterampilan berpikir di abad 21 untuk guru SD dan SMP Sungailiat. Martabe: Jurnal Pengabdian Kepada Masyarakat, 5(1), 252-258.
• Rebollar, C., Varela, C., & Eugenio, O. (2022). First-year engineering students' computational reasoning abilities. International Journal of Advanced Science and Computer Applications, 1(2).
• Sarıtepeci, M. (2017). Investigation of information-processing thinking skills at secondary education level in terms of various variables. In 5th International Instructional Technologies and Teacher Education Symposium Proceedings (pp. 218-226).
• Selby, C., & Woollard, J. (2013). Computational thinking: The developing definition.
• Sert-Orhan, M. (2023). Examination of teacher candidates' lifelong learning tendencies, cognitive flexibility and computer thinking skills [Unpublished master's thesis]. Aydın Adnan Menderes University, Institute of Social Sciences.
• Subaşı, E. (2022). Sosyal bilgiler öğretmen adayilerinin bilişimsel düşüncelerme becereri düzeyilerinin incelenmesi [Unpublished master's thesis]. Akdeniz University Institute of Educational Sciences.
• Şahiner, A., & Kert, S. B. (2016). Examining the studies on the concept of computational thinking between 2006-2015. European Journal of Science and Technology, 5(9), 38-43.
• Togyer, J., & Wing, M. J. (2017). Research notebook: Computational thinking-What and why. Retrieved February 27, 2018.
• Türk, A. M., & Bilge, A. (2018). Tracking technology trends in computer engineering education. arXiv preprint arXiv:1807.07571.
• Üzümcü, Ö. (2023). Computational thinking scale: The predictive role of metacognition in the context of higher order thinking skills. Journal for the Education of Gifted Young Scientists, 11(3), 423-437.
• Üzümcü, Ö., & Bay, E. (2018). New 21st century skill in education: Computational thinking. International Journal of Social Sciences in Turkish Cultural Geography, 3(2), 1-16.
• Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education: Towards an agenda for research and practice. Education and Information Technologies, 20, 715-728.
• Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
• Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society, 366, 3717-3725.
• 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.
• Yecan, E., Özçınar, H., & Tanyeri, T. (2017). Information technologies teachers' experiences in teaching visual programming. İlköğretim Online, 16(1), 377-393.
• Yılmaz, M., & Güven, E. (2023). Exploring the role of computational thinking in higher education: A review of recent studies. International Journal of Educational Research, 58(1), 87-102.