The relationship between the 21st-century skills and computational thinking skills of prospective mathematics and science teachers
Deniz Kaya 1 * , Ayten Öykü Yaşar 1, İbrahim Çetin 2, Tamer Kutluca 3
More Detail
1 Nevşehir Hacı Bektaş Veli University, Türkiye
2 Necmettin Erbakan University, Türkiye
3 Dicle University, Türkiye
* Corresponding Author

Abstract

This study aimed to determine the strength of the relationship between 21st-century skills and the computational thinking skill levels of prospective teachers, as well as the affect of 21st-century skills on computational thinking. This study adopted a correlational design as part of a quantitative methodology. The study sample consists of 300 prospective teachers, selected using purposive sampling. Multidimensional 21st Century Skills and Computational Thinking scales were used as data collection tools. The results revealed that the 21st-century skill components of prospective teachers did not differ by department; however, relationships were found with gender, grade level, and academic achievement. Additionally, a significant correlation was identified between department, gender, grade level, and academic achievement in relation to the components of computational thinking skills. A significant positive correlation was found between 21st-century skill components and computational thinking skill levels, with the 21st-century skill components of prospective teachers significantly influencing their computational thinking levels. As prospective teachers' information and technology literacy, critical thinking and problem solving, entrepreneurship, innovation, social responsibility and leadership skills increase, their computational thinking levels also increase. It was recommended that prospective teachers' awareness of the importance of 21st-century skills be enhanced, and that mathematics and science curricula be designed to incorporate future-oriented skills.  

Keywords

References

  • AlAli, R., & Wardat, Y. (2024). How ChatGPT will shape the teaching learning landscape in future. Journal of Educational and Social Research, 14(2), 336-345. https://doi.org/10.36941/jesr-2024-0047
  • Avcu, Y. E., & Ayverdi, L. (2020). Examination of the computer programming self-efficacy’s prediction towards the computational thinking skills of the gifted and talented students. International Journal of Educational Methodology, 6(2), 259-270. https://doi.org/10.12973/ijem.6.2.259
  • Bartolini-Bussi, M., & Baccaglini-Frank, A. (2015). Geometry in early years: Sowing seeds for a mathematical definition of squares and rectangles. ZDM Mathematics Education, 47(3), 391-405. https://doi.org/10.1007/s11858-014-0636-5
  • Binkley, M., Erstad, O., Herman, J., Raizen, S., Ripley, M., & Rumble, M. (2012). Defining 21st century skills. In P. Griffin, B. McGaw, & E. Care (Eds.), Assessment and teaching of 21st century skills (pp. 17-66). Springer.
  • Blackwell, C., Cummins, R., Townsend, C. D., & Cummings, S. (2007). Assessing perceived student leadership skill development in an academic leadership development program. Journal of Leadership Education, 6(1), 39-58. https://doi.org/10.12806/V6/I1/RF1
  • Can, A. (2023). Quantitative data analysis in the scientific research process with SPSS. Pegem Academy.
  • Cevik, M., & Senturk C. (2019). Multidimensional 21st century skills scale: Validity and reliability study. Cypriot Journal of Educational Sciences, 14(1), 11-28.
  • Cropley, A. J. (2001). Creativity in education and learning: A guide for teachers and educators. Routledge.
  • Curtis, E.A., Comiskey, C., & Dempsey, O. (2016). Importance and use of correlational research. Nurse Researcher, 23(6), 20-25. https://doi.org/10.7748/nr.2016.e1382
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2021). Multivariate statistics for social sciences: SPSS and LISREL applications. Pegem Academy.
  • Doleck, T., Bazelais, P., Lemay, D. J., Saxena, A., & Basnet, R. B. (2017). Algorithmic thinking, cooperativity, creativity, critical thinking, and problem solving: Exploring the relationship between computational thinking skills and academic performance. Journal of Computers in Education, 4(4), 355-369. https://doi.org/10.1007/s40692-017-0090-9
  • Dyer, J., Gregersen, H., & Christensen, C. M. (2019). The Innovator’s DNA, updated, with a new preface: Mastering the five skills of disruptive innovators. Harvard Business Press.
  • Eagly, A. H., & Johannesen-Schmidt, M. C. (2001). The leadership styles of women and men. Journal of Social Issues, 57(4), 781–797. https://doi.org/10.1111/0022-4537.00241
  • Erdogan, N., & Bozeman, T. (2015). Models of project-based learning for the 21st century. In A. Sahin (Ed.), A practice-based model of STEM teaching (pp. 31-42). Sense.
  • Esteve-Mon, F., Llopis, M., & Adell-Segura, J. (2020). Digital competence and computational thinking of student teachers. International Journal of Emerging Technologies in Learning, 15(2), 29-41. https://doi.org/10.3991/ijet.v15i02.11588
  • Facione, P. A. (2011). Critical thinking: What it is and why it counts. The California Academic Press.
  • Fannakhosrow, M., Nourabadi, S., Ngoc Huy, D. T., Dinh Trung, N., & Tashtoush, M. A. (2022). A comparative study of information and communication technology (ICT)‐based and conventional methods of instruction on learners’ academic enthusiasm for L2 learning. Education Research International, 2022(1), 1-8. https://doi.org/10.1155/2022/5478088
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.
  • Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education. McGraw-Hill.
  • Gadanidis, G., Clements, E., & Yiu, C. (2018). Group theory, computational thinking, and young mathematicians. Mathematical Thinking and Learning, 20(1), 32-53. https://doi.org/10.1080/10986065.2018.1403542
  • Gadanidis, G., Hughes, J., Minniti, L., & White, B. (2017). Computational thinking, grade 1 students and the binomial theorem. Digital Experiences in Mathematics Education, 3(2), 77-96. https://doi.org/10.1007/s40751-016-0019-3
  • Grover, S., & Pea, R. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher, 42(1), 38-43. http://dx.doi.org/10.3102/0013189X12463051
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis. Prentice Hall.
  • Halpern, D. F. (2014). Thought and knowledge: An introduction to critical thinking. Psychology Press.
  • Hershkovitz, A., Sitman, R., Israel-Fishelson, R., Eguíluz, A., Garaizar, P., & Guenaga, M. (2019). Creativity in the acquisition of computational thinking. Interactive Learning Environments, 27(5–6), 628-644. https://doi.org/10.1080/10494820.2019.1610451
  • Hussein, L. A., Alqarni, K., Hilmi, M. F., Agina, M. F., Shirawia, N., Abdelreheem, K. I., Hassan, T., & Tashtoush, M. A. (2024). The mediating role of learning management system use in enhancing system effectiveness. WSEAS Transactions on Business and Economics, 21, 2067-2078. https://doi.org/10.37394/23207.2024.21.169
  • International Society for Technology in Education [ISTE]. (2016). ISTE Standards for students. Author. https://iste.org/standards/students
  • International Society for Technology in Education & Computer Science Teachers Association [ISTE & CSTA]. (2011). Operational definition of computational thinking for K–12 education. Author. https://cdn.iste.org
  • İlhan, E., & Unal, M. (2021). An investigation of the 21st century skills use of university students in Turkey. International Journal of Curriculum and Instruction 13(3), 2462-2481.
  • Jarrah, A. M., Wardat, Y., & Fidalgo, P. (2023). Using ChatGPT in academic writing is (not) a form of plagiarism: What does the literature say?. Online Journal of Communication and Media Technologies, 13(4), 1-20. https://doi.org/10.30935/ojcmt/13572
  • Johnson, D. W., & Johnson, R. (1989). Cooperation and competition: theory and research. Interaction Book Company.
  • Jonassen, D. (2011). Supporting problem solving in PBL. Interdisciplinary Journal of Problem-Based Learning, 5, 95-119. https://doi.org/10.7771/1541-5015.1256
  • Kaup, C. F., Pedersen, P. L., & Tvedebrink, T. (2023). Integrating computational thinking to enhance students’ mathematical understanding. Journal of Pedagogical Research, 7(2), 127-142. https://doi.org/10.33902/JPR.202319187
  • Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). Guilford Press.
  • 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. https://doi.org/10.1016/j.chb.2017.01.005
  • Leopold, T. A., Ratcheva, V. S., & Saadia, Z. (2018). The future of jobs report 2018. World Economic Forum. Retrieved from http://www3.weforum.org/docs/WEF_Future_of_Jobs_2018.pdf Accessed 23.04.2024
  • Looi, C. K., Chan, S. W., Wu, L., Huang, W., Kim, M. S., & Sun, D. (2024). Exploring computational thinking in the context of mathematics learning in secondary schools: Dispositions, engagement and learning performance. International Journal of Science and Mathematics Education, 22(6), 993-1011. https://doi.org/10.1007/s10763-023-10419-1
  • Lumley, T., Diehr, P., Emerson, S., & Chen, L. (2002). The importance of the normality assumption in large public health data sets. Annual Review of Public Health, 23, 151-169. https://doi.org/10.1146/annurev.publhealth.23.100901.140546
  • Marshall, C., & Rossman, G. (2016). Designing qualitative research. Sage.
  • Moon, P. F., Himmelsbach, J., Weintrop, D., & Walkoe, J. (2023). Developing preservice teachers’ intuitions about computational thinking in a mathematics and science methods course. Journal of Pedagogical Research, 7(2), 5-20. https://doi.org/10.33902/JPR.202318599
  • Mumcu, F., Kıdıman, E., & Özdinç, F. (2023). Integrating computational thinking into mathematics education through an unplugged computer science activity. Journal of Pedagogical Research, 7(2), 72-92. https://doi.org/10.33902/JPR.202318528
  • National Research Council (NRC). (2011). Assessing 21st-century skills: Summary of a workshop. National Academies Press.
  • Organisation for Economic Cooperation and Development (OECD). (2023). Education at a glance 2023- OECD indicators. Author.
  • Organisation for Economic Cooperation and Development (OECD). (2019). OECD future of education and skills 2030: OECD learning compass 2030. Author.
  • Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Basic Books.
  • Partnership for 21st Century Learning [P21]. (2019). Framework for 21st century learning. A network of battelle for kids. Author.
  • Paul, R., & Elder, L. (2006). Critical thinking: learn the tools the best thinkers use. Pearson Prentice Hall.
  • Rodríguez-Martínez, J. A., González-Calero, J. A., & Sáez-López, J. M. (2020). Computational thinking and mathematics using Scratch: An experiment with sixth-grade students. Interactive Learning Environments, 28(3), 316-327. https://doi.org/10.1080/10494820.2019.1612448
  • Savickas, M. L. (2005). The theory and practice of career construction. In S. D. Brown & R. W. Lent (Eds.), Career development and counseling: Putting theory and research to work (pp. 42–70). John Wiley & Sons.
  • Shute, V., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22(1), 142-158. https://doi.org/10.1016/j.edurev.2017.09.003
  • Sneider, C., Stephenson, C., Schafer, B., & Flick, L. (2014). Computational thinking in high school science classrooms. The Science Teacher, 81(5), 10-15. https://doi.org/10.2505/4/tst14_081_05_53
  • Sung, W., Ahn, J., & Black, J. B. (2017). Introducing computational thinking to young learners: Practicing computational perspectives through embodiment in mathematics education. Technology, Knowledge and Learning, 22(2), 443-463. https://doi.org/10.1007/s10758-017-9328-x
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Pearson.
  • Tabesh, Y. (2017). Computational thinking: A 21st century skill. Olympiads in Informatics, 11(2), 65-70. https://doi.org/10.15388/ioi.2017.special.10
  • Tashtoush, M. A., AlAli, R., Wardat, Y., Alshraifin, N., & Toubat, H. (2023). The impact of information and communication technologies (ICT)-based education on the mathematics academic enthusiasm. Journal of Educational and Social Research, 13(3), 284-293. https://doi.org/10.36941/jesr-2023-0077
  • Trilling, B., & Fadel, C. (2009). 21st century skills: Learning for life in our times. John Wiley & Sons.
  • Voogt, J., Erstad, O., Dede, C., & Mishra, P. (2013). Challenges to learning and schooling in the digital networked world of the 21st century. Journal of Computer Assisted Learning, 29(5), 403-413. https://doi.org/10.1111/jcal.12029
  • 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. https://doi.org/10.1080/00220272.2012.668938
  • Wang, M. T., & Degol, J. L. (2017). Gender gap in science, technology, engineering, and mathematics (STEM): Current knowledge, implications for practice, policy, and future directions. Educational Psychology Review, 29(1), 119-140. https://doi.org/10.1007/s10648-015-9355-x
  • Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25(1), 127-147. https://doi.org/10.1007/s10956-015-9581-5
  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215
  • Wing, J. M. (2008a). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 366(1881), 3717-3725. https://doi.org/10.1098/rsta.2008.0118
  • Wing, J. M. (2008b). Five deep questions in computing. Communications of the ACM, 51(1), 58-60. https://doi.org/10.1145/1327452.1327479
  • World Economic Forum [WEF]. (2016). New vision for education: Fostering social and emotional learning through technology. Author.
  • Yadav, A., Ocak, C., & Oliver, A. (2022). Computational thinking and metacognition. TechTrends, 66(3), 405-411. https://doi.org/10.1007/s11528-022-00695-z
  • Ye, H., Liang, B., Ng, O. L., & Chai, C. S. (2023). Integration of computational thinking in K-12 mathematics education: A systematic review on CT-based mathematics instruction and student learning. International Journal of STEM Education, 10(1), 1-26. https://doi.org/10.1186/s40594-023-00396-w
  • Yıldırım, A., & Şimşek, H. (2021). Qualitative research methods in the social sciences. Seçkin.

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.