Computational thinking skills and its impact on TIMSS achievement: An Instructional Design Approach
Abstract
The need in raising levels of achievement in math and science has led instructional design researchers to a focus on investigating the factors that shape achievement in these subjects. Understanding how students think might influence Mathematics achievement may guide educators in their efforts to raise achievement by designing learning models that provide most efficient and effective instructional strategies and learning experiences. This research examined relationships between Computational thinking skills (CT) and their results in Mathematics test in TIMSS. Five skills of CT were considered: creativity, algorithmic thinking, cooperativity, critical thinking and problem solving. Being aware of thinking skills and their influence on students' results may provide educators with ideas for designing instruction and may help improve TIMSS achievement. Participants were 46 Students; 100% were female. Results indicated that high CT levels predicted of high Mathematics results in TIMSS. Problem solving skill had the highest impact in the test result, while the creativity skill was the least influential. It was concluded that students might need to improve their solving problems skill rather than their critical thinking skill in order to become successful in TIMSS assessments. Further empirical evidence is needed for whether CT tools improves students’ achievement.
DOI:10.2458/azu_itet_v7i1_alyahya
Keywords
References
AETC Definition and Terminology Committee (2008). Definition. In A. Januszewski & M. Molenda (Eds.)., Educational technology: A definition with commentary. New York: Lawrence Erlbaum.
Aksoy, B. (2004). Problem based learning approaches on geography instruction (Unpublished master’s thesis). Gazi University, Institute of Education Sciences, Ankara
Augustine, N. R. (2005). Rising above the gathering storm: energizing and employing America for a brighter economic future. Washington DC: National Academies Press.
Boddy, N., Watson, K., & Aubusson, P. (2003). A trial of the five Es: A referent model for constructivist teaching and learning. Research in Science Education, 33(1), 27-42.
Boden, M. A. (1990). The creative mind: Myths & mechanisms. Great Britain: George Weidenfeld and Nicolson Ltd.
Brandell, J. R. (2010). Theory & practice in clinical social work. Thousand Oaks, CA: Sage.
Brown, W. (2015). Introduction to algorithmic thinking. Retrieved from www.cs4fn.com/algoritmicthinking.php
CSTA, & ISTE (2011). Operational definition of computational thinking for Ke12 education. Retrieved from http://csta.acm.org/Curriculum/sub/CurrFiles/ CompThinkingFlyer.pdf
Curzon, P., Black, J., Meagher, L. R., & McOwan, P. (2009). cs4fn. org: Enthusing students about Computer Science. Proceedings of Informatics Education Europe IV, 73-80.
Czerkawski, B. (2013, March). Instructional design for computational thinking. Paper presented at the Society for Information Technology & Teacher Education International Conference.
Czerkawski, B., & Xu, L. (2012, June). Computational thinking and educational technology. In EdMedia: World Conference on Educational Media and Technology (pp. 2607-2610). Association for the Advancement of Computing in Education (AACE).
de Bono, E. (1976). Teaching thinking. London: Penguin.
Denning, P. J. (2009). The profession of IT beyond computational thinking. Communications of the ACM, 52(6), 28-30.
Dick, W. (1986). Instructional design and the curriculum development process. Educational Leadership, 44(4), 54-56.
Ennis, R. R. (1989). Critical thinking and subject specificity: Clarification and needed research. Educational Researcher, 18, 4–10.
García-Peñalvo, F. J. (2018). Editorial computational thinking. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 13(1), 17-19.
Gardner, D. P. (1983) A nation at risk: the imperative for educational reform. U.S. Department of Education, Washington, DC.
Google (2016). Computational thinking for educators [online course]. Retrieved from https://computationalthinkingcourse.withgoogle.com/unit?lesson=8&unit=1
Grønmo, L. S., Lindquist, M., Arora, A., & Mullis, I. V. (2015). TIMSS 2015 mathematics framework. Boston, MA: TIMSS & PIRLS International Study Centre.
Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38-43.
Holmes, N. G., Wieman, C. E., & Bonn, D. A. (2015). Teaching critical thinking. Proceedings of the National Academy of Sciences, 112(36), 11199-11204.
Hopson, M. H., Simms, R. L., & Knezek, G. A. (2001). Using a technology-enriched environment to improve higher-order thinking skills. Journal of Research on Technology in education, 34(2), 109-119.
Hossain, A., & Tarmizi, R. A. (2013). Effects of cooperative learning on students’ achievement and attitudes in secondary mathematics. Procedia-Social and Behavioral Sciences, 93, 473-477.
ISTE. (2015). CT leadership toolkit. Retrieved from http://www.iste.org/docs/ctdocuments/ct-leadershipt-toolkit.pdf
Johnson, D. W., Johnson, R. T., & Smith, K. (1991). Cooperative learning: Increasing college faculty instructional productivity (ASHE-ERIC Higher Education Report No. 4). Washington, DC: The George Washington University, School of Education and Human Development.
Kingdom of Saudi Arabia (2016). Vision 2030 Kingdom of Saudi Arabia. Retrieved from http://vision2030.gov.sa/en.
Korkmaz, Ö., Çakır, R., & Özden, M. Y. (2016). Computational thinking levels scale (CTLS) adaptation for secondary school level. Gazi Journal of Educational Science, 1(2), 143-162.
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.
Kuhn, D. (1999). A developmental model of critical thinking. Educational Researcher, 28(1), 16–26.
Lee, I., Martin, F., & Apone, K. (2014). Integrating computational thinking across the K-8 curriculum. Acm Inroads, 5(4), 64-71.
Leou, M., Abder, P., Riordan, M., & Zoller, U. (2006). ‘Using HOCS-centered learning’ as a pathway to promote science teachers’ metacognitive development. Research in Science Education, 36(1–2), 69–84.
Marshall, J. C., & Horton, R. M. (2011). The relationship of teacher‐facilitated, inquiry‐based instruction to student higher‐order thinking. School Science and Mathematics, 111(3), 93-101.
Martin, O. M., Mullis, I. V. S., & Foy, P. (2015). TIMSS 2015 assessment design. In I. V. S. Mullis, & M. O. Martin (Eds.), TIMSS 2015 assessment frameworks (pp. 85-99). Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.
McLeod, G. (2003). Learning theory and instructional design. London: Learning Matters, 2, 35-43.
Ministry of Education. (n.d.). المملكة العربية السعودية. Retrieved from https://www.moe.gov.sa/en/Pages/vision2030.aspx
Miri, B., David, B. C., & Uri, Z. (2007). Purposely teaching for the promotion of higher-order thinking skills: A case of critical thinking. Research in science education, 37(4), 353-369.
Morris, D., Uppal, G., & Wells, D. (2017). Teaching computational thinking and coding in primary schools. London: Learning Matters.
Mullis, I. V., Martin, M. O., Foy, P., & Arora, A. (2012). TIMSS 2011 international results in mathematics. International Association for the Evaluation of Educational Achievement. Amsterdam
Nam, C. W. (2014). The effects of trust and constructive controversy on student achievement and attitude in online cooperative learning environments. Computers in Human Behavior, 37, 237-248.
Olson, J. F., Martin, M. O., & Mullis, I. V. (Eds.). (2008). TIMSS 2007 technical report. Boston: TIMSS & PIRLS International Study Center.
Quinn, B. J. (2016). Computational thinking guiding change in online education. Journal of Medical Biomedical and Applied Sciences, 3(12). 8-17.
Resnick, L. (1987). Education and learning to think. Washington, DC: National Academy.
Saudi Vision 2030 (2016). Retrieved from http://vision2030.gov.sa/en/node
Schacter, D. L., Gilbert, D. T., & Wegner, D. M. (2009).
Introducing psychology. London, England: Macmillan.
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142-158.
Stupple, E. J., Maratos, F. A., Elander, J., Hunt, T. E., Cheung, K. Y., & Aubeeluck, A. V. (2017). Development of the critical thinking toolkit (CriTT): A measure of student attitudes and beliefs about critical thinking. Thinking Skills and Creativity, 23, 91-100.
Trilling, B., & Fadel, C. (2009). 21st century skills: Learning for life in our times. Hoboken, NJ: John Wiley & Sons.
UK DFE (2013). National Curriculum in England: Computing Programmes of Study. (Dept. Education No. DFE-00171-2013). UK. Retrieved from https://www.gov.uk/government/publications/national-curriculum-inengland-computing-programmes-of-study
Watts, M., Jofili, Z., & Bezerra, R. (1997). A case for critical constructivism and critical thinking in science education. Research in Science Education, 27(2), 309–322.
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.
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 of London A: mathematical, physical and engineering sciences, 366(1881), 3717-3725.
Wing, J. M. (2016). Computational thinking, 10 years later. Retrieved from https://phys.org/news/2016-03-years.html.
Zohar, A., & Dori, Y. J. (2003). Higher order thinking skills and low achieving students: Are they mutually exclusive? Journal of the Learning Sciences, 12(2), 145–183.
Zoller, U. (2001). Alternative assessment as (critical) means of facilitating HOCS-promoting teaching and learning in chemistry education. Chemical Education Research and Practice in Europe, 2(1), 9–17.
