Computational thinking scale: the predictive role of metacognition in the context of higher order thinking skills

Year 2023, Volume: 11 Issue: 3 - September 2023, 423 - 437, 02.10.2023

Özlem Üzümcü

https://doi.org/10.17478/jegys.1355722

Cited By: 1

Abstract

This study aims to determine the predictive role of cognition in computational thinking. In this context, the research has two problem situations. The first one is the development of a computational thinking scale for prospective teachers. The second is to determine the predictive role of metacognition in computational thinking with this scale. In Study-1, the computational thinking scale was developed with (N= 365) participants. In Study-2 (N=306), the role of metacognition in computational thinking was explained with structural equation modeling. These findings show that, the computational thinking scale consisting of 28 items in Study-1 explained 48% of the total variance with a single factor structure and the internal consistency coefficient was found to be .985. In Study-2, the role of metacognition in computational thinking was tested with structural equation modeling. Accordingly, the planning, debugging and procedural knowledge sub-dimensions of metacognition explained 47% of the variance of computational thinking.

Keywords

computational thinking, metacognition, higher-order thinking skills, structural equation model

References

• Aho, A. V. (2012). Computation and computational thinking. The computer journal, 55(7), 832-835. doi: 10.1093/comjnl/bxs074
• Akın, A., Abacı, R., & Çetin, B. (2007). Bilişötesi Farkındalık Envanteri’nin Türkçe Formunun Geçerlik ve Güvenirlik Çalışması. Educational Sciences: Theory & Practice, 7(2), 655-680.
• Al Rabadi, W. M., & Salem, R. K. (2018). The Level of High-Order Thinking and Its Relation to Quality of Life among Students at Ajloun University College. International Education Studies, 11(6), 8-21. https://doi.org/10.5539/ies.v11n6p8
• Ananiadou, K., & Claro, M. (2009). 21St century skills and competences for new millennium learners in OECD countries. OECD education working papers, no. 41. OECD Publishing (NJ1).
• Anderson, J. R. (2005). Human symbol manipulation within an integrated cognitive architecture. Cognitive Science, 29(3), 313–341. https://doi.org/10.1207/s15516709cog0000_22
• Anderson, J.R. (1995) Cognitive Psychology and its Implications, 4th edition, W. H. Freeman and Company.
• Atkinson, S. (2000). Does the need for high levels of performance curtail the development of creativity in design and technology project work?. International Journal of Technology and Design Education, 10(3), 255-281.
• 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. https://doi.org/10.1145/1929887.1929905
• Barrón-Estrada, M.L., Zatarain-Cabada, R., Romero-Polo, J.A. et al. Patrony: A mobile application for pattern recognition learning. Educ Inf Technol 27, 1237–1260 (2022). https://doi.org/10.1007/s10639-021-10636-7
• Bayram, N. (2016). Yapısal eşitlik modellemesine giriş. AMOS uygulamaları (3. Baskı). Ankara: EzgiYayınları.
• Bers, M., Flannery, L., Kazakoff, E., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145-157. https://doi.org/10.1016/j.compedu.2013.10.020
• Bloom, B., Englehart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. New York, NY:David McKay.
• Braithwaite, D. W., & Sprague, L. (2021). Conceptual Knowledge, Procedural Knowledge, and Metacognition in Routine and Nonroutine Problem Solving. Cognitive Science, 45(10), e13048. https://doi.org/10.1111/cogs.13048
• Bravo, A., A. Porzecanski, E. Sterling, N. Bynum, M. Cawthorn, D. S. Fernandez, L. Freeman, S. Ketcham, T. Leslie, J. Mull & D. Vogler (2016). Teaching for higher levels of thinking: developing quantitative and analytical skills in environmental science courses. Ecosphere 7(4):e01290. 10.1002/ecs2.1290
• Brennan, K., & Resnick, M. (2012, April). New frameworks for studying and assessing the development of computational thinking. In Proceedings of the 2012 annual meeting of the American educational research association, Vancouver, Canada (Vol. 1, p. 25).
• Brookhart, S. M. (2010). How to Assess Higher-Order Thinking Skills in Your Classroom. Alexandria. Retrieved from http://www.ascd.org/ASCD/pdf/books/brookhart2010b_copyright.pdf
• Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In: Bollen, K.A., & Long, J.S. (Eds.), Testing structural equation models (pp. 136-162). Beverly Hills, CA: Sage.
• Buckley, S. (2012, October). The role of computational thinking and critical thinking in problem solving in a learning environment. In European Conference on e-Learning (pp. 63-70). Academic Conferences International Limited.
• Bussaban, K., & Waraporn, P. (2015). Preparing undergraduate students majoring in computer science and mathematics with data science perspectives and awareness in the age of big data. Procedia - Social and Behavioral Sciences, 197, 1443–1446. https://doi.org/10.1016/j.sbspro.2015.07.092
• Büyüköztürk, Ş. (2011). Sosyal bilimler için veri analizi el kitabı (15. Baskı). Ankara: Pegem Akademi.
• Calderon, A. C., Crick, T., & Tryfona, C. (2015, July). Developing computational thinking through pattern recognition in early years education. In Proceedings of the 2015 British HCI conference (pp. 259-260). https://doi.org/10.1145/2783446.2783600
• Can, A. (2014). SPSS ile bilimsel araştırma sürecinde nicel veri analizi (3. Baskı). Ankara: Pegem Akademi.
• Cañas, A. J., Reiska, P., & Möllits, A. (2017). Developing higher-order thinking skills with concept mapping: A case of pedagogic frailty. Knowledge Management & E-Learning, 9(3), 348–365.
• Casakin, H., Davidovitch, N., & Milgram, R. M. (2010). Creative thinking as a predictor of creative problem solving in architectural design students. Psychology of Aesthetics, Creativity, and the Arts, 4(1), 31–35. https://doi.org/10.1037/a0016965
• Cetin, I., & Dubinsky, E. (2017). Reflective abstraction in computational thinking. The Journal of Mathematical Behavior, 47, 70-80.https://doi.org/10.1016/j.jmathb.2017.06.004
• Choi, J., Lee, Y. & Lee, E. Puzzle Based Algorithm Learning for Cultivating Computational Thinking. Wireless Pers Commun 93, 131–145 (2017). https://doi.org/10.1007/s11277-016-3679-9
• Cross, D. R. & Paris, S. G. (1988). Developmental and instructional analyses of children’s metacognition and reading comprehension. Journal of Educational Psychology, 80(2), 131-142. https://doi.org/10.1037/0022-0663.80.2.131
• CSTA, (2017). Computer Science Teachers Association K-12 Computer Science Standards. Retrieved from 20 May 2022, https://www.csteachers.org/page/standards
• DeVellis, R. F. (2003). Scale development: Theory and applications (2nd ed.). Thousand Oaks, CA: Sage.
• Doğan, A., Ribas, M. A., & Begonya, M. R. (2009). Metacognitive tools in interpreting training: A pilot study. Hacettepe Üniversitesi Edebiyat Fakültesi Dergisi, 26(1).
• Doleck, T., Bazelais, P., Lemay, D.J. et al. (2017). Algorithmic thinking, cooperativity, creativity, critical thinking, and problem solving: exploring the relationship between computational thinking skills and academic performance. J. Comput. Educ. 4, 355–369. https://doi.org/10.1007/s40692-017-0090-9
• Dolmacı, A., & Akhan, N. E. (2020). Bilişimsel Düşünme Becerileri Ölçeğinin Geliştirilmesi: Geçerlik ve Güvenirlik Çalışması. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 9(3), 3050-3071.
• Drmrod, J.E. (1990). Human Learning. Macmillan P. Company. New York.
• Eby, J. W., & Kujawa, E. (1994). Reflective planning, teaching and evaluation: K-12. New York: Macmillan Publishing Company.
• Ertugrul-Akyol, B. (2019). Development of computational thinking scale: Validity and reliability study. International Journal of Educational Methodology, 5(3), 421-432.
• Fitzgerald, S., Lewandowski, G., McCauley, R., Murphy, L., Simon, B., Thomas, L., & Zander, C. (2008). Debugging: finding, fixing and flailing, a multi-institutional study of novice debuggers. Computer Science Education, 18(2), 93-116.
• Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American psychologist, 34(10), 906-911.
• Flavell, J.H. (1976). Metacognitive aspects of problem solving. In L. Resnick, ed., The Nature of Intelligence. Hillsdale, NJ: Lawrence Erlbaum As.
• Garner, R., & Alexander, P. A. (1989). Metacognition: Answered and unanswered questions. Educational psychologist, 24(2), 143-158. https://doi.org/10.1207/s15326985ep2402_2
• Ghanizadeh, A. (2017). The interplay between reflective thinking, critical thinking, self-monitoring, and academic achievement in higher education. Higher Education, 74(1), 101-114. https://doi.org/10.1007/s10734-016-0031-y
• Göğüş, A., Göğüş, N.G., & Bahadır, E. (2020). Intersections between critical thinking skills and reflective thinking skills toward problem solving. Pamukkale Üniversitesi Eğitim Fakültesi Dergisi ,49, 1-19. doi:10.9779/pauefd.526407
• Gresse Von Wangenheım, C., Araújo E Sılva De Medeıros, G., Mıssfeldt Fılho, R., Petrı, G., Da Cruz Pınheıro, F., F.
• Ferreıra, M. N., & Hauck, J. C. R. (2019). SplashCode - A Board Game for Learning an Understanding of Algorithms in Middle School. Informatics in Education, 18(2), 259-280. doi:10.15388/infedu.2019.12
• Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational researcher, 42(1), 38-43. https://doi.org/10.3102/0013189X12463051
• Gülbahar, Y., Kert, S. B. & Kalelioğlu F. (2018). Bilgi Işlemsel Düşünme Becerisine Yönelik Öz Yeterlik Algısı Ölçeği (BİDBÖA): Geçerlik Ve Güvenirlik Çalışması. Türk Bilgisayar ve Matematik Eğitimi Dergisi. Advance online publication. doi:10.16949/turkbilmat.385097
• Güner, P., & Erbay, H. N. (2021). Prospective mathematics teachers’ thinking styles and problem-solving skills. Thinking Skills and Creativity, 40, 100827. https://doi.org/10.1016/j.tsc.2021.100827
• Gürbüz, S. (2019). AMOS ile yapısal eşitlik modellemesi. Ankara: Seçkin Yayınları.
• Hamzah, H., Hamzah, M. I., & Zulkifli, H. (2022). Systematic Literature Review on the Elements of Metacognition-Based Higher Order Thinking Skills (HOTS) Teaching and Learning Modules. Sustainability, 14(2), 813. https://doi.org/10.3390/su14020813
• Hartman, H. J. (1998). Metacognition in teaching and learning: An introduction [Special issue]. Instructional Science, 1-3.
• He, Z.; Wu, X.; Wang, Q.; Huang, C. (2021) Developing Eighth-Grade Students’ Computational Thinking with Critical Reflection. Sustainability, 13, 11192. https://doi.org/10.3390/su132011192
• Ho R. (2006). Handbook of univariate and multivariate data analysis and interpretation with SPSS. Boca Raton, FL: CRC Press.
• Hooshyar, D., Malva, L., Yang, Y., Pedaste, M., Wang, M., Lim, H. (2021). An adaptive educational computer game: Effects on students’ knowledge and learning attitude in computational thinking. Computers in Hu¬man Behavior, 114, 106575. https://doi.org/https://doi.org/10.1016/j.chb.2020.106575
• Husamah, H., Fatmawati, D., & Setyawan, D. (2018). OIDDE learning model: Improving higher order thinking skills of biology teacher candidates. International Journal of Instruction, 11(2), 249-264.
• Jackson, D. L., Gillaspy J. A., & Purc-Stephenson, R. (2009). Reporting practices in confirmatory factor analysis: an overview and some recommendations. Psychological methods, 14, 6-23.
• Kalelioglu, F., Gulbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4(3), 583–596.
• Karalar, H., & Alpaslan, M. M. (2021). Assessment of eighth grade students’ domain-general computational thinking skills. International Journal of Computer Science Education in Schools, 5(1), 35–47. https://doi.org/10.21585/ijcses.v5i1.126
• Kim, C., Yuan, J., Vasconcelos, L. et al. Debugging during block-based programming. Instr Sci 46, 767–787 (2018). https://doi.org/10.1007/s11251-018-9453-5
• Kim, S., Raza, M., & Seidman, E. (2019). Improving 21st-century teaching skills: The key to effective 21st-century learners. Research in Comparative and International Education, 14(1), 99–117. https://doi.org/10.1177/1745499919829214
• Kline, R. B., (2005). Principles and Practice of Structural Equation Modeling (2nd ed.). New York: Guilford Press. Knochel, A. D., & Patton, R. M. (2015). If art education then critical digital making: Computational thinking and creative code. Studies in Art Education, 57(1), 21–38. https://doi.org/10.1080/00393 541.2015.11666280
• 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.
• Kukul, V., & Karatas, S. (2019). Computational thinking self-efficacy scale: Development, validity and reliability. Informatics in Education, 18(1), 151-164.
• Kumar, A. E. (1998). The influence of metacognition on managerial hiring decision making: Implications for management development. Doctoral dissertation, Virginia Polytechnic Institute and State University.
• Lee, H. J. (2005). Understanding and assessing preservice teachers’ reflective thinking. Teaching and teacher education, 21(6), 699-715. https://doi.org/10.1016/j.tate.2005.05.007
• Lee, K. H. (2005). The Relationship between Creative Thinking Ability and Creative Personality of Preschoolers. International Education Journal, 6(2), 194-199.
• Lee, S. J., Francom, G. M., & Nuatomue, J. (2022). Computer science education and K-12 students’ computational thinking: A systematic review. International Journal of Educational Research. https://doi.org/10.1016/j.ijer.2022.102008
• Lu, C., Macdonald, R., Odell, B. et al. (2022). A scoping review of computational thinking assessments in higher education. J Comput High Educ 34, 416–461 https://doi.org/10.1007/s12528-021-09305-y
• Mayer, R. E. (1998). Cognitive, metacognitive, and motivational aspects of problem solving. Instructional science, 26(1), 49-63. https://doi.org/10.1023/A:1003088013286
• Meijer, J., Veenman, M. V., & van Hout-Wolters, B. H. (2006). Metacognitive activities in text-studying and problem-solving: Development of a taxonomy. Educational Research and Evaluation, 12(3), 209-237. doi: 10.1080/13803610500479991
• Meng, Q., Jia, J., & Zhang, Z. (2020). A framework of smart pedagogy based on the facilitating of high order thinking skills. Interactive Technology and Smart Education.
• 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.
• Mumford, M. D., Giorgini, V., Gibson, C., & Mecca, J. (2013). Creative thinking: Processes, strategies and knowledge. In Handbook of research on creativity. Edward Elgar Publishing.
• Newmann, F. M. (1988). Higher Order Thinking in the High School Curriculum. NASSP Bulletin, 72(508), 58–64. https://doi.org/10.1177/019263658807250812
• Nguyễn, T. M. T., & Nguyễn, T. T. L. (2017). Influence of explicit higher-order thinking skills instruction on students’ learning of linguistics. Thinking Skills and Creativity, 26, 113-127.
• Ohtani, K., Hisasaka, T. Beyond intelligence: a meta-analytic review of the relationship among metacognition, intelligence, and academic performance. Metacognition Learning 13, 179–212 (2018). https://doi.org/10.1007/s11409-018-9183-8
• Özgenel, M. & Çetin, M. (2018). Development of the Marmara critical thinking dispositions scale: Validity and reliability analysis. International Journal of Eurasia Social Sciences, Vol: 9, Issue: 32, pp. (991-1015).
• Özmutlu, M., Atay, D., & Erdoğan, B. (2021). Collaboration and engagement based coding training to enhance children’s computational thinking self-efficacy. Thinking Skills and Creativity, 40, 100833.
• Palts, T., & Pedaste, M. (2020). A model for developing computational thinking skills. Informatics in Education, 19(1), 113-128.
• Pedaste M., Palts T., Kori K., Sõrmus M. & Leijen Ä., "Complex Problem Solving as a Construct of Inquiry, Computational Thinking and Mathematical Problem Solving," 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), 2019, pp. 227-231, doi: 10.1109/ICALT.2019.00071.
• Pegg, J. (2010), “Promoting the acquisition of higher-order skills and understandings in primary and secondary mathematics”, Research Conference 2010, pp. 35-38. Retrieved from https://research.acer.edu.au/research_conference/RC2010/16august/19/
• Qian, Y., Choi, I. Tracing the essence: ways to develop abstraction in computational thinking. Education Tech Research Dev (2022). https://doi.org/10.1007/s11423-022-10182-0
• Resnick, L. (1987). Education and learning to think. Washington, DC: National Academy.
• Rhodes, M. G. (2019). Metacognition. Teaching of Psychology, 46(2), 168-175. https://doi.org/10.1177/0098628319834381
• Rıjke, W. J., Bollen, L., Eysınk, T. H. S., & Tolboom, J. L. J. (2018). Computational Thinking in Primary School: An Examination of Abstraction and Decomposition in Different Age Groups. Informatics in Education, 17(1), 77-92. doi:10.15388/infedu.2018.05
• Rich, P. J., Larsen, R. A., & Mason, S. L. (2021). Measuring teacher beliefs about coding and computational thinking. Journal of Research on Technology in Education, 53(3), 296-316.
• Rijo-García, S., Segredo, E., & León, C. (2022). Computational Thinking and User Interfaces: A Systematic Review. IEEE Transactions on Education.
• Rodgers, C. (2002). Defining Reflection: Another Look at John Dewey and Reflective Thinking. Teachers College Record, 104(4), 842–866. https://doi.org/10.1111/1467-9620.00181
• Saad, A., & Zainudin, S. (2022). A review of Project-Based Learning (PBL) and Computational Thinking (CT) in teaching and learning. Learning and Motivation, 78, 101802. https://doi.org/10.1016/j.lmot.2022.101802
• Schneider, W. & Lockl, K. (2002). The development of metacognitive knowledge in childrenand adolescents. In Perfect, T. & Schwartz, B. (Eds.), Applied metacognition. Cambridge, UK: Cambridge University Press.
• Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary educational psychology, 19(4), 460-475. https://doi.org/10.1006/ceps.1994.1033.
• Selby, C., & Woollard, J. (2013). Computational thinking: the developing definition. Proceedings of the 45th ACM technical symposium on computer science education. Canterbury, ACM.
• Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142-158.
• Simamora, R. E., & Saragih, S. (2019). Improving Students' Mathematical Problem Solving Ability and Self-Efficacy through Guided Discovery Learning in Local Culture Context. International Electronic Journal of Mathematics Education, 14(1), 61-72. https://doi.org/10.12973/iejme/3966
• Stanger-Hall, K. F. (2012). Multiple-choice exams: an obstacle for higher-level thinking in introductory science classes. CBE—Life Sciences Education, 11(3), 294-306.
• Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). New York: Harper & Row.
• Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148, 103798. https://doi.org/10.1016/j.compedu.2019.103798
• Tsai, M. J., Liang, J. C., Lee, S. W. Y., & Hsu, C. Y. (2022). Structural validation for the developmental model of computational thinking. Journal of Educational Computing Research, 60(1), 56-73. https://doi.org/10.1177/07356331211017
• Umay, A., & Ariol, S., (2011). A Comprasion Problem Solving Skills in Terms of Holistic and Analytical Thinking Styles. Pamukkale Unıversity Journal of Education , no.30, 27-37.
• Uzumcu, O., Bay, E. (2021). The effect of computational thinking skill program design developed according to interest driven creator theory on prospective teachers. Educ Inf Technol 26, 565–583. https://doi.org/10.1007/s10639-020-10268-3
• Van Borkulo, S., Chytas, C., Drijvers, P., Barendsen, E., & Tolboom, J. (2021, October). Computational thinking in the mathematics classroom: fostering algorithmic thinking and generalization skills using dynamic mathematics software. In The 16th Workshop in Primary and Secondary Computing Education (pp. 1-9).
• Vourletsis, I., Politis, P. & Karasavvidis, I. (2021). The Effect of a Computational Thinking Instructional Intervention on Students’ Debugging Proficiency Level and Strategy Use. In: Tsiatsos, T., Demetriadis, S., Mikropoulos, A., Dagdilelis, V. (eds) Research on E-Learning and ICT in Education. Springer, Cham. https://doi.org/10.1007/978-3-030-64363-8_2
• Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215
• Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 366(1881), 3717-3725.
• Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. T. (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education (TOCE), 14(1), 1-16. https://doi.org/10.1145/2576872
• Yadav, A., Ocak, C. & Oliver, A. (2022). Computational Thinking and Metacognition. TechTrends 66, 405–411. https://doi.org/10.1007/s11528-022-00695-z
• Yağcı, M. (2019). A valid and reliable tool for examining computational thinking skills. Education and Information Technologies, 24(1), 929-951.
• Yurdakal, H.İ. (2019). Yaratıcı okuma çalışmalarının yaratıcı düşünme becerilerini geliştirmeye etkisi. Pamukkale Üniversitesi Eğitim Fakültesi Dergisi,47, 130-144. doi: 10.9779/pauefd.492812
• Zain, F. M., Sailin, S. N., & Mahmor, N. A. (2022). Promoting higher order thinking skills among pre-service teachers through group-based flipped learning. International Journal of Instruction, 15(3), 519-542. https://doi.org/10.29333/iji.2022.15329a
• Zhang, L. & Nouri, J. (2019). A systematic review of learning computational thinking through Scratch in K-9. Computers & Education, 141, 103607. https://doi.org/https://doi.org/10.1016/j.compedu.2019.103607
• Zohar, A. (1999). Teachers’ metacognitive knowledge and the instruction of higher order thinking. Teaching and teacher Education, 15(4), 413-429.