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STEM teaching intention and computational thinking skills of pre-service teachers

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Abstract

The aim of the study is to examine the Science, Technology, Engineering and Mathematics (STEM) teaching intention of science and primary school pre-service teachers in terms of Computational Thinking (CT) skill, gender, grade level, daily computer usage, internet usage, smartphone usage, and the department variables. The study employs the correlational survey model. The participants of this research are 440 pre-service teachers at Van Yüzüncü Yıl University, Turkey. The STEM teaching intention scale, and the CT skill scale were used for data collection. Chi-Squared Automatic Interaction Detector (CHAID) analysis, independent samples t- test, and single factor variance analysis (ANOVA) was used for data analysis. According to the results; CT has the most significant effect in terms of STEM teaching intentions. Department is also another important variable for STEM teaching intentions. STEM teaching intention measures do not differ according to gender, grade level, daily average computer usage, internet usage and smart phone usage.

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References

  • Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832–835.

    Article  Google Scholar 

  • Aydın, G., Saka, M., & Guzey, S. (2018). Engineering knowledge level measurement scale for students in grades 4 through 8. Elementary Education Online, 17(2), 750–768.

    Google Scholar 

  • Bakırcı, H., & Karışan, D. (2018). Investigating the preservice primary school, mathematics and science teachers’ stem awareness. Journal of Education and Training Studies, 6(1), 32–42.

    Article  Google Scholar 

  • Bakırcı, H., & Kutlu, E. (2018). Identifying science teachers’ views on stem approach. Turkish Journal of Computer and Mathematics Education, 9(2), 367–389.

    Google Scholar 

  • Beheshti, E., Weintrop, D., Swanson, H., Orton, K., Horn, M. S., Kona, J. & Wilensky, U. (2017). Computational thinking in practice: How STEM professionals use CT in their work. In American Education Research Association Annual Meeting 2017.

  • Bilbao, J., Bravo, E., Garcia, O., Varela, C., & Rebollar, C. (2017). Assessment of computational thinking notions in secondary school. Baltic Journal of Modern Computing, 5(4), 391–397.

    Article  Google Scholar 

  • Bissaker, K. (2014). Transforming STEM education in an innovative Australian school: The role of teachers’ and academics’ professional partnership. Theory Into Practice, 53, 55–63.

    Article  Google Scholar 

  • Bozkurt, E. (2014). The effect of engineering design based science instruction on science teacher candidates' decision making skills, science process skills and perceptions about the process. PhD thesis, Institute of Educational Sciences, Gazi University, Turkey.

  • Bybee, R. W. (2010). Advancing STEM education: A 2020 vision. Technology and Engineering Teacher, 70(1), 30–35.

    Google Scholar 

  • Carbone, J. N., & Crowder, J. A. (2017). Addressing global education concerns-teaching computational thinking. Rich, P. J., & Hodges, C. B. (Eds.). Emerging research, practice, and policy on computational thinking. Springer.

  • Cooper, M. M. (2013). Chemistry and the next generation science standards. Journal of Chemical Education., 90, 679–680.

    Article  Google Scholar 

  • Denson, C. (2011). Building a framework for engineering design experiences in STEM: A synthesis. National Center for Engineering and Technology Education., 169, 1–6.

    Google Scholar 

  • Dugger, W. E. (2010). Evolution of STEM in the United States. Presented at the 6thBiennial International Conference on Technology Education Research, Gold Coast, and Queensland.

  • English, L. D. (2017). Advancing elementary and middle school STEM education. International Journal of Science and Mathematics Education, 15(1), 5–24.

    Article  MathSciNet  Google Scholar 

  • Ercan, S., & Şahin, F. (2015). The usage of engineering practices in science education: Effects of design based science learning on students’ academic achievement. Necatibey Faculty of Education Electronic Journal of Science and Mathematics Education, 9(1), 128–164.

    Google Scholar 

  • Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38–43.

    Article  Google Scholar 

  • Hacıömeroğlu, G., & Bulut, A. S. (2016). Integrative STEM teaching intention questionnaire: A validity and relaibility study of the Turkish form. Journal of Theory and Practice in Education, 12(3), 654–669.

    Google Scholar 

  • Hsu, T. C., Chang, S. C., & Hung, Y. T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126, 296–310.

    Article  Google Scholar 

  • Hutchins, N. M., Zhang, N., & Biswas, G. (2017). The role gender differences in computational thinking confidence levels plays in STEM applications. International Conference on Computational Thinking Education. 13-15 July 2017. Hong Kong.

  • International Society for Technology in Education (ISTE) (2018) ISTE Standards for Students. Date of access: 15.08.2018. On the web: https://www.iste.org/standards/for-students.

  • ISTE & CSTA (2011). Operational definition of computational thinking for K-12 thinking operational-definition-flyer.pdf. Date of access: 15.08.2018. On the web: http://www.iste.org/docs/ct-documents/computational-thinking-operational-definition-flyer.pdf?sfvrsn=2.

  • Jona, K., Wilensky, U., Trouille, L., Horn, M. S., Orton, K., Weintrop, D., & Beheshti, E. (2014). Embedding computational thinking in science, technology, engineering, and math (CT-STEM). In future directions in computer science education summit meeting. FL: Orlando.

    Google Scholar 

  • Jonassen, D. H. (2011). Design problems for secondary students. National Center for Engineering and Technology Education., 170, 1–6.

    Google Scholar 

  • Karasar, N. (2009). Scientific research method. Ankara: Nobel Publishing.

    Google Scholar 

  • Karışan, D., & Bakırcı, H. (2018). Exploration of preservice teachers’ STEM teaching intentions with respect to the department and grade level. Adıyaman University Journal of Educational Sciences, 8(2), 1–21.

    Google Scholar 

  • Kırılmazkaya, G. (2017). Investigation of elementary pre-service teachers’ opinions on STEM teaching (Şanlıurfa sample). Harran Educational Journal, 2(2), 59–73.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Kotsopoulos, D., Floyd, L., Khan, S., Namukasa, I. K., Somanath, S., Weber, J., & Yiu, C. (2017). A pedagogical framework for computational thinking. Digital Experiences in Mathematics Education, 3(2), 154–171.

    Article  Google Scholar 

  • Lin, K. Y., & Williams, P. J. (2016). Taiwanese preservice teachers’ science, technology, engineering, and mathematics teaching intention. International Journal of Science and Mathematics Education, 14(6), 1021–1036.

    Article  Google Scholar 

  • Moore, T. J., Stohlmann, M. S., Wang, H.-H., Tank, K. M., & Roehrig, G. H. (2014). Implementation and integration of engineering in K-12 STEM education. In J. Strobel, S. Purzer, & M. Cardella (Eds.), Engineering in precollege settings: Research into practice. West Lafayette: Purdue Press.

    Google Scholar 

  • P21 (2018). P21 Framework Definitions. Date of access: 15.08.2018. On the web: http://www.p21.org/storage/documents/P21_Framework_Definitions.pdf.

  • Pollack, S., Haberman, B. & Meerbaum-Salant, O. (2017). Constructing models in physics: What computational thinking occurs? International Conference on Computational Thinking Education. 13–15 July 2017. Hong Kong.

  • Psycharis, S. (2018). STEAM in education: A literature review on the role of computational thinking, engineering epistemology and computational science. Computational STEAM pedagogy (CSP). Scıentıfıc Culture, 4(2), 51–72.

    Google Scholar 

  • Roehrig, G. H., Moore, T. J., Wang, H. H., & Park, M. S. (2012). Is adding the enough? Investigating the impact of k-12 engineering standards on the implementation of STEM integration. School Science and Mathematics, 112(1), 31–44.

    Article  Google Scholar 

  • Román-González, M., Pérez-González, J. C., & Jiménez-Fernández, C. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the computational thinking test. Computers in Human Behavior, 72, 678–691.

    Article  Google Scholar 

  • Sanders, M. (2009). Stem, stem education, stemmania. The Technology Teacher, 68(4), 20–26.

    Google Scholar 

  • Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with k-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies, 18(2), 351–380.

    Article  Google Scholar 

  • Smith, J., & Karr-Kidwell, P. (2000). The interdisciplinary curriculum: A literary review and a manual for administrators and teachers. Retrieved from ERIC database. (ED443172).

  • Swanson, H., Anton, G., Bain, C., Horn, M. & Wilensky, U. (2017). Computational thinking in the science classroom. International Conference on Computational Thinking Education. 13-15 July 2017. Hong Kong.

  • Swanson, H., Irgens, G.A., Bain, C., Hall, K.R., Woods, P.A., & Rogge, C. (2018). Characterizing Computational Thinking in High School Science. Date of access: 15.08.2018. On the web: http://tidal.northwestern.edu/media/files/pubs/icls18a-sub2015-i8_Final.pdf

  • Tarkın-Çelikkıran, A., & Aydın-Günbatar, S. (2017). Investigation of pre-service chemistry teachers’ opinions about activities based on stem approach. Yüzüncü Yıl University Journal of Education Faculty, 14(1), 1624–1656.

    Google Scholar 

  • Tekerek, B., & Karakaya, F. (2018). STEM education awareness of pre-service science teachers. International Online Journal of Education and Teaching, 5(2), 348–359.

    Google Scholar 

  • Thomas, T. A. (2014). Elementary teachers’ receptivity to integrated science, technology, engineering, and mathematics (STEM) education in the elementary grades (doctoral dissertation, University of Nevada, Reno). Date of access: 10.08.2018. Retrived from: https://scholarworks.unr.edu/handle/11714/2852.

  • Wang, X. (2013). Why students choose STEM majors: Motivation, high school learning, and postsecondary context of support. American Educational Research Journal, 50(5), 1081–1121.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Wing, J. (2011). Research notebook: Computational thinking-what and why? Spring: The Link Magazine.

    Google Scholar 

  • Yamak, H., Bulut, N., & Dündar, S. (2014). The impact of activities on 5th grade students’ scientific process skills and their attitudes towards. Gazi University Journal of Educational Faculty, 34(2), 249–265.

    Google Scholar 

  • Yasar, O. (2013). Teaching science through computation. International Journal of Science, Technology &Society, 1, (1).

    Article  Google Scholar 

  • Yılmaz, H., Yiğit-Koyunkaya, M., Güler, F., & Güzey, S. (2017). Turkish adaptation of the attitudes toward science, technology, engineering, and mathematics (STEM) education scale. Kastamonu Education Journal, 25(5), 1787–1800.

    Google Scholar 

  • Young, S. P. (2018). How to equip students to be problem solvers through STEAM. JSSE Research Report, 32(8), 3–6.

    Google Scholar 

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Authors and Affiliations

  1. Faculty of Education, Department of Computer Education and Instructional Technology, Van Yüzüncü Yıl University, Van, Turkey

    Mustafa Serkan Günbatar

  2. Faculty of Education, Department of Elementary and Early Childhood Education, Van Yüzüncü Yıl University, Van, Turkey

    Hasan Bakırcı

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  1. Mustafa Serkan Günbatar
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  2. Hasan Bakırcı
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Correspondence to Mustafa Serkan Günbatar.

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Günbatar, M.S., Bakırcı, H. STEM teaching intention and computational thinking skills of pre-service teachers. Educ Inf Technol 24, 1615–1629 (2019). https://doi.org/10.1007/s10639-018-9849-5

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