676
Views
6
CrossRef citations to date
0
Altmetric
Articles

Evaluation and developmental suggestions on undergraduates’ computational thinking: a theoretical framework guided by Marzano’s new taxonomy

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 6588-6610 | Received 08 Jul 2021, Accepted 07 Feb 2022, Published online: 13 Mar 2022

References

  • Anderson, N. D. (2016). A call for computational thinking in undergraduate psychology. Psychology Learning & Teaching, 15(3), 226–234. https://doi.org/10.1177/1475725716659252
  • Angeli, C., & Valanides, N. (2020). Developing young children’s computational thinking with educational robotics: An interaction effect between gender and scaffolding strategy. Computers in Human Behavior, 105, 105954. https://doi.org/10.1016/j.chb.2019.03.018
  • Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661–670. https://doi.org/10.1016/j.robot.2015.10.008
  • 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
  • Bebras−Ireland. (2019). The Bebras computational thinking challenge. https://bebras.techweek.ie/
  • Birney, L., & McNamara, D. (2019). The curriculum and community enterprise for restoration science S.T.E.M. + C professional learning model: Expansion and enhancement. Journal of Curriculum and Teaching, 8(3), 122–131. https://doi.org/10.5430/jct.v8n3p122
  • Brennan, K., & Resnick, M. (2012, April 13–17). New frameworks for studying and assessing the development of computational thinking. Annual Meeting of the American Educational Research Association (pp. 1–25), Vancouver, BC, Canada.
  • Butler, D., & Leahy, M. (2021). Developing preservice teachers’ understanding of computational thinking: A constructionist approach. British Journal of Educational Technology, 52(3), 1060–1077. https://doi.org/10.1111/bjet.13090
  • Chevalier, M., Giang, C., Piatti, A., & Mondada, F. (2020). Fostering computational thinking through educational robotics: A model for creative computational problem solving. International Journal of STEM Education, 7(1), 39. https://doi.org/10.1186/s40594-020-00238-z
  • Curzon, P. (2015). Computational thinking: Searching to speak. http://teachinglondoncomputing.org/free-workshops/computational-thinking/searching-to-speak/
  • Dam, G. T., & Volman, M. L. (2004). Critical thinking as a citizenship competence: Teaching strategies. Learning and Instruction, 14(4), 359–379. https://doi.org/10.1016/j.learninstruc.2004.01.005
  • Dasuki, S., & Quaye, A. (2017). Undergraduate students’ failure in programming courses in institutions of higher education in developing countries: A Nigerian perspective. The Electronic Journal of Information Systems in Developing Countries, 76(1), 1–18. https://doi.org/10.1002/j.1681-4835.2016.tb00559.x
  • Denning, P. J., & Tedre, M. (2019). Computational thinking. MIT Press.
  • DeVellis, R. F. (1991). Scale development: Theory and application. SAGE.
  • Durak, H. Y., & Saritepeci, M. (2018). Analysis of the relation between computational thinking skills and various variables with the structural equation model. Computers & Education, 116, 191–202. https://doi.org/10.1016/j.compedu.2017.09.004
  • Edwards, B. D. (2010). Confirmatory factor analysis for applied research. Organizational Research Methods, 13(1), 214–217. https://doi.org/10.1177/1094428108323758
  • Espino, E., & González, G. (2016, September 13–16). Gender and computational thinking: Review of the literature and applications. The XVII International Conference on Human Computer Interaction (pp. 1–2), New York: ACM.
  • Evia, C., Sharp, M. R., & Pérez-Quiñones, M. A. (2015). Teaching structured authoring and DITA through rhetorical and computational thinking. IEEE Transactions on Professional Communication, 58(3), 328–343. http://works.bepress.com/matthew_sharp/3/ https://doi.org/10.1109/TPC.2016.2516639
  • Fields, D. A., Shaw, M. S., & Kafai, Y. B. (2018, August 21–25). Personal learning journeys: Reflective portfolios as “objects-to-learn-with” in an e-textiles high school class. V. Dagiene, & E. Jastu_e (Eds.), Constructionism 2018: Constructionism, computational thinking and educational innovation: Conference proceedings (pp. 213–223), Vilnius, Lithuani. http://www.constructionism2018.fsf.vu.lt/proceedings
  • Gagne, R. M., & Briggs, L. J. (1974). Principles of instructional design. Holt, Rinehart & Winston.
  • Gignac, G. E., & Szodorai, E. T. (2016). Effect size guidelines for individual differences researchers. Personality and Individual Differences, 102, 74–78. https://doi.org/10.1016/j.paid.2016.06.069
  • 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
  • Guzdial, M. (2008). Education paving the way for computational thinking. Communications of the ACM, 51(8), 25–27. https://doi.org/10.1145/1378704.1378713
  • He, M., Chen, W., Chen, X., Ye, X., Yang, F., & Wang, K. (2014). Analysis on the reform method of university computer basic course based on computational thinking. Computer Engineering and Science, 36(S1), 96–99. (In Chinese). https://doi.org/10.13966/j.cnki.kfjyyj.2008.02.001
  • ISTE. (2015). CT leadership toolkit. http://www.iste.org/docs/ctdocuments/ct-leadershipt-toolkit.pdf?sfvrsn¼4
  • Jun, S., Han, S., & Kim, S. (2017). Effect of design-based learning on improving computational thinking. Behaviour & Information Technology, 36(1), 43–53. https://doi.org/10.1080/0144929X.2016.1188415
  • Kale, U., Akcaoglu, M., Cullen, T., & Goh, D. (2018). Contextual factors influencing access to teaching computational thinking. Computers in the Schools, 35(2), 69–87. https://doi.org/10.1080/07380569.2018.1462630
  • Katai, Z. (2014). The challenge of promoting algorithmic thinking of both sciences- and humanities-oriented learners. Journal of Computer Assisted Learning, 31(4), 287–299. https://doi.org/10.1111/jcal.12070
  • Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). The 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
  • Lee, M., & Lee, J. (2021). Enhancing computational thinking skills in informatics in secondary education: The case of South Korea. Educational Technology Research and Development, 2021, 1–25. https://doi.org/10.1007/s11423-021-10035-2
  • Leonard, J., Mitchell, M., Barnes-Johnson, J., Unertl, A., Outka-Hill, J., Robinson, R., & Hester-Croff, C. (2018). Preparing teachers to engage rural students in computational thinking through robotics, game design, and culturally responsive teaching. Journal of Teacher Education, 69(4), 386–407. https://doi.org/10.1177/0022487117732317
  • Luo, F., Antonenko, P. D., & Davis, E. C. (2020). Exploring the evolution of two girls’ conceptions and practices in computational thinking in science. Computers & Education, 146, 103759. https://doi.org/10.1016/j.compedu.2019.103759
  • Lyon, J. A., & Magana, A. J. (2020). Computational thinking in higher education: A review of the literature. Computer Applications in Engineering Education, 28(5), 1174–1189. https://doi.org/10.1002/cae.22295
  • Marzano, R. J. (1998). A theory-based meta-analysis of research on instruction (technical report). Mid-continent Regional Educational Laboratory.
  • Marzano, R. J. (2001). Designing a new taxonomy of educational objectives. Corwin Press.
  • Marzano, R. J., & Kendall, J. S. (2007). The new taxonomy of educational objectives. Corwin Press.
  • Master, A., Cheryan, S., & Meltzoff, A. N. (2016). Computing whether she belongs: Stereotypes undermine girls’ interest and sense of belonging in computer science. Journal of Educational Psychology, 108(3), 424–437. https://doi.org/10.1037/edu0000061
  • Ministry of Education of the People’s Republic of China. (2011). Notice on the issuance of the catalogue of disciplines for degree awarding and Talent training (2011). http://www.moe.gov.cn/srcsite/A22/moe_833/201103/t20110308_116439.html
  • Ministry of Education of the People’s Republic of China. (2018). Notice on the publication of the list of computer curriculum reform projects in universities. http://edu.sh.gov.cn/xxgk_jyyw_gdjy_5/20200514/0015−gw_418212019002.html
  • Moreno−León, J., Robles, G., & Román−González, M. (2016). Code to learn: Where does it belong in the K−12 curriculum? Journal of Information Technology Education: Research, 15, 283–303. https://doi.org/10.28945/3521
  • Nouri, J., Zhang, L., Mannila, L., & Noren, E. (2020). Development of computational thinking, digital competence and 21st century skills when learning programming in K− 9. Education Inquiry, 11(1), 1–17. https://doi.org/10.1080/20004508.2019.1627844
  • NRC. (2011). Report of a workshop on the pedagogical aspects of computational thinking. Nat. Acad. Press. https://doi.org/10.17226/13170
  • Pan, T. T., Zhan, G. H., & Li, Z. H. (2016). Exploration on the cultivation of computational thinking ability in the teaching of PhotoShop. L. Huang, J. Cao & J. Gao (Eds.), Proceedings of the first international conference on information technology in education and learning (pp. 32–35). 1st International Conference on Information Technologies in Education and Learning (ICITEL), December 19–20.
  • Papert, S. (1980). Mindstorms: Children, computers and powerful ideas. Basic Books, Inc.
  • Plucker, J., Beghetto, R., & Dow, G. (2004). Why isn't creativity more important to educational psychologists? Potentials, pitfalls, and future directions in creativity research. Educational Psychologist, 39, 83–96. https://doi.org/10.1207/s15326985ep3902_1
  • Pompili, M., Tatarelli, R., Rogers, J. R., & Lester, D. (2007). The hopelessness scale: A factor analysis. Psychological Reports, 100(2), 375–378. https://doi.org/10.2466/pr0.100.2.375-378
  • Resnick, L. (1987). Education and learning to think. National Academy Press.
  • Román-González, M., Pérez-González, J., & Jiménez-Fernández, C. (2017). Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test. Computers in Human Behavior, 72, 678–691. https://doi.org/10.1016/j.chb.2016.08.047
  • Rose, S., Habgood, J., & Jay, T. (2018, October 4–5). Pirate plunder: Game-based computational thinking using Scratch blocks. 12th European Conference on Game Based Learning (pp. 556–564), Sophia Antipolis, France. SKEMA Business School
  • Sáez-López, J., Román-González, M., & Vázquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two year case study using “scratch” in five schools. Computers & Education, 97, 129–141. https://doi.org/10.1016/j.compedu.2016.03.003
  • Sheng, Q. L. (2008). Foster high-level ability of problem-solving: The systemic explanation of Marzano’ s taxonomy of cognitive objectives. Open Education Research, 14(2), 10–21. (In Chinese). https://doi.org/10.13966/j.cnki.kfjyyj.2008.02.001
  • Sousa, D. A., & Tomlinson, C. A. (2011). Differentiation and the brain: How neuroscience supports the learner-friendly classroom. Bloomington.
  • Sternberg, R. J., & Grigorenko, E. L. (1997). Are cognitive styles still in style? American Psychologist, 52(7), 700–712. https://doi.org/10.1037/0003-066X.52.7.700
  • Sun, L., Hu, L., Yang, W., Zhou, D., & Wang, X. (2020). STEM learning attitude predicts computational thinking skills among primary school students. Journal of Computer Assisted Learning, 37(2), 346–358.
  • Sun, L., Hu, L., & Zhou, D. (2021a). Which way of design programming activities is more effective to promote K-12 students’ computational thinking skills? A meta-analysis. Journal of Computer Assisted Learning, 37(4), 1048–1062.
  • Sun, L., Hu, L., & Zhou, D. (2021b). Improving 7th-graders’ computational thinking skills through unplugged programming activities: A study on the influence of multiple factors. Thinking Skills and Creativity, 42, 1000926.
  • Tang, X. D., Yin, Y., Lin, Q., Hadad, R., & Zhai, X.M. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148, 103798. https://doi.org/10.1016/j.compedu.2019.103798
  • Tikva, C., & Tambouris, E. (2020). Mapping computational thinking through programming in K-12 education: A conceptual model based on a systematic literature review. Computers & Education, 162, 104083. https://doi.org/10.1016/j.compedu.2020.104083
  • Tsai, M. J., Liang, C. J., Lee, S. W., & Hsu, C. Y. (2021). Structural validation for the developmental model of computational thinking. Journal of Educational Computing Research, 60, 1–18. https://doi.org/10.1177/07356331211017794
  • 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. https://doi.org/10.1098/rsta.2008.0118
  • Wing, J. M. (2010). Computational thinking: What and why? http://www.cs.cmu.edu/~CompThink/resources/TheLinkWing.pdf,2010-11-17.
  • Xing, W. (2021). Large-scale path modeling of remixing to computational thinking. Interactive Learning Environments, 29(3), 414–427. https://doi.org/10.1080/10494820.2019.1573199
  • Yagci, M. (2019). A valid and reliable tool for examining computational thinking skills. Education and Information Technologies, 24(1), 929–951. https://doi.org/10.1007/s10639-018-9801-8
  • Yu, T., & Richardson, J. (2015). Examining reliability and validity of a Korean version of the community of inquiry instrument using exploratory and confirmatory factor analysis. The Internet and Higher Education, 25, 45–52. https://doi.org/10.1016/j.iheduc.2014.12.004

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.