Conditions and Problems of Computational Thinking Instruction in Lower Secondary Schools

Main Article Content

Kitiya Middleton
Praweenya Suwannatthachote

Abstract

       The objectives of this study were to examine the conditions and problems of computational thinking instruction in lower secondary students and to suggest directions for developing a learning model that supports computational thinking in lower secondary students. This research project applied quantitative and qualitative research methods by collecting data from twenty-four teachers. The methodologies were also included survey and an interview with five experts. (Item Objective Congruence: IOC = 0.98).  The data were analyzed by finding frequency, percentage, mean ( ) and standard deviation (S.D.) in each question. We also included inductive analysis by interpretation and drew conclusions from the information obtained from the interviews. The study revealed that teachers agreed that there are problems in computational thinking in the areas of problem decomposition and modularity. There are four factors affecting students' comprehension of computational thinking: 1) students; 2) teachers; 3) learning activities; and 4) other factors. Methods used to prepare students were first, analyzing the content / students / purposes; second, preparation of media and equipment, and third, the design of learning activities. The research findings, suggested that directions for developing a learning model consist of analyzing contents, students, and purpose, preparation of instructional media, and design of learning activities. Teachers should choose the teaching method that is most suitable for the students. Create computational thinking experience for students both in the classroom and outside the classroom; and create a community about computational thinking. Furthermore, teachers should develop their own computational thinking skills continually and should also promote computational thinking research. The research’s contribution is providing information for teachers to develop and improve teaching methods and models of computational thinking.

Downloads

Download data is not yet available.

Article Details

Section
บทความวิจัย (Research article)

References

Asbell-Clarke, J., Rowe, E., Almeda, V., Edwards, T., Bardar, E., Gasca, S., Baker, R. S., Scruggs, R. (2021). The development of students’ computational thinking practices in elementary- and middle-school classes using the learning game, Zoombinis. Computers in Human Behavior, 115 ; 106587.
Basu, S., Biswas, G., and Kinnebrew, J. (2017). Learner modeling for adaptive scaffolding in a Computational Thinking-based science learning environment. User Modeling and User-Adapted Interaction, 27(1) ; 5-53.
Brasiel, S., Close, K., Jeong, S., Lawanto, K., Janisiewicz, P., and Martin, T. (2017). Measuring Computational Thinking Development with the FUN! Tool. In P. J. Rich and C. B. Hodges (Eds.), Emerging Research, Practice, and Policy on Computational Thinking (pp. 327-347). Cham : Springer International Publishing.
Buitrago Flórez, F., Casallas, R., Hernández, M., Reyes, A., Restrepo, S., and Danies, G. (2017). Changing a Generation’s Way of Thinking: Teaching Computational Thinking Through Programming. Review of Educational Research, 87(4) ; 834-860.
Caeli, E. N., and Yadav, A. (2020). Unplugged Approaches to Computational Thinking: a Historical Perspective. TechTrends, 64(1) ; 29-36.
Eggen, P. D., and Kauchak, D. P. (2011). Strategies and models for teachers : teaching content and thinking skills. 6th ed. Boston : Pearson/Allyn and Bacon.
Eggen, P. D., and Kauchak, D. P. (2016). Educational Psychology: Windows on Classrooms. 10th ed. New Jersy : Pearson.
Flórez, F. B., Casallas, R., Hernández, M., Reyes, A., Restrepo, S., and Danies, G. (2017). Changing a Generation’s Way of Thinking: Teaching Computational Thinking Through Programming. Review of Educational Research, 87(4) ; 834–860.
Gleasman, C., and Kim, C. (2020). Pre-Service Teacher’s Use of Block-Based Programming and Computational Thinking to Teach Elementary Mathematics. Digital Experiences in Mathematics Education, 6(April 2020) ; 52–90.
Hannafin, M. J., Land, S., and Oliver, K. (1999). Open learning environments: Foundations, Methods, and Models. In C. M. Reigeluth (Ed.), Instructional-design theories and models Volume II: A new paradigm of Instructional theory. London : Lawrence erlbaum associates.
Hickmott, D., Prieto-Rodriguez, E., and Holmes, K. (2018). A Scoping Review of Studies on Computational Thinking in K–12 Mathematics Classrooms. Digital Experiences in Mathematics Education, 4(1) ; 48-69.
Hsu, T.-C., Chang, S.-C., and Hung, Y.-T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers and Education, 126(November 2018) ; 296-310.
International Society for Technology in Education. (2017). ISTE Standards for Students. Cited 28 2021, Retrieved Febuary 28, 2021, from https://www.iste.org/standards/for-students.
Kale, U., Akcaoglu, M., Cullen, T., Goh, D., Devine, L., Calvert, N., and Grise, K. (2018). Computational What? Relating Computational Thinking to Teaching. TechTrends, 62(6) ; 574-584.
Karl, B. (2017). Computational Thinking : A Beginner's Guide to Problem-solving and Programming. Swindon, UK : BCS, The Chartered Institute for IT.
Korkmaz, Ö., Çakir, R., and Özden, M. Y. (2017). A validity and reliability study of the computational thinking scales (CTS). Computers in Human Behavior, 72(2017) ; 558-569.
Lawanto, K., Close, K., Ames, C., and Brasiel, S. (2017). Exploring Strengths and Weaknesses in Middle School Students’ Computational Thinking in Scratch. In P. J. Rich and C. B. Hodges (Eds.), Emerging Research, Practice, and Policy on Computational Thinking (pp. 307-326). Cham: Springer International Publishing.
Lee, I., Grover, S., Martin, F., Pillai, S., and Malyn-Smith, J. (2020). Computational Thinking from a Disciplinary Perspective: Integrating Computational Thinking in K-12 Science, Technology, Engineering, and Mathematics Education. Journal of Science Education and Technology, 29(1) ; 1-8.
Lyon, J. A., and Magana, A. J. (2021). The use of engineering model-building activities to elicit computational thinking: A design-based research study. Journal of Engineering Education, 110(1) ; 184-206.
Malyn-Smith, J., and Angeli, C. (2020). Computational Thinking. In A. Tatnall (Ed.), Encyclopedia of Education and Information Technologies (pp. 333-340). Cham : Springer International Publishing.
Repenning, A., Basawapatna, A. R., and Escherle, N. A. (2017). Principles of Computational Thinking Tools. In P. J. Rich and C. B. Hodges (Eds.), Emerging Research, Practice, and Policy on Computational Thinking (pp. 291-305). Cham : Springer International Publishing.
Rose, S. P., Habgood, M. P. J., and Jay, T. (2017). An Exploration of the Role of Visual Programming Tools in the Development of Young Children's Computational Thinking. Electronic Journal of e-Learning, 15(4) ; 297-309.
Saputri, A. A., and Wilujeng, I. (2017). Developing Physics E-Scaffolding Teaching Media to Increase the Eleventh-Grade Students' Problem Solving Ability and Scientific Attitude. International Journal of Environmental and Science Education, 12(4) ; 729-745.
Song, D., Hong, H., and Oh, E. Y. (2021). Applying computational analysis of novice learners' computer programming patterns to reveal self-regulated learning, computational thinking, and learning performance. Computers in Human Behavior, 120(2021) ; 106746.
Tikva, C., and Tambouris, E. (2021). Mapping computational thinking through programming in K-12 education: A conceptual model based on a systematic literature Review. Computers and Education, 162(March 2021) ; 104083.
Vygotsky, L. S. (1979). The Development of Higher Forms of Attention in Childhood. Soviet Psychology, 18(1) ; 67-115.
Yadav, A., Good, J., Voogt, J., and Fisser, P. (2017). Computational Thinking as an Emerging Competence Domain. In M. Mulder (Ed.), Competence-based Vocational and Professional Education: Bridging the Worlds of Work and Education (pp. 1051-1067). Cham : Springer International Publishing.
Yildiz Durak, H. (2020). The Effects of Using Different Tools in Programming Teaching of Secondary School Students on Engagement, Computational Thinking and Reflective Thinking Skills for Problem Solving. Technology, Knowledge and Learning, 25(1) ; 179-195.