Computational thinking and its relationship to the statistical problem-solving reluctance among the higher and lower level of mathematics phobia for students of the College of Education

  • Mahmoud Ali Moussa Lecturer of Assessment and Educational Evaluation, College of Education, Suez Canal university, Egypt. mahmod567@yahoo.com
  • Hisham Ibrahim Ismael Elnersh Professor of Educational Psychology, College of Education, Port Said University, Egypt, elnersh@edu.psu.edu.eg
Keywords: Mathematics phobia; Computational thinking; Problem-solving reluctance

Abstract

The study aimed to investigate the relationship between computational thinking and statistical problem-solving reluctance among high and low mathematics students in the College of Education. The study sample amounted to 115 male and female students, and it is an available sample from the Ismailia and Port said College of Education College. The study translated the computational thinking, the problem-solving reluctance, and the mathematics phobia scale. The confirmatory factor analysis tested the validity of the study scales, and it was appropriate to the essence of the sample in the Egyptian environment. The study depended on a score of 99 cut-off point for the Maths phobia scale according to the median score, which corresponds to the degree. The results showed the superiority of those with low Maths phobia in computational thinking. Higher Maths phobia tends to the problem-solving reluctant. The findings showed that there is a negative relationship between the division and the statistical problem-solving reluctance for the lower phobia level and without the presence of phobia. It was noted that there were no relationships between problem-solving reluctance with summarization, evaluation, and generalization. There were no differences in performance between the undergraduate and postgraduate levels on the scale of computational thinking and the scale of problem-solving reluctance, and the three study variables were not affected by the Participants' age.

Downloads

Download data is not yet available.

References

أسماء الجمال (2016). أثر استخدام استراتيجية ويتلي في تنمية التفكير الرياضيّ وخفض قلق الرياضيّات لدى طلبة الصّف التّاسع الأساسّي في الأردنّ. رسالة ماجستير غير منشورة. كلية العلوم التربوية. إربد. الأردن.
علي فارس (2018). العلاقة بين قلق الرياضيات والقدرة علي حل المشكلات الرياضياتية لدي التلاميذ السنة الثالثة ثانوي. مجلة حقائق للدراسات النفسية والاجتماعية. 3(9). 12- 30.
Abbasi,M. Samadzadeh,M. & Shahbazzadegan,B (2012). Study of Mathematics Anxiety in High School Students and it's Relationship with Self-esteem and Teachers’ Personality Characteristics. Procedia-Social and Behavioral Sciences, 83, 1-6.
Ahmad, C. V. (2021). Causes of students’ reluctance to participate in classroom discussions. ASEAN Journal of Science and Engineering Education, 1(1), 47-62.
Angeli, C. (2022). The effects of scaffolded programming scripts on pre-service teachers’ computational thinking: Developing algorithmic thinking through programming robots. International Journal of Child-Computer Interaction, 31, 100329.
Baltaci, S. (2016).. Malaysian Online Journal of Educational Technology, 4(4), 18-35.
Carney, M., Paulding, K., & Champion, J. (2022). Efficient Assessment of Students’ Proportional Reasoning. Applied Measurement in Education, 1-17.
Ersoy, E., &Guner, P. (2015). The place of problem solving and mathematical thinking in the mathematical teaching. The Online Journal of New Horizons in Education-January, 5(1), 120-130.
Ertugrul-Akyol, B. (2019). Development of computational thinking scale: Validity and reliability study. International Journal of Educational Methodology, 5(3), 421-432.
Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational researcher, 42(1), 38-43.
Kania,N. Jatisunda,M. Suciawati,V & Nahdi,D (2020). Student mathematical anxiety: investigation on problem based learning. Journal of Physics Conference Series. 1613(1), 1-8.
Kátai, Z. (2015). The challenge of promoting algorithmic thinking of both sciences‐and humanities‐oriented learners. Journal of Computer Assisted Learning, 31(4), 287-299.
Kholid, M. N., Sa’Dijah, C., Hidayanto, E., &Permadi, H. (2022). Students’ reflective thinking pattern changes and characteristics of problem solving. Reflective Practice, 1-23.
Kooloos, C., Oolbekkink-Marchand, H., van Boven, S., Kaenders, R., & Heckman, G. (2022). Making sense of student mathematical thinking: the role of teacher mathematical thinking. Educational Studies in Mathematics, 1-22.
Kooloos, C., Oolbekkink-Marchand, H., van Boven, S., Kaenders, R., & Heckman, G. (2022). Making sense of student mathematical thinking: the role of teacher mathematical thinking. Educational Studies in Mathematics, 1-22.
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.
Liang, S. (2022). Habits of Mathematical Thinking and Development of Heuristics. Contemporary Mathematics and Science Education, 3(1).
Lourenço, M., Costa, C., Cruz, C., & Gonçalves, A. (2022, March). STUDENTS’REPRESENTATIONS IN A FLOWERBED CONSTRUCTION: A WINDOW FOR MATHEMATICAL THINKING AND LEARNING. In Proceedings of INTED2022 Conference (Vol. 7, p. 8th).
Lubin, A., Kana, L., Ducloy, N., Delteil, F., Perdry, H., &Mikaeloff, Y. (2022). Do children with mathematical learning disabilities use the inversion principle to solve three-term arithmetic problems?: The impact of presentation mode. Journal of Experimental Child Psychology, 216, 105343.
Marasabessy, R. (2021). Study of Mathematical Reasoning Ability for Mathematics Learning in Schools: A Literature Review. Indonesian Journal of Teaching in Science, 1(2), 79-90.
Marsh, H. W., &Balla, J. (1994). Goodness of fit in confirmatory factor analysis: The effects of sample size and model parsimony. Quality and Quantity, 28(2), 185-217.
Monrat, N., Phaksunchai, M., &Chonchaiya, R. (2022). Developing Students’ Mathematical Critical Thinking Skills Using Open-Ended Questions and Activities Based on Student Learning Preferences. Education Research International, 2022.
Nicol, D., Thomson, A., & Breslin, C. (2014). Rethinking feedback practices in higher education: a peer review perspective. Assessment & Evaluation in Higher Education, 39(1), 102-122.
Öztürk, G. (2021). Pre-Service Teachers' Skills in Analysing Achievements in Regard to the Revised Bloom's Taxonomy. International Journal of Progressive Education, 17(1), 277-293.‏
Rusyda, N. A.; Suherman; Dwina, F.; Manda, T. G. & Rusdinal, R. (2021). The Role of Mathematics Anxiety and Mathematical Problem-Solving Skill. Journal of Physics: Conference Series, 1742(1), 1-5.
Schneider,M. Beeres,K. Coban,L. Merz,S. Schmidt,S. Stricker,J & Smedt,B (2016). Associations of non-symbolic and symbolic numerical magnitude processing with mathematical competence: a meta-analysis. Journal of Developmental Science, 1-16.
Suinn, R. M., & Winston, E. H. (2003). The mathematics anxiety rating scale, a brief version: psychometric data. Psychological reports, 92(1), 167-173.
Suseelan, M., Chew, C. M., & Chin, H. (2022). School-Type Difference Among Rural Grade Four Malaysian Students’ Performance in Solving Mathematics Word Problems Involving Higher Order Thinking Skills. International Journal of Science and Mathematics Education, 1-21.
Tang, X., Yin, Y., Lin, Q., Hadad, R., &Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148, 103798.
Teuscher, D., Leatham, K. R., & Peterson, B. E. (2017). From a framework to a lens: Learning to notice student mathematical thinking. In Teacher noticing: Bridging and broadening perspectives, contexts, and frameworks (pp. 31-48). Springer, Cham.
Tsai, M. J., Liang, J. C., & Hsu, C. Y. (2021). The computational thinking scale for computer literacy education. Journal of Educational Computing Research, 59(4), 579-602.
Wing, J. (2006). Computational Thinking Communications of the ACM, 49 (3), 33-35.
Published
2023-12-15
How to Cite
Moussa, M., & Elnersh, H. (2023). Computational thinking and its relationship to the statistical problem-solving reluctance among the higher and lower level of mathematics phobia for students of the College of Education. International Journal of Research in Educational Sciences., 7(1), 133 - 176. Retrieved from http://iafh.net/index.php/IJRES/article/view/423
Section
Articles

Most read articles by the same author(s)