Learning Implementation based on Mathematical Modeling to Enhance Statistical Thinking Abilities in Statistics for Grade 8 Students
Article Sidebar
Main Article Content
Abstract
This research aimed to 1) investigate pedagogical guidelines for mathematical modeling-based learning to promote mathematical thinking, and 2) study the effects of this approach on the mathematical thinking of Grade 8 students in the topic of Statistics. The target group consisted of 39 Grade 8 students from an extra-large school in Phichit Province during the second semester of the 2025 academic year. The study utilized a Classroom Action Research design across four cycles, totaling 12 hours. Research instruments included lesson plans, learning reflection forms, activity sheets, and a mathematical thinking ability test. Data were validated through triangulation and analyzed using qualitative methods. The research findings revealed that: 1. Pedagogical guidelines for mathematical modeling-based learning should prioritize the roles of teachers and students in three key areas: 1) selecting real-world, open-ended, and meaningful situations to serve as a starting point for students to independently define the scope of their mathematical models; 2) utilizing scaffolding questions to prompt students to analyze conditions and initial agreements when transforming real-world problems into mathematical models; and 3) emphasizing the connection of results from the model back to the real-world context and validating their reasonableness, rather than focusing solely on computational accuracy. 2. Students demonstrated a sequential improvement in their mathematical thinking abilities through the mathematical modeling process. Based on the activity sheets, all aspects of the students' mathematical thinking abilities were at Level 2, ranked from highest to lowest as follows: reasoning, problem-solving, and representation. This contrasted with the results of the mathematical thinking ability test, which ranked the abilities from highest to lowest as follows: problem-solving, representation, and reasoning. These findings indicate that the mathematical modeling-based learning approach effectively reflects the development of students' mathematical thinking, particularly enhancing their capacities to solve, understand, execute, and conclude solutions to mathematical problems.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The Journal of Science and Science Education (JSSE) retain the right of all articles published in JSSE. The coresponding author or the authorized person on behalf of the authors must send the complete Copyright Transfer Form to JSSE before any article get published in JSSE.
Copyright Transfer Form
The JSSE request the coresponding author or the authorized person on behalf of the authors upload the manuscript under the together with the Copyright Transfer Form under the supplementary data. The guidline for uploading both manuscript and Copyright Transfer Form is shown below:
1. Upload the manuscript in the sub-menu, Article Component > Article Text.
2. Upload the the Copyright Transfer Form in the sub-menu, Article Component > Other.
Download Copyright Transfer Form
References
Aumpuan, N. and Chuasuwanthavee, C. (2022). Effects of problem-based learning management using daily life contexts on mathematical problem-solving ability (in Thai). Journal of Learning and Innovation, 2(1), 12-25.
Blomhoej, M. and Jensen, T. H. (2003). Developing mathematical modelling competence: Conceptual clarification and educational planning. Teaching Mathematics and its Applications: International Journal of the IMA, 22(3), 123-139.
Blum, W. (2011). Can modelling be taught and learnt? Some Answers from Empirical Research. In Trends in teaching and learning of mathematical modelling (pp. 15-30). Springer.
Blum, W. and Borromeo Ferri, R. (2009). Mathematical modelling: Can it be taught and learnt?. Journal of Mathematical Modelling and Application, 1(1), 45-58.
Blum, W. and Leiss, D. (2007). How do students' structures their modelling process? The theoretical framework of the solution plan and empirical results. In Mathematical Modelling: Education, Engineering and Economics. Chichester: Horwood.
Doğan, M. and Sir, M. (2022). Examination of middle school students' mathematical reasoning in the mathematical modeling process. Journal of Computer and Education Research, 10(19), 133–158.
English, L. D. (2006). Introduces statistical distributions through a data-modeling context. Teaching Statistics, 28(2), 34-39.
Gal, I. (2002). Adults' statistical literacy: Meanings, components, responsibilities. International Statistical Review, 70(1), 1-25.
Haines, C. and Crouch, R. (2007). Mathematical modelling and applications: Ability and competence frameworks. In Modelling and applications in mathematics education: The 14th ICMI study (pp. 417-424). Boston, MA: Springer.
Institute for the Promotion of Teaching Science and Technology. (2017). Manual for the Basic Education Core Curriculum: Mathematics (Revised Edition 2017) (in Thai). Bangkok: Kurusapa Printing House.
Kitkuekul, S. (2014). Science learning management: Directions for teachers in the 21st century (in Thai). Phetchabun: Juladis Printing.
Kriegler, S. (2004). Just what is algebraic thinking?. Arithmetic Teacher, 38(1), 38-43.
Lesh, R. and Doerr, H. M. (2003). Beyond constructivism: Models and modeling perspectives on mathematics problem solving, learning, and teaching. Mahwah, NJ: Lawrence Erlbaum Associates.
Makanong, A. (2014). Mathematical skills and processes: Development for progress (in Thai). Bangkok: Center for Textbook and Academic Documents, Faculty of Education, Chulalongkorn University.
Ministry of Education. (2019). Guidelines for learner competency development in basic education (in Thai). Bangkok: Agricultural Cooperative Federation of Thailand Printing House.
Mousoulides, N. G. (2011). Exploring the activity of mathematical modeling: The role of external representations. In Trends in teaching and learning of mathematical modelling: ICTMA 14 (pp. 525-535). Springer.
Muller, E. and Burkhardt, H. (2007). Applications and modelling for mathematics—overview. Modelling and applications in mathematics education: The 14th ICMI study, 267-274.
National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Reston, VA: Author.
Nentian, S. (2017). Mathematics learning management through real-world problems emphasizing mathematical modeling (in Thai). Journal of Education, Chulalongkorn University, 45(2), 238-253.
OECD. (2019). OECD Learning Compass 2030: A Framework for Education. OECD Publishing.
Schukajlow, S., Rellensmann, J. and Achmetli, K. (2024). Visual representations and mathematical modeling: {A}n experimental study on the effects of prompting students to draw. Educational Studies in Mathematics, 115(2), 185–203.
Srimasaka, W. and Supap, W. (2022). The development of mathematical problem solving and communication abilities of grade 7 students using active learning with scaffolding questions (in Thai). Naresuan University Educational Research Journal, 14(2), 89-102.
Sriraman, B. and Lesh, R. (2006). Modeling conceptions revisited. ZDM – International Journal on Mathematics Education, 38(3), 247-254.
Stillman, G. (2011). Applying metacognitive knowledge and strategies in applications and modelling tasks at secondary school. In Trends in teaching and learning of mathematical modelling: ICTMA 14 (pp. 165-174). Springer.
Vengvichit, K. (2020). The development of mathematical modeling competency and mathematical problem solving ability of grade 8 students using mathematical modeling-based learning (in Thai). Master’s Thesis. Nakhon Pathom: Silpakorn University.
Wessels, H. M. (2014). Levels of mathematical creativity in model-eliciting activities. Journal of Mathematical Modelling and Application, 1(9), 22-40.
Wulandari, S., Herman, T. and Fatimah, S. (2024). Enhancing students’ mathematical reasoning skills through mathematical modeling in statistical learning. Journal of Mathematics Education, 15(1), 45-62.
