Improving Students' Mathematical Disposition with the Knowledge Sharing Learning Strategy
DOI:
https://doi.org/10.33541/edumatsains.v10i3.7620Keywords:
mathematical disposition, knowledge sharing Learning, learning strategyAbstract
Applied graph is a compulsory course in the Pamulang Informatics Engineering study program. Applied graph is a course that teaches the concepts, algorithms, and practical applications of graph theory. Graph theory itself is a branch of discrete mathematics that studies network structures consisting of nodes (vertices) connected by edges (arcs). Although the applied graph course is an important course to study, some students still consider it difficult to understand. The purpose of this study was to determine whether there was a difference in the mathematical disposition of students who were given treatment using the knowledge sharing strategy and students who were given treatment using the expository strategy. The research method used was a quantitative method with a quasi-experimental design. The sample used in this study consisted of 59 students. Data collection was carried out using a mathematical disposition questionnaire. The instrument was tested for validity on 136 students, with 29 valid statements, and for reliability using Cronbach's alpha coefficient 0.992. The analysis technique used an independent t-test with a p-value of 0.005. The results of this study indicate that there is a difference in the mathematical disposition of students who were given the knowledge sharing strategy and students who were given the expository strategy.
References
Almerino, P. M., Etcuban, J. O., Jose, C. G. De, Almerino, J. G. F., & Leyte, S. (2019). Students ’ Affective Belief as the Component in Mathematical Disposition. IEJME: INTERNATIONAL ELECTRONIC JOURNAL OF MATHEMATICS EDUCATION, 14(3), 475–487.
Anthony, G., & Walshaw, M. (2009). Characteristics of Effective Teaching of Mathematics : A View from the West. Journal of Mathematics Education, 2(2), 147–164.
Azizah, D., & Fadlikah, V. (2023). Analysis Of Mathematical Problem-Solving Ability In View Of Mathematical Disposition. Jurnal Matematika Dan Pendidikan Matematika, 8, 153–169.
Deal, E., Mooney, E., Cullen, A., Kroesch, A., Priya, N., Corven, J., Macdonald, B., Deal, E., Mooney, E., Cullen, A., Kroesch, A., & Priya, N. (2025). Investigations in Mathematics Learning Accessing and Assessing Components of Elementary and Middle School Students ’ Mathematical Disposition Through Metaphors. Investigations in Mathematics Learning, 17(3), 259–275. https://doi.org/10.1080/19477503.2024.2419291
Dina, Z. H., & Ikhsan, M. (2019). The Improvement of Communication and Mathematical Disposition Abilities through Discovery Learning Model in Junior High School. JRAMathEdu: Journal of Research and Advances in Mathematics Education, 4(1), 11–22.
Feldhaus, C. (2014). How Pre Service Elementary School Teachers‟ Mathematical Disposition are Influenced by School Mathematics. American International Journal of Contemporary Research, 4(6).
Fitrianna, A. Y., Dinia, S., & Nurhafifah, A. Y. (2018). Mathematical Representation Ability of Senior High School Students : An Evaluation from Students ’ Mathematical Disposition. JRAMathEdu: Journal of Research and Advances in Mathematics Education, 3(1), 46–56.
Fitriya, Y., Wulandari, R., & Sumadi, C. D. (2023). ANALYSIS OF MATHEMATICAL DISPOSITION IN ELEMENTARY. Jurnal Cakrawala Pendas, 9(3), 475–487. https://doi.org/10.31949/jcp.v9i3.5127 p-ISSN:
Graven, M. (2012). Accessing and assessing young learner ’ s mathematical dispositions. South African Journal of Childhood Education, 2(1), 49–62.
Handayani, I., & Husnul, N. R. I. (2025). Comparative Effectiveness of ICT-Based APOS and M-APOS Learning Models on Students ’ Self-Efficacy Viewed from Initial Mathematical Ability. 13(3), 832–847.
Handayani, I., & Noviana, W. (2021). Perngaruh Model Apos Berbasis Ict Dan Model M-Apos Terhadap Self Efficacy Mahasiswa. Jurnal Pendidikan Glasser, 5(1), 1. https://doi.org/10.32529/glasser.v5i1.370
Hendy, H., Irawan, M. I., Mukhlash, I., & Rinurwati, R. (2025). Hybrid ant colony optimization algorithm with binary gray wolf optimization for detour metric dimension and bi-metric dimension problem. Communications in Combinatorics and Optimization, xx(x), 1–26.
Huffaker, D. A., & Calvert, S. L. (2003). THE NEW SCIENCE OF LEARNING : ACTIVE LEARNING , METACOGNITION , AND TRANSFER OF KNOWLEDGE IN E-LEARNING APPLICATIONS *. Journal Educational Research, 29(3), 325–334. https://doi.org/10.2190/4T89-30W2-DHTM-RTQ2
Hutajulu, M., Wijaya, T. T., Hidayat, W., Info, A., & Solving, P. (2019). THE EFFECT OF MATHEMATICAL DISPOSITION AND LEARNING MOTIVATION ON PROBLEM SOLVING : Infinity: Journal of Mathematics Education, 8(2), 229–238.
Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 38(5), 365–379. https://doi.org/10.3102/0013189X09339057
Kamid, K., Huda, N., Syafmen, W., Sufri, S., & Sofnidar, S. (2021). The relationship between students’ mathematical disposition and their learning outcomes. Journal of Education and Learning (EduLearn), 15(3), 376–382. https://doi.org/10.11591/edulearn.v15i3.17604
Kusmaryono, I., Suyitno, H., Dwijanto, D., & Dwidayati, N. (2019). The Effect of Mathematical Disposition on Mathematical Power Formation : Review of Dispositional Mental Functions. International Journal of Instruction, 12(1), 343–356.
Lin, S., & Tai, W.-C. (2016). A Longitudinal Study for Types and Changes of Students ’ Mathematical Disposition. Universal Journal of Educational Research, 4(8), 1903–1911. https://doi.org/10.13189/ujer.2016.040821
National Council of Teachers of Mathematics. (1989). Curriculum and evaluation standards for school mathematics. NCTM.
OECD. (2023). PISA 2022 Result (Colume I): The State of Learning and Equity in Education. OECD Publishing.
Provasnik, S., Kastberg, D., Ferraro, D., Lemanski, N., Roey, S., & Jenkins, F. (2012). Highlights from TIMSS 2011 Mathematics and Science Achievement of U.S. Fourth- and Eighth-Grade Students in an International Context (NCES 2013-009 Revised). National Center for Education Statistics, Institut of Education Sciences, U.S. Department of Education.
Sari, D. P. (2020). IMPLEMENTATION OF REACT STRATEGY TO DEVELOP MATHEMATICAL REPRESENTATION , REASONING , AND DISPOSITION ABILITY. Journal on Mathematics Education, 11(1), 145–156. https://doi.org/10.22342/jme.11.1.7806.145-156
Setiawan, Y. E. (2023). The Effect of Mathematical Disposition on Basic Mathematical Abilities in the Online Learning. Journal of Education Research and Evaluation, 7(2), 259–266. https://doi.org/10.23887/jere.v7i2.58437
Ulia, N., Islam, U., Agung, S., Islam, U., & Agung, S. (2021). Mathematical disposition of students ’, teachers , and parents in distance learning : A survey. Premiere Educandum: Jurnal Pendidikan Dasar Dan Pembelajaran, 11(May), 147–159. https://doi.org/10.25273/pe.v11i1.8869
White, D. Y., Murray, E. C., & Brunaud-vega, V. (2012). Discovering Multicultural Mathematics Dispositions. Journal of Urban Mathematics Education, 5(1), 31–43.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Ita Handayani, Widyah Noviana, Weni Gurita Aedi

This work is licensed under a Creative Commons Attribution 4.0 International License.


















_(1).png)