The quality of mathematical proficiency in solving geometry problem: difference cognitive independence and motivation
DOI:
https://doi.org/10.47750/pegegog.13.03.27Keywords:
level of independence, level of motivation, mathematical proficiencyAbstract
Mathematical proficiency is essential to supporting students' success in learning mathematics. It is the ability to use conceptual understanding, procedural fluency, strategic competence, adaptive reasoning, and productive disposition in problem-solving. Cognitive independence shows students' ability to process information. Meanwhile, motivation is related to things that encourage students to learn mathematics. This study aims to determine the effect of cognitive independence and motivation on mathematical proficiency. It involved 131 students and used a mixed method with Sequential Explanatory Design. The quantitative research part of the study was used to determine the effect of cognitive independence and motivation on mathematical proficiency using a multiple linear regression test. Furthermore, the qualitative research was used to deeply scrutinize the effect by using in-depth interviews. The results showed that students with high cognitive independence can process the knowledge that has been possessed logically while students with low cognitive independence did it illogically. Students with low motivation use trial and error strategies to maximize mathematical proficiency, while students with high motivation use analytical strategy.
Downloads
References
Abramovich, A. Z. Grinshpan, and D. L. Milligan . (2019). Teaching mathematics through concept motivation and action learning. Education Research International, 2019, 1-13. Doi: 10.1155/2019/3745406.
Abrams and F. Z. Belgrave, “Field Dependence,” Encycl. Cross-Cultural Psychol., pp. 545–547, 2013, doi: 10.1002/9781118339893.wbeccp221.
Alghadari, F., Herman, T., & Prabawanto, S. (2020). Factors affecting senior high school students to solve three-dimensional geometry problems. International Electronic Journal of Mathematics Education, 15(3), doi : 10.29333/iejme/8234.
Awaji, B. M. A. (2021). Investigating the effectiveness of using GeoGebra software on students ’ mathematical proficiency. Doctoral dissertation, University of Glasgow. 291. https://theses.gla.ac.uk/82594/
Awofala, A. O. A. (2017). Assessing senior secondary school students’ mathematical proficiency as related to gender and performance in mathematics in Nigeria. International Journal of Research in Education and Science, 3(2), 488–502, doi: 10.21890/ijres.327908.
Babakr, Z. H., Mohamedamin, P., & Kakamad, K. (2019). Piaget’s Cognitive Developmental Theory: Critical Review. Education Quarterly Reviews, 2(3), 517–524. https://doi.org/10.31014/aior.1993.02.03.84
Bernardo, A. B. (2019). Sociocultural dimensions of student motivation: Research approaches and insights from the Philippines. Asian Education Miracles
Budayasa, I. K., & Juniati, D. (2019). The Influence of Cognitive Style on Mathematical Communication of Prospective Math Teachers in Solving Problems. Journal of Physics: Conference Series, 1417(1), 012056, doi: 10.1088/1742-6596/1417/1/012056.
Cerbito, A. F. (2020). Comparative Analysis of Mathematics Proficiency and Attitudes Toward Mathematics of Senior High School Student. International Journal of Scientific and Research Publications (IJSRP), 10(05), 211–222. https://doi.org/10.29322/ijsrp.10.05.2020.p10125.
Cuneo, F., Antonietti, J. P., & Mohr, C. (2018). Unkept promises of cognitive styles: A new look at old measurements. PLoS ONE, 13(8), 1–19. https://doi.org/10.1371/journal.pone.0203115
E. Z. F. Liu and C. H. Lin. (2010). The survey study of mathematics motivated strategies for learning questionnaire (MMSLQ) for grade 10-12 Taiwanese students. TOJET: The Turkish Online Journal of Educational Technology, 9(2), 221-233
Groves, S. (2012). SEAMEO Regional Centre for Education in Science and Mathematics. Journal of Science and Mathematics Education in Southeast Asia, 35(2), 119–145. http://hdl.handle.net/10536/DRO/DU:30051321
Haviger, J., & Vojkůvková, I. (2014). The van Hiele geometry thinking levels: gender and school type differences. Procedia-Social and Behavioral Sciences, 112, 977-981, doi: 10.1016/j.sbspro.2014.01.1257.
Jawad, L.F. (2021). The Impact Of Innovative Matrix Strategy And The Problem Tree Strategy On The Mathematical Proficiency Of Intermediate Grade Female Students. Turkish Journal of Computer and Mathematics Education (TURCOMAT). 12(7), 3296–3305. https://www.turcomat.org/index.php/turkbilmat/article/view/4408
Juniati, D., & Budayasa, I. K. (2022). European Journal of Educational Research. European Journal of Educational Research, 11(1), 1–16. https://doi.org/10.12973/eu-jer.11.3.1379
Kilpatrick, J. (2001). Understanding mathematical literacy: The contribution of research. Educational Studies in Mathematics, 47(1), 101–116. https://doi.org/10.1023/A:1017973827514
Liu, X. (2013). Full-Text Citation Analysis : A New Method to Enhance. Journal of the American Society for Information Science and Technology, 64(July), 1852–1863. https://doi.org/10.1002/asi.23053
Mailizar, A. Almanthari, S. Maulina, and S. Bruce, “. (2020). Secondary School Mathematics Teachers' Views on E-Learning Implementation Barriers during the COVID-19 Pandemic: The Case of Indonesia. Eurasia journal of mathematics, science and technology education, 16(7). Doi: 10.29333/EJMSTE/8240.
Mazana, M. Y., Montero, C. S., & Casmir, R. O. (2018). Investigating Students’ Attitude towards Learning Mathematics. International Electronic Journal of Mathematics Education, 14(1), 207-231. https://doi.org/10.29333/iejme/3997
McCann, P. H. (1975). Training Mathematics Skills with Games. Research and Evaluation. 25(1).
Miles, M. B., Huberman, A. M., & Saldaña, J. (2018). Qualitative data analysis: A methods sourcebook. Sage publications. http://www.worldcat.org/oclc/1047532295.
Onwumere, O., & Reid*, N. (2014). Field Dependency and Performance in Mathematics. European Journal of Educational Research, 3(1), 43–57. https://doi.org/10.12973/eu-jer.3.1.43
Qiu, X., & Wu, S. sheng. (2019). Contextual variables of student math proficiency and their geographic variations in Missouri. Applied Geography, 109, 102040. https://doi.org/10.1016/j.apgeog.2019.102040
Rahman, M. S., Juniati, D., & Manuharawati. (2022). Strategic competence in solving-problem and productive disposition of high school students based on cognitive styles. AIP Conference Proceedings. 2577(1), 020053. https://doi.org/10.1063/5.0096029
Ramos, R. R., Baking, E. G., Quiambao, D. T., c. Nicdao, R., Nuqui, A. V, & Cruz, R. C. (2015). The reading comprehension and mathematics proficiency level of high school students and their correlates. Journal of Business & Management Studies, 1(2), 1-7. https://www.semanticscholar.-org/paper/THE-READING-COMPREHENSION-AND-MATHEMATICS-LEVEL-OF-Ramos-Baking/12c502f68f1c0c2a5003a27fe31294d99-847775b.
S. K. Cheung and J. L. Y. Kwan. (2021). Parents’ perceived goals for early mathematics learning and their relations with children's motivation to learn mathematics. Early Childhood Research Quarterly, 56, 90-102. Doi: 10.1016/j.ecresq.2021.03.003.
Son, A. L., & Fatimah, S. (2020). Students' Mathematical Problem-Solving Ability Based on Teaching Models Intervention and Cognitive Style. Journal on Mathematics Education, 11(2), 209-222. http://doi.org/10.22342/jme.11.2.10744.209-222.
Son, A. L., & Fatimah, S. (2020). Students' Mathematical Problem-Solving Ability Based on Teaching Models Intervention and Cognitive Style. Journal on Mathematics Education. 11(2), 209–222. http://doi.org/10.22342/jme.11.2.10744-.209-222.
Sudia, M., & Lambertus. (2017). Profile Of High School Student Mathematical Reasoning To Solve The Problem Mathematical Viewed From Cognitive Style. International Journal of Education and Research, 5(6), 163–174. Retrieved from https://www.ijern.com/journal/2017/June-2017/14.pdf.
Syukriani, A., Juniati, D., & Siswono, T. Y. E. (2017). Strategic competence of senior secondary school students in solving mathematics problem based on cognitive style. AIP Conference Proceedings, 1868(1), 050009. https://doi.org/10.1063/1.4995136.
Yeo, K. K. J. (2009). Secondary 2 Students' Difficulties in Solving Non-Routine Problems. International Journal for Mathematics Teaching and Learning.
Yuan, X., Zhang, X., Chen, C., & Avery, J. M. (2011). Seeking information with an information visualization system: A study of cognitive styles. Information Research, 16(4), 4-20. https://files.eric.ed.gov/fulltext/EJ956119.pdf.
Zolkower, B., Bressan, A. M., Pérez, S., & Gallego, M. F. (2020). From the bottom up—Reinventing realistic mathematics education in Southern Argentina. In International reflections on the Netherlands didactics of mathematics, 13, 133-166 https://doi.org/10.1007/978-3-030-20223-1_9.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Pegem Journal of Education and Instruction
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
