Conceptual Errors in Quadratic Function Problem Solving: Perspective of Economics Education Students
DOI:
https://doi.org/10.37010/nuc.v5i02.1875Keywords:
conceptual error, quadratic function, economic maths, students, learningAbstract
This study aims to identify errors made by students in solving problems about Quadratic Functions in the context of the application of economic mathematics. The method used in this research is qualitative research with a descriptive approach. The research subjects consisted of students of Economic Education Study Programme of Ndraprasta PGRI University. Data collection techniques are carried out systematically and in accordance with predetermined procedures. This systematic method involves measurement techniques to evaluate students' abilities in Quadratic Function Application material in Economics through the administration of a questionnaire containing 5 description questions. The results showed that students experienced errors in working on Quadratic Function material in the application of economic mathematics, where 39% of students did not understand the concept. In addition, 31.3% per cent of students did not understand the correct steps to solve the problem, and there were also errors in the process of solving the problem. Students' accuracy in solving problems is also relatively low, and 29.3% of students who are able to solve perfectly. Thus, the level of error in this material is still very high among students.
References
Ashcraft, M. H., & Krause, J. A. (2007). Working memory, math performance, and math anxiety. Psychonomic Bulletin & Review, 14, 243–248.
Bressoud, D., & Rasmussen, C. (2015). Seven characteristics of successful calculus programs. Notices of the AMS, 62(2), 144–146.
Engelbrecht, W. (2008). Technology Teachers’ Experience of an Industry-Sponsored, School-Focused Model for Continuing Professional Teacher Development. University of Johannesburg (South Africa).
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.
Heid, M. K. (2005). Technology in mathematics education: Tapping into visions of the future. Technology-Supported Mathematics Learning Environments, 67, 345.
Hutagaol, H. K. (2024). Pengaruh Dukungan Sosial Teman Sebaya Terhadap Kepercayaan Diri Siswa Di Sma Negeri 2 Kota Jambi. Universitas Jambi.
Kerslake, R. M., & Krishnamurti, C. (2024). New world, or out of this world? Columbus–an exploratory study of HASS and STEM success factors in the first “space” race. Accounting, Auditing & Accountability Journal.
Mkhatshwa, T. P. (2024). An investigation of business calculus students’ covariational reasoning, procedural knowledge and conceptual knowledge in the context of price elasticity of demand. Teaching Mathematics and Its Applications: An International Journal of the IMA, hrae004.
Scott, J., & Cano, S. (2024). Sports in principles of economics textbooks. Managerial Finance.
Sugiyono, M. (2008). Penelitian Kuantitatif Kualitatif dan R&D. Bandung: Alfabeta.
Sullivan, T. (2024). An Equity Centered Analysis of Course Coordination’s Effect on Undergraduate Calculus 1 Students’ Mathematics Identity. Clemson University.
Usodo, B. (2011). Profil intuisi mahasiswa dalam memecahkan masalah matematika ditinjau dari gaya kognitif field dependent dan field independent. Prosiding Seminar Nasional Matematika Dan Pendidikan Matematika UNS, 95–102.
Wang, S., Huang, Y., & Cao, G. (2024). Review on functional data classification. Wiley Interdisciplinary Reviews: Computational Statistics, 16(1), e1638.
Yasin, M., Garancang, S., & Hamzah, A. A. (2024). Metode dan Instrumen Pengumpulan Data (Kualitatif dan Kuantitatif). Journal of International Multidisciplinary Research, 2(3), 161–173.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Ahmad Fahrudin, Hamzah Robbani

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