PREDICTION MODEL FOR ENGINEERING STUDENTS’ PERFORMANCE IN DIFFERENTIAL EQUATIONS
DOI:
https://doi.org/10.18623/rvd.v23.4327Keywords:
Mathematical Prediction Model, Differential Equation, Calculus, Mathematics in the Modern World, Engineering Mathematics PerformanceAbstract
This study developed a Mathematical Prediction Model that determines which among the prerequisite Mathematics courses best predict success performance in the Differential Equations. The study used 646 students enrolled in different engineering programs of the Technological University of the Philippines Manila Campus during the 2nd Semester of School Year 2018-2019. This study utilized document content analysis as a data gathering technique. Findings revealed that in all of the Mathematics courses considered in this study: MMW, Calculus I, Calculus II and Differential Equations, most of the students clustered on grades 82-84 and 85-87. The model showed that the grades of students in MMW and Calculus II are not significantly related to their performance in Differential Equations. However, only grades in Calculus I are measured significantly related to Differential Equations.
References
Abad, M. L. I. (2020). Comparative assessment of academic performance in mathematics of college freshman civil engineering students: Inputs to numeracy enhancement extension project. Indian Journal of Science and Technology, 13(33), 3377–3386. https://doi.org/10.17485/IJST/v13i33.866
Agatep, J. L. E. (2018). Student performance in pre-calculus courses: Unbolting gate for success in differential calculus. Scholar Journal of Applied Sciences and Research, 1(3). https://www.innovationinfo.org/articles/SJASR-3-123.pdf
Aisha, B., Syed Zamri, S. N., Abedalaziz, N. A. M., Ahmad, M., & Satti, U. (2017). Factors affecting differential equation problem solving ability of students at pre-university level: A conceptual model. MOJES: Malaysian Online Journal of Educational Sciences, 5(4), 1–12. Retrieved from https://ejournal.um.edu.my/index.php/MOJES/article/view/12516
Aisha, B., Syed Zamri, S. N. A., Abedalaziz, N. A. M; Ahmad, M; Dad, H. (2018). Role of Students' Context Familiarity in Differential Equations Problem Solving at Pre University Level. Malaysian Online Journal of Educational Sciences, 6(4), 48-57.
Bengmark, M., Thunberg, H., & Winberg, M. (2020). First-year engineering students’ mathematics task performance and its relation to their motivational values and views about mathematics. Studies in Higher Education, 45(12), 2345–2357. https://doi.org/10.1080/03043797.2020.1849032
Buddo, C., Sherriffe, D., & McCarthy-Curvin, A. (2019). Realistic Mathematics Education (RME) approach: Exploring solving differential equations in the learning of calculus at The University of the West Indies, Mona. Journal of Education & Development in the Caribbean, 18(1), 183–225.
Chen, L., Jagota, V., & Kumar, A. (2022). Influence of mathematics on the academic performance of mechanical engineering students: A PLS-SEM approach. International Journal of System Assurance Engineering and Management, 13(1), 1–10. https://doi.org/10.1007/s13198-022-01803-1
Commission on Higher Education. (2013). CHED Memorandum Order No. 20, series of 2013: General Education Curriculum Holistic Understandings, Intellectual and Civic Competencies. https://ched.gov.ph/wp-content/uploads/2017/10/CMO-No.-20-s.-2013.pdfched.gov.ph
Commission on Higher Education. (2018). CHED on the Supreme Court decision on the removal of Filipino from the new General Education Curriculum. https://ched.gov.ph/ched-on-the-supreme-court-decision-on-the-removal-of-filipino-from-the-new-general-education-curriculum/
Eykhoff, P. (1974). System identification: Parameter and state estimation. Wiley.
George, R. (2019). Predictors for success in Calculus I (Paper ID #25942). 126th ASEE Annual Conference & Exposition. https://www.asee.org/public/conferences/140/papers/25942/view
Gerstle, K. (2019). Incorporating meaningful reflection into calculus assignments. PRIMUS, 29(1), 71–81. https://doi.org/10.1080/10511970.2018.1489312
Islam, M. M., & Al-Ghassani, A. (2015). Predicting college math success: Do high school performance and gender matter? Evidence from Sultan Qaboos University in Oman. International Journal of Higher Education, 4(2), 67–80. https://doi.org/10.5430/ijhe.v4n2p67
Kula Unver, S., Hidiroglu, C. N., Tekin Dede, A., & Bukova Guzel, E. (2018). Factors revealed while posing mathematical modelling problems by mathematics student teachers. European Journal of Educational Research, 7(4), 941–952. https://doi.org/10.12973/eu-jer.7.4.941
Linear Regression and Predictions. Statistics and Risk Regression. http://jukebox.esc13.net/untdeveloper/RM/Stats_Module_5/Stats_Module_56.html
López-Reyes, L. J., Jiménez-Gutiérrez, A. L., & Costilla-López, D. (2022). The effects of blended learning on the performance of engineering students in mathematical modeling. Education Sciences, 12(12), 931. https://doi.org/10.3390/educsci12120931
Lowe, J., Carter, M., & Cooper, T. (2018). Mathematical modelling in the junior secondary years: An approach incorporating mathematical technology. Australian Mathematics Teacher, 74(1), 4–12.
Lozada, E., Guerrero, C., & Medina, R. (2021). Classroom methodologies for teaching and learning ordinary differential equations: A systemic literature review and bibliometric analysis. Mathematics, 9(7), 745. https://doi.org/10.3390/math9070745
Marcos, M. C., Subia, G. S., & Ermita, P. P. (2020). Entry competencies and performance in mathematics of first-year engineering students in state universities in Region 3. TEST Engineering & Management, 83, 1–10. https://www.testmagzine.biz/index.php/testmagzine/article/view/9028
Mohammad, N. M., Demers, M., & Kopel, K. (2023). A comparison of flipped learning with traditional learning (face-to-face) in large calculus courses: The effects on students’ achievement and cognitive engagement. Journal of Mathematics and Science Teacher, 3(2), em051. https://doi.org/10.29333/mathsciteacher/13720
Moore, B. R., Höhna, S., May, M. R., Rannala, B., & Huelsenbeck, J. P. (2016). Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures. Proceedings of the National Academy of Sciences, 113(34), 9569–9574. https://doi.org/10.1073/pnas.1518659113
Online Sources:
Post, T. R., Medhanie, A., Harwell, M., Norman, K. W., Dupuis, D. N., et al. (2010). The impact of prior mathematics achievement on the relationship between high school mathematics curricula and postsecondary mathematics performance, course-taking, and persistence. Journal for Research in Mathematics Education, 41(3), 274–308.
Remo, L. M. (2019). Prediction and assessment of students’ performance in Mathematics in the Modern World (MMW). International Journal of Scientific & Technology Research, 8(4), 187–191.
Roman, A. G., & Villanueva, R. U. (2019). Competency acquisition, difficulty, and performance of first-year college students in Mathematics in the Modern World (MITMW). International Journal of Scientific & Technology Research, 8(12), 2801–2805.
Sagdullaeva, M.Z., & Atabekovich, Y.S. (2023). The Importance of Mathematics in the Field of Engineering. European International Journal of Multidisciplinary Research and Management Studies. DOI: https://doi.org/10.55640/eijmrms-03-03-01
Strickland J (2015) Predictive modeling and analytics. The rest of the story. Lulu Press.
Sule, B. O., & Saporu, F. W. O. (2015). A logistic regression model of students’ academic performance in University of Maiduguri, Maiduguri, Nigeria. Mathematical Theory and Modeling, 5(1), 124–136.
Van de Sande, C., & Reiser, M. (2018). The effect of summer break on engineering student success in calculus. International Journal of Research in Education and Science, 4(2), 349–357. https://doi.org/10.21890/ijres.428946
Yushau, B., & Omar, M. H. (2019). Investigating the role of the preparatory year program courses as predictors of first calculus course grade: A longitudinal study. King Fahd University of Petroleum & Minerals Technical Report Series, 1–23.
Downloads
Published
How to Cite
Issue
Section
License
I (we) submit this article which is original and unpublished, of my (our) own authorship, to the evaluation of the Veredas do Direito Journal, and agree that the related copyrights will become exclusive property of the Journal, being prohibited any partial or total copy in any other part or other printed or online communication vehicle dissociated from the Veredas do Direito Journal, without the necessary and prior authorization that should be requested in writing to Editor in Chief. I (we) also declare that there is no conflict of interest between the articles theme, the author (s) and enterprises, institutions or individuals.
I (we) recognize that the Veredas do Direito Journal is licensed under a CREATIVE COMMONS LICENSE.
Licença Creative Commons Attribution 3.0
