Mathematical Resilience and Academic Science Emotion in Students: New Insights from Canonical Correlation Analysis
DOI:
10.29303/jppipa.v11i4.8838Published:
2025-04-30Downloads
Abstract
This research aims to explore the correlation between mathematical resilience and academic science emotion and provides new insights into this association through the application of canonical correlation analysis. The study involved a sample of 191 students from a state university in Central Java, Indonesia. Participants completed self-report measures to assess their levels of mathematical resilience and academic science emotion. Data was collected by randomly distributing questionnaires to students, evaluating five indicators of academic resilience (self-efficacy, planning, control, low anxiety, persistence) and three indicators of science emotions (class-related emotions, learning-related emotions, test emotions). Canonical correlation analysis was conducted to examine the multidimensional relationship between these variables and identify underlying patterns and associations. The analysis, conducted using R programming, yielded canonical correlation coefficients of 0.785, 0.396, and 0.119, indicating a significant positive linear relationship between the analyzed variables. These findings provide insight for educators and policymakers to design interventions that enhance both mathematical resilience and emotional well-being in science education
Keywords:
Academic Canonical correlation Mathematical resilience Science emotionReferences
Arribathi, A. H., Suwarto, Miftakhu Rosyad, A., Budiarto, M., Supriyanti, D., & Mulyati, F. (2021). An analysis of student learning anxiety during the COVID-19 pandemic: a study in Higher Education. The Journal of Continuing Higher Education, 69(3), 192–205. https://doi.org/https://doi.org/10.1080/07377363.2020.1847971
Chamdani, M., Mahmudah, U., & Fatimah, S. (2021). Analyzing the Mental Health of Students in Dealing with the Coronavirus Disease Pandemic (Covid-19). JPI (Jurnal Pendidikan Indonesia), 10(4).
Fong, C. J., Kremer, K. P., Hill-Troglin Cox, C., & Lawson, C. A. (2021). Expectancy-value profiles in math and science: A person-centered approach to cross-domain motivation with academic and STEM-related outcomes. Contemporary Educational Psychology, 65, 101962. https://doi.org/10.1016/J.CEDPSYCH.2021.101962
Gómez‐Rios, M. D., Paredes‐Velasco, M., Hernández‐Beleño, R. D., & Fuentes‐Pinargote, J. A. (2023). Analysis of emotions in the use of augmented reality technologies in education: A systematic review. Computer Applications in Engineering Education, 31(1), 216–234. https://doi.org/https://doi.org/10.1002/cae.22593
Härdle, W. K., & Simar, L. (2015). Applied multivariate statistical analysis, fourth edition. In Applied Multivariate Statistical Analysis, Fourth Edition. Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-662-45171-7
Knopik, T., & Oszwa, U. (2021). E-cooperative problem solving as a strategy for learning mathematics during the COVID-19 pandemic. Education in the Knowledge Society (EKS), 22, e25176–e25176. https://doi.org/https://doi.org/10.14201/eks.25176
Levy, H. E., Fares, L., & Rubinsten, O. (2021). Math anxiety affects females’ vocational interests. Journal of Experimental Child Psychology, 210, 105214. https://doi.org/10.1016/J.JECP.2021.105214
Mahmudah, U., Lola, M. S., Fatimah, S., & Suryandari, K. C. (2022). Academic Resilience and Science Academic Emotion in Numeration under Online Learning: Predictive Capacity of an Artificial Neural Network. Jurnal Pendidikan IPA Indonesia, 11(4), 542–551. https://doi.org/https://doi.org/10.15294/jpii.v11i4.39091
Martin, A. J., & Marsh, H. W. (2006). Academic resilience and its psychological and educational correlates: A construct validity approach. Psychology in the Schools, 43(3), 267–281. https://doi.org/10.1002/pits.20149
Miao, M., Hu, W., Xu, B., Zhang, J., Rodrigues, J. J. P. C., & de Albuquerque, V. H. C. (2021). Automated CCA-MWF algorithm for unsupervised identification and removal of EOG artifacts from EEG. IEEE Journal of Biomedical and Health Informatics, 26(8), 3607–3617. https://doi.org/https://doi.org/10.1109/JBHI.2021.3131186
Mulbar, U., & Bahri, A. (2021). Scientific Literacy Skills of Students: Problem of Biology Teaching in Junior High School in South Sulawesi, Indonesia. International Journal of Instruction, 14(3). https://doi.org/https://doi.org/10.29333/iji.2021.14349a
Nisrina, H., Agustin, D. S. R., & Mahmudah, U. (2021). Etnomatematika: Analisis Problem Solving Pada Mata Kuliah Program Linier Berbasis Kearifan Lokal. JMPM: Jurnal Matematika Dan Pendidikan Matematika, 6(1), 72–80.
Pekrun, R., Goetz, T., Frenzel, A. C., Barchfeld, P., & Perry, R. P. (2011). Measuring emotions in students’ learning and performance: The Achievement Emotions Questionnaire (AEQ). Contemporary Educational Psychology, 36(1), 36–48. https://doi.org/10.1016/J.CEDPSYCH.2010.10.002
Rohayana, A. D., & Mahmudah, U. (2018). Canonical Correlation for Analyzing the Relationship between Educational Attainment and Marriage of Indonesian Youth. The New Eucational Review, 52(2). https://doi.org/10.15804/tner.2018.52.2.14
Starr, C. R., & Simpkins, S. D. (2021). High school students’ math and science gender stereotypes: relations with their STEM outcomes and socializers’ stereotypes. Social Psychology of Education, 24(1), 273–298. https://doi.org/10.1007/s11218-021-09611-4
Thompson, M. E. (2021). Grade Expectations: The Role of First-Year Grades in Predicting the Pursuit of STEM Majors for First- and Continuing-Generation Students. Https://Doi.Org/10.1080/00221546.2021.1907169, 92(6), 961–985. https://doi.org/10.1080/00221546.2021.1907169
Wang, H.-T., Smallwood, J., Mourao-Miranda, J., Xia, C. H., Satterthwaite, T. D., Bassett, D. S., & Bzdok, D. (2020). Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists. NeuroImage, 216, 116745. https://doi.org/https://doi.org/10.1016/j.neuroimage.2020.116745
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