Exploring Latent Class Profiles of Mathematics Performance: Insights from PISA 2022 Using Growth Mindset Indicators and Group Comparison Analysis
Keywords:
Growth Mindset, Group Comparison Analysis, Latent Class Analysis, Mathematics Performance, PISA
Abstract
Purpose of the study: This study investigates the influence of a growth mindset on Filipino students' mathematics performance as assessed in the PISA 2022 survey. The research aims to identify distinct latent class profiles based on growth mindset indicators and to explore their relationship with mathematics achievement.
Methodology: Data from 6,791 Filipino students who participated in PISA 2022 were analyzed. Latent Class Analysis (LCA) was employed to classify students into distinct mindset profiles, while Analysis of Variance (ANOVA) assessed differences in mathematics performance across these groups. Tukey’s post hoc analysis was used to examine pairwise differences further.
Main Findings: Based on the data, three distinct latent classes were identified among Filipino learners: Limitation Acceptors (50%), Optimistic Learners (17%), and Mindset Explorers (33%). Optimistic Learners, who exhibited a strong growth mindset and disagreed with statements endorsing fixed intelligence, achieved the highest average scores in mathematics. ANOVA results confirmed significant differences in mathematics performance among these three groups. Tukey’s post hoc analysis further revealed that Optimistic Learners significantly outperformed Limitation Acceptors and Mindset Explorers, while no significant performance difference was found between Limitation Acceptors and Mindset Explorers.
Novelty/Originality of this study: These findings highlight the critical role of a growth mindset in shaping academic achievement and suggest that fostering growth-oriented beliefs could enhance mathematics performance. This study provides actionable insights for educators and policymakers, emphasizing the need for targeted interventions to cultivate positive beliefs about intelligence among students.
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[3] OECD, PISA 2022 Results (Volume II): Learning During – and From – Disruption. in PISA. OECD, 2023. doi: 10.1787/a97db61c-en.
[4] Dr., Department of Mathematics Education, Faculty of Education, Akdeniz University, Turkey, kozaciftci@gmail.com, Ş. K. Çiftçi, P. Yıldız, and Department of Mathematics Education, Faculty of Education, Çanakkale 18 Mart University, Turkey, akdalpinar@gmail.com, “The Effect of Self-Confidence on Mathematics Achievement: The Meta-Analysis of Trends in International Mathematics and Science Study (TIMSS),” Int. J. Instr., vol. 12, no. 2, pp. 683–694, Apr. 2019, doi: 10.29333/iji.2019.12243a.
[5] T. Asparouhov and B. Muthén, “Latent Variable Centering of Predictors and Mediators in Multilevel and Time-Series Models,” Struct. Equ. Model. Multidiscip. J., vol. 26, no. 1, pp. 119–142, Jan. 2019, doi: 10.1080/10705511.2018.1511375.
[6] S. L. Ferguson, E. W. G. Moore, and D. M. Hull, “Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers,” Int. J. Behav. Dev., vol. 44, no. 5, pp. 458–468, Sep. 2020, doi: 10.1177/0165025419881721.
[7] N. A. Nacion and E. A. Balila, “Latent Class Analysis of Learning Strategies and Metacognition: Their Effects on Mathematics Performance”.
[8] S. Yalcin, “Determining the Relationships between Selected Variables and Latent Classes in Students’ PISA Achievement,” Int. J. Res. Educ. Sci., pp. 589–589, Jul. 2017, doi: 10.21890/ijres.328089.
[9] J. B. Medina, “Promoting Collaboration in InFleX Modality: A Case on Teaching History of Mathematics,” J. Pendidik. Mat. Kudus, vol. 6, no. 1, p. 1, Jun. 2023, doi: 10.21043/jpmk.v6i1.19405.
[10] R. Z. Dela Cruz and G. D. Hernandez, “Challenges of public-school elementary mathematics teaching in the new normal,” Indones. J. Soc. Sci., vol. 15, no. 1, pp. 8–20, Jun. 2023, doi: 10.20473/ijss.v15i1.40340.
[11] B. Atweh, M. R. C. Lapinid, A. A. Limjap, L. E. Elipane, M. Basister, and R. L. Conde, “Critical Analysis of Mathematics Education Doctoral Dissertations in the Philippines: 2009–2021,” in Asian Research in Mathematics Education, B. Atweh, L. Fan, and C. P. Vistro-Yu, Eds., in Mathematics Education – An Asian Perspective. , Singapore: Springer Nature Singapore, 2023, pp. 69–95. doi: 10.1007/978-981-99-0643-7_4.
[12] A. B. I. Bernardo, M. O. C. Ii, M. R. C. Lapinid, J. M. M. Teves, S. A. Yap, and U. C. Chua, “Contrasting Profiles of Low-Performing Mathematics Students in Public and Private Schools in the Philippines: Insights from Machine Learning,” 2022.
[13] V. Lopez, “The Nexus between English Language Proficiency and Mathematics Competency: The Case of Filipino K-12 Graduates,” AIDE Interdiscip. Res. J., vol. 3, pp. 527–577, Apr. 2023, doi: 10.56648/aide-irj.v3i1.84.
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[15] E. Peteros, A. Gamboa, J. O. Etcuban, A. Dinauanao, R. Sitoy, and R. Arcadio, “Factors Affecting Mathematics Performance of Junior High School Students,” Int. Electron. J. Math. Educ., vol. 15, no. 1, Sep. 2019, doi: 10.29333/iejme/5938.
[16] E. N. Ocampo, F. D. Mobo, and A. L. Cutillas, “Exploring the Relationship Between Mathematics Performance and Learn-ing Style Among Grade 8 Students,” Int. J. Multidiscip. Appl. Bus. Educ. Res., vol. 4, no. 4, pp. 1165–1172, Apr. 2023, doi: 10.11594/ijmaber.04.04.14.
[17] M. D. L. Mata, V. Monteiro, and F. Peixoto, “Attitudes towards Mathematics: Effects of Individual, Motivational, and Social Support Factors,” Child Dev. Res., vol. 2012, pp. 1–10, Oct. 2012, doi: 10.1155/2012/876028.
[18] N. Scammacca, A.-M. Fall, P. Capin, G. Roberts, and E. Swanson, “Examining factors affecting reading and math growth and achievement gaps in grades 1–5: A cohort-sequential longitudinal approach.,” J. Educ. Psychol., vol. 112, no. 4, pp. 718–734, May 2020, doi: 10.1037/edu0000400.
[19] G. D. Abalde and R. M. Oco, “Factors Associated with Mathematics Performance,” Asian Res. J. Math., vol. 19, no. 6, pp. 45–60, Apr. 2023, doi: 10.9734/arjom/2023/v19i6665.
[20] J. Mercader, M.-J. Presentación, R. Siegenthaler, V. Molinero, and A. Miranda, “Motivation and Mathematics Performance: A Longitudinal Study in Early Educational Stages,” Rev. Psicodidáct. Engl. Ed, vol. 22, no. 2, pp. 157–163, Jun. 2017, doi: 10.1016/j.psicoe.2017.05.008.
[21] F. Kolyda, “Fostering a growth mindset in higher education for inclusive learning for all,” J. Learn. Dev. High. Educ., no. 27, Apr. 2023, doi: 10.47408/jldhe.vi27.929.
[22] X. Xu, Q. Zhang, J. Sun, and Y. Wei, “A bibliometric review on latent topics and research trends in the growth mindset literature for mathematics education,” Front. Psychol., vol. 13, p. 1039761, Nov. 2022, doi: 10.3389/fpsyg.2022.1039761.
[23] L. Dong, X. Jia, and Y. Fei, “How growth mindset influences mathematics achievements: A study of Chinese middle school students,” Front. Psychol., vol. 14, p. 1148754, Mar. 2023, doi: 10.3389/fpsyg.2023.1148754.
[24] N. M. Lou and K. A. Noels, “Mindsets Matter for Linguistic Minority Students: Growth Mindsets Foster Greater Perceived Proficiency, Especially for Newcomers,” Mod. Lang. J., vol. 104, no. 4, pp. 739–756, Dec. 2020, doi: 10.1111/modl.12669.
[25] L. M. Collins and S. T. Lanza, “Latent Class and Latent Transition Analysis”.
[26] B. E. Weller, N. K. Bowen, and S. J. Faubert, “Latent Class Analysis: A Guide to Best Practice,” J. Black Psychol., vol. 46, no. 4, pp. 287–311, May 2020, doi: 10.1177/0095798420930932.
[27] B. Muthen, “Bayesian Analysis In Mplus: A Brief Introduction”.
[28] T. Wen Chun and L. Su Wei, “Relationship between problem-solving style and mathematical literacy,” Educ. Res. Rev., vol. 10, no. 11, pp. 1480–1486, Jun. 2015, doi: 10.5897/ERR2015.2266.
[29] A. B. I. Bernardo, “Socioeconomic status moderates the relationship between growth mindset and learning in mathematics and science: Evidence from PISA 2018 Philippine data,” Int. J. Sch. Educ. Psychol., vol. 9, no. 2, pp. 208–222, Apr. 2021, doi: 10.1080/21683603.2020.1832635.
[30] N. B. Ortiz Alvarado, M. Rodríguez Ontiveros, and E. A. Ayala Gaytán, “Do Mindsets Shape Students’ Well-Being and Performance?,” J. Psychol., vol. 153, no. 8, pp. 843–859, Nov. 2019, doi: 10.1080/00223980.2019.1631141.
[31] C. Hoetmer, “Het Gebruik van Groeimindset en Competitie om Motivatie te Ondersteunen en de”.
Published
2025-01-08
How to Cite
[1]
V. L. A. Chavez, “Exploring Latent Class Profiles of Mathematics Performance: Insights from PISA 2022 Using Growth Mindset Indicators and Group Comparison Analysis”, Jor. Eva. Edu, vol. 6, no. 1, Jan. 2025.
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