Elaboration–Fluency Cognitive Activation Theory of Creative Thinking in Mathematics Performance: Evidence from Structural Equation Modeling

Authors

DOI:

https://doi.org/10.11594/

Keywords:

Creative thinking, Elaboration, Fluency, Mathematics performance, Mediation, Structural equation modeling

Abstract

ive thinking is widely recognized as essential for mathematics learning; however, the structural mechanisms linking its domains to mathematics performance remain insufficiently understood. This theory-building study investigated the relationship between the domains of creative thinking and mathematics performance among junior high school learners. Using a quantitative, non-experimental design, data were collected from 300 Grade 9 learners in the Tugbok District, Division of Davao City, Philippines. Creative thinking was operationalized using a researcher-developed 16-item instrument that assessed four domains: fluency, flexibility, originality, and elaboration. The instrument is an open-ended questionnaire requiring respondents to generate varied responses, which were evaluated using teacher-scored rubrics. Fluency was measured by relevant ideas produced to solved the problems; flexibility by the diverse of solution of strategies used; originality by the uniqueness with valid reasoning of responses; and elaboration by the level of explanation, clarity of ideas, and completeness of mathematical steps used. Mathematics performance was obtained from official academic records. Structural Equation Modeling (SEM) was fit to utilize for testing multiple hypothesized models and identify which among the models is the best-fitting structural representation of these relationships. Results showed that elaboration do not significantly predict mathematics performance but indirectly significant when both the elaboration and mathematics performance is linked with fluency. 

Downloads

Download data is not yet available.

References

Ay, S., Edulsa Jr., V. A., & Istikomah, S. (2016). Conceptual understanding and academic performance of learners in mathematics. Psychology and Education, 5(1), 736–745.

Browne, M. W., & Cudeck, R. (1993). Alterna-tive ways of assessing model fit. In Test-ing structural equation models (pp. 136–162). Sage

Chomeya, R., Tayraukham, S., & Tongkham-banchong, S. (2022). Sample size deter-mination techniques for structural equa-tion modeling: SEM. Journal of Educa-tional Measurement Mahasarakham Uni-versity, 28(2), 24–40.

Creswell, C., & Speelman, C. P. (2020). Does mathematics training lead to better logi-cal thinking and reasoning? A cross-sectional assessment from learners to professors. PLOS ONE, 15(7), e0236153. https://doi.org/10.1371/journal.pone.0236153

DeCaro, M. S. (2022). Inducing mental set con-strains procedural flexibility and concep-tual understanding in mathematics. Memory & Cognition, 44(7), 1138–1148. https://doi.org/10.3758/s13421-016-0614-y

Denis, D. J. (2021). Applied univariate, bivari-ate, and multivariate statistics: Under-standing statistics for social and natural scientists, with applications in SPSS and R. John Wiley & Sons.

Department of Education (DepEd). (2015). DepEd Order No. 8, s. 2015: Policy and guidelines on classroom assessment for K to 12 curriculum. https://www.deped.gov.ph/wp-con-tent/uploads/2015/04/DO_s2015_08.pdf

Department of Education. (2024). MATATAG curriculum framework: Strengthening the K to 10 curriculum. Department of Educa-tion, Philippines. https://www.deped.gov.ph/matatag-curriculum

Flores, G. M. (2019). Triarchic intelligences, engagement, and self-efficacy beliefs of grade 10 learners: A structural model on mathematics performance. [Unpublished doctoral dissertation, Bukidnon State University].

Guilford, J. P. (1950). Creativity. American Psy-chologist, 5(9), 444–454.

Handayani, S. A., Rahayu, Y. S., & Agustini, R. (2021). Learners' creative thinking skills in biology learning: Fluency, flexibility, originality, and elaboration. Journal of Physics: Conference Series, 1747(1), 012040. https://doi.org/10.1088/1742-6596/1747/1/012040

Hickendorff, M. (2022). Flexibility and adap-tivity in arithmetic strategy use: What children know and what they show. Jour-nal of Numerical Cognition, 8, 367–381. https://doi.org/10.5964/jnc.7277

Hu, L. T., & Bentler, P. M. (1999). Cutoff crite-ria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.

Hunter, J., Perger, P., & Darragh, L. (2018). Making waves, opening spaces. In Pro-ceedings of the 41st annual conference of the Mathematics Education Research Group of Australasia (pp. 202–209). Auckland: MERGA

Kellman, P. J., Massey, C. M., & Son, J. Y. (2020). Perceptual learning modules in mathematics: Enhancing learners' pattern recognition, structure extraction, and flu-ency. Topics in Cognitive Science, 2(2), 285–305. https://doi.org/10.1111/j.1756-8765.2009.01053.x

Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press.

Lin, S., & Tai, W. (2015). Latent class analysis of learners' mathematics learning strate-gies and the relationship between learn-ing strategy and mathematical literacy. Universal Journal of Educational Re-search, 3, 390–395. https://api.semanticscholar.org/CorpusID:14883063

Lince, R. (2016). Creative thinking ability to increase learner mathematics of junior high school by applying models num-bered heads together. Journal of Educa-tion and Practice, 7, 206–212. https://api.semanticscholar.org/CorpusID:59385426

Ling, A. N. B., & Mahmud, M. S. (2023). Chal-lenges of teachers when teaching sen-tence-based mathematics problem-solving skills. Frontiers in Psychology, 13, Article 1074202. https://doi.org/10.3389/fpsyg.2022.1074202

Magen-Nagar, N. (2016). The effects of learn-ing strategies on mathematical literacy: A comparison between lower and higher achieving countries. International Journal of Research in Education and Science, 2, 306–314. https://doi.org/10.21890/ijres.77083

Maharani, H., Sukestiyarno, S., & Waluya, B. (2017). Creative thinking process based on Wallas model in solving mathematics problem. International Journal on Emerg-ing Mathematics Education, 1(2), 177–184. https://doi.org/10.12928/ijeme.v1i2.5783

Mednick, S. A. (1962). The associative basis of the creative process. Psychological Re-view, 69(3), 220–232. https://doi.org/10.1037/h0048850

Mullis, I., Martin, M., Foy, P., Kelly, D., & Fishbein, B. (2019). TIMSS 2019 interna-tional results in mathematics and science. TIMSS & PIRLS International Study Cen-ter, Lynch School of Education and Hu-man Development, Boston College, and International Association for the Evalua-tion of Educational Achievement (IEA).

OECD. (2019). Programme for International Learner Assessment (PISA) results from PISA 2018. https://www.oecd.org/pisa/publications/PISA2018_CN_PHL.pdf

OECD. (2024). PISA 2022 results (Volume III): Creative minds, creative schools. OECD Publishing. https://doi.org/10.1787/765ee8c2-en

Philippine Statistics Authority. (2020). 2020 census of population and housing (CPH). https://psa.gov.ph/statistics/census/population-and-housing

Piaget, J. (1936). Origins of intelligence in the child. Routledge & Kegan Paul.

Santana, A., Roazzi, A., & Nobre, A. (2022). The relationship between cognitive flexibility and mathematical performance in chil-dren: A meta-analysis. Trends in Neuro-science and Education, 28, Article 100179. https://doi.org/10.1016/j.tine.2022.100179

Sari, T. H. N. I. S. (2019). The relationship be-tween creative thinking and mathemati-cal proving abilities among junior high school learners. IOP Conference Series: Earth and Environmental Science, 243(1), 012100. https://doi.org/10.1088/1755-1315/243/1/012100

Second Congressional Commission on Educa-tion. (2023). Fixing the foundations: A matter of national survival. Government of the Philippines.

Spencer, M., Fuchs, L. S., Geary, D. C., & Fuchs, D. (2022). Connections between mathe-matics and reading development: Numer-ical cognition mediates relations between foundational competencies and later aca-demic outcomes. Journal of Educational Psychology, 114(2), 273–288. https://doi.org/10.1037/edu0000670

Stocker, J. D., Jr., & Kubina, R. M., Jr. (2021). Building prealgebra fluency through a self-managed practice intervention: Or-der of operations. Behavior Analysis in Practice, 14(3), 608–622. https://doi.org/10.1007/s40617-020-00501-3

Ten Braak, D., Lenes, R., Purpura, D. J., Schmitt, S. A., & Størksen, I. (2022). Why do early mathematics skills predict later mathematics and reading achievement? The role of executive function. Journal of Experimental Child Psychology, 214, Arti-cle 105306. https://doi.org/10.1016/j.jecp.2021.105306

Van der Stel, M., & Veenman, M. V. J. (2014). Metacognitive skills and intellectual abil-ity of young adolescents: A longitudinal study from a developmental perspective. European Journal of Psychology of Educa-tion, 29(1), 117–137. https://doi.org/10.1007/s10212-013-0196-x

Walia, S., & Walia, S. (2017). Mathematical creativity: Its measurement and its rela-tion to intelligence, mathematical compe-tence and general creativity. Journal of Mathematical Behavior, 48, 1–15. https://doi.org/10.1016/j.jmathb.2017.03.001

Zohar, A., & Dori, Y. J. (2016). Higher-order thinking skills and low-achieving learn-ers: Are they mutually exclusive? The Journal of the Learning Sciences, 12(2), 145–181. https://doi.org/10.1080/10508406.2016.1154601

Downloads

Published

23-04-2026

Data Availability Statement

Yes, publicly available: If your dataset can be openly shared.

How to Cite

Borres, J. V., & Luzano, J. F. P. (2026). Elaboration–Fluency Cognitive Activation Theory of Creative Thinking in Mathematics Performance: Evidence from Structural Equation Modeling. International Journal of Multidisciplinary: Applied Business and Education Research, 7(4), 1645-1658. https://doi.org/10.11594/