Enhancing Students Performance on Graphing of Polynomial Functions Through Flowchart-Based Instruction

Authors

  • Kimberly Joy M. Geron Balungao National High School, Department of Education; University of Luzon Graduate School, Philippines Author
  • Ana Perla B. De Guzman Bantugan Elementary School, Pozorrubio, Pangasinan, Philippines Author

DOI:

https://doi.org/10.5281/zenodo.21877099

Keywords:

flowchart-based instruction, polynomial functions, mathematics education, visual scaffolding, Grade 10

Abstract

This study examined the effectiveness of flowchart-based instruction in improving Grade 10 students' performance in graphing polynomial functions, particularly in determining degree, identifying the sign of the leading coefficient, and describing graph end behavior. A pretest-posttest quasi-experimental design was used with two intact classes at Balungao National High School in Pangasinan, Philippines. The control group (n = 35) received conventional teacher-led instruction, whereas the experimental group (n = 35) was taught through a structured flowchart that guided learners through successive decision points. A content-validated 30-item multiple-choice test was administered before and after the one-week intervention. Pilot testing yielded Cronbach's alpha coefficients of .802 and .921 for the assessment forms. Means, standard deviations, independent-samples t tests, and paired-samples t tests were used to analyze the data. The groups had comparable pretest performance (M = 15.03 and 15.54, respectively), t = 0.490, p = .626. At posttest, the experimental group obtained a higher mean score (M = 22.54, SD = 4.10) than the control group (M = 18.77, SD = 4.05), t = 3.876, p < .001. Both groups improved significantly; however, the experimental group's mean gain (7.00) was nearly twice that of the control group (3.74). The findings indicate that flowchart-based instruction can serve as an effective visual scaffold for organizing multi-step algebraic reasoning. Its use is recommended for concepts that require systematic interpretation, while longer and multisite studies are needed to establish broader generalizability.

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References

Al-Rababaha, H., Yew, W. T., & Meng, C. C. (2020). Students’ misconceptions in interpreting polynomial graphs. International Journal of Academic Research in Progressive Education and Development, 9(2), 1–12.

Bruner, J. S. (1966). Toward a theory of instruction. Harvard University Press.

Cahapay, M. B., & Labrador, M. G. P. (2022). Instructional practices of Filipino teachers in remote mathematics education in COVID-19 times. International Journal of Didactical Studies, 3(1), Article 101458.

Chechan, A., Ampadu, E., & Pears, J. (2023). Effect of using Desmos on high school students’ understanding and learning of functions. Eurasia Journal of Mathematics, Science and Technology Education, 19(2), em2235.

Department of Education. (2016). K to 12 curriculum guides: Mathematics (Grade 1 to Grade 10). Republic of the Philippines.

Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). SAGE Publications.

Mayer, R. E. (2001). Multimedia learning. Cambridge University Press.

Nagashima, J., & Rittle-Johnson, B. (2021). Anticipatory diagrammatic self-explanation improves learning of algebraic procedures. Journal of Educational Psychology, 113(4), 678–693.

Nagashima, J., McNamara, A., & Rittle-Johnson, B. (2022). Enhancing conceptual knowledge in early algebra through diagrammatic self-explanation. Carnegie Mellon University & University of Wisconsin.

Organisation for Economic Co-operation and Development. (2023). PISA 2022 results: The state of learning and equity in education. OECD Publishing.

Paivio, A. (1986). Mental representations: A dual coding approach. Oxford University Press.

Skemp, R. R. (1976). Relational understanding and instrumental understanding. Mathematics Teaching, 77, 20–26.

Soso, G. D. (2020). The competency of Grade 7 students in solving polynomial problems. SMCC Higher Education Research Journal, 2(1).

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285.

Tall, D., & Vinner, S. (1981). Concept image and concept definition in mathematics learning. Educational Studies in Mathematics, 12(2), 151–169.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

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Published

2026-08-11

How to Cite

Geron, K. J., & De Guzman, A. P. (2026). Enhancing Students Performance on Graphing of Polynomial Functions Through Flowchart-Based Instruction. International Journal of Education, Research, and Innovation Perspectives, 2(8), 675-680. https://doi.org/10.5281/zenodo.21877099

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