The Impact of Intelligence (IQ) and Learning Styles on Mathematics Learning Motivation and Achievement in Secondary School Students
DOI:
https://doi.org/10.26740/jrpipm.v9n1.p101-117Keywords:
Academic Achievement, Intelligence Quotient, Learning Styles, Student Motivation, Mathematic EducationAbstract
This study aims to examine the influence of intelligence quotient (IQ) and learning styles on students’ learning motivation and mathematics achievement among tenth-grade high school students. The research employed a quantitative approach using an ex post facto design. A total of 83 students participated in the study, selected through a census sampling technique, as the entire population of tenth-grade students was included. Instruments used in this study included an IQ test, a learning style questionnaire (covering auditory, visual, and kinesthetic styles), a motivation questionnaire, and a mathematics achievement test. Data analysis involved instrument validity and reliability testing, classical assumption tests (normality and homogeneity), and multivariate analysis (MANOVA) to assess both the direct and interaction effects of IQ and learning styles on learning motivation and mathematics achievement. The results showed that IQ had a significant effect on mathematics achievement (p < 0.05), but no significant effect on learning motivation. Learning styles did not significantly influence either mathematics achievement or learning motivation. Furthermore, there was no significant interaction between IQ and learning styles in relation to either outcome. The coefficient of determination (R²) indicated that the model explained 26.3% of the variance in mathematics achievement and 16.5% of the variance in learning motivation. It can be concluded that IQ contributes to students’ success in mathematics, while learning motivation and performance are also shaped by other factors beyond IQ and learning styles. These findings highlight the importance of instructional strategies that consider students’ intellectual capacities along with affective and contextual factors
References
Andari, U., & Lestari, D. S. (2023). Pengembangan media pembelajaran matematika berbasis teknologi digital. JRSMe, 7(1), 45–58.
Arikunto, S. (2025). Prosedur penelitian: Suatu pendekatan praktik (Edisi Revisi terbaru). Rineka Cipta.
Azwar, S. (2015). Reliabilitas dan validitas (Edisi revisi). Pustaka Pelajar.
Chairuddin, C., Arisetyawan, A., & Ekawati, R. (2024). Uncovering mathematical literacy ability of eighth grade junior high school students based on VARK learning style. Jurnal Elemen, 10(1), 1–16. https://doi.org/10.29408/jel.v10i1.8120
Creswell, J. W., & Guetterman, T. C. (2024). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (7th ed.). Pearson
Cuevas, J. A. (2015). Is learning‑styles‑based instruction effective? A comprehensive analysis of recent research on learning styles. Theory and Research in Education, 13(3), 308–333
Fatih A. Marzuqoh, A. A. Sujadi, & T. A. Arigiyati. (2023). Hubungan antara motivasi, keaktifan, gaya belajar dengan prestasi belajar matematika siswa SMA se‑Kecamatan Banguntapan. Union: Jurnal Ilmiah Pendidikan Matematika
Gottfredson, L. S. (2018). g theory: How recurring variation in human intelligence and the complexity of everyday tasks create social structure and the democratic dilemma. In R. J. Sternberg (Ed.), The Nature of Human Intelligence (pp. 130–151). Cambridge University Press.
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference (4th ed.). Allyn & Bacon.
Ghozali, I. (2016). Multivariate analysis with SPSS (7th ed.). Badan Penerbit Universitas Diponegoro.
Handarini, D. N., Sasmita, K., & Lestari, I. (2021). The influence of intellectual intelligence and learning motivation against students’ mathematics learning outcomes in Region 3 Kelurahan Pegadungan Jakarta Barat. Syntax Literate: Jurnal Ilmiah Indonesia, 6(12)
Hertanti, A., Aprisal, F., Fitriani, F., & Wustqa, D. U. (2024). Mathematical-logical intelligence, visual-spatial intelligence, and learning motivation: Which variables affect mathematics problem-solving ability? Jurnal Tadris Matematika (JTMT
Hidayat, D. D. & Mahmudi, A. (2024). Impact of Multiple Intelligences and Problem-Based Learning on Mathematical Literacy and Self‑Efficacy in Junior High School Students. AL-ISHLAH: Jurnal Pendidikan, 17(1), Article 5463. https://doi.org/10.35445/alishlah.v17i1.5463
Indra M. Rusmana & Dwi S. Wulandari. (2024). Pengaruh gaya belajar dan kecerdasan logika matematika terhadap prestasi belajar matematika. Jurnal Lebesgue, 1(2), Article 18
Mulyani. (2020). The relationship between intelligence level, achievement motivation, and mathematics study habits with students' mathematics learning achievement. Jurnal Inovasi Edukasi, 3(2), Article 764
Murayama, K., Pekrun, R., Lichtenfeld, S., & vom Hofe, R. (2012). Motivation, study habits—and not IQ—determine growth in math achievement. Child Development, 83(1), 167–179.
Murtafiah, M., Muniroh, S., & Widiati, U. (2024). Multiple intelligences on students’ learning outcomes: Differentiated learning context. Erudio Journal of Educational Innovation, 11(2), 187–194
Nur Muslimah, H. Haeruddin, & P. Fendiyanto. (2023). The influence of learning styles and learning motivation on mathematics learning outcomes of eighth-grade students at SMP Negeri 1 Kembang Janggut. PHI: Jurnal Pendidikan Matematika.
Pietschnig, J., Oberleiter, S., Toffalini, E., & Giofrè, D. (2023). Reliability of the g factor over time in Italian INVALSI data (2010–2022): What can achievement‑g tell us about the Flynn effect? arXiv
Pizon, M. G., & Ytoc, S. T. (2021). A path model to infer mathematics performance: The interrelated impact of motivation, attitude, learning style and teaching strategies variables. International Journal of Advanced Research in Multidisciplinary Field, 7(5), 24–32
Pritchard, A. M. (2017). Ways of learning: Learning theories and learning styles in the classroom (4th ed.). Routledge.
Rahmawati, I., & Putri, A. R. (2020). The influence of learning styles on elementary school students’ learning motivation. Jurnal Pendidikan Dasar, 11(1), 1–10.
Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2020). Providing instruction based on students’ learning style preferences does not improve learning. Frontiers in Psychology, 11, 164
Santoso, D. (2018). The influence of intellectual intelligence on students’ mathematics learning achievement. Jurnal Pendidikan Matematika Indonesia, 3(2), 87–94.
Santrock, J. W. (2023). Educational psychology (8th ed.). McGraw-Hill Education
Sengodan, V., & Iksan, Z. H. (2016). Students’ learning styles and intrinsic motivation in learning mathematics. Asian Journal of Education and e-Learning, 4(1), 1–7
Siddiq, S. (2023). Effect of Multiple Intelligences on Achievement in Mathematics: A Meta‑Analysis. International Journal of Research in Academic World, 2(6), 36–43
Sikhah, F. (2017). The relationship between the level of intelligence, achievement motivation, mathematics learning habits and learning achievement. Unnes Journal of Mathematics Education, 6(1), 108–1131
Sternberg, R. J. (2020). Cambridge Handbook of Intelligence (2nd ed.). Cambridge University Press
Sugiyono. (2017). Metode penelitian pendidikan: Pendekatan kuantitatif, kualitatif, dan R&D. Alfabeta.
Wechsler, D. (2024). Wechsler Adult Intelligence Scale – Fifth Edition (WAIS‑5). Pearson
Woolfolk, A., & Usher, E. (2022). Educational Psychology (15th ed.). Pearson
Published
How to Cite
Issue
Section
Abstract views: 0
