The Limits of Cognitive Preferences: How Gender and Conceptual Understanding Shape Mathematical Representations

Nur Fauziyah(1,Mail), Septiana Maulidinah(2), Hasan Basri(3), Wannaporn Siripala(4) | CountryCountry:


(1) Department of Teacher Professional Education, Universitas Muhammadiyah Gresik, Indonesia
(2) Department of Teacher Professional Education, Universitas Muhammadiyah Gresik, Indonesia
(3) Department of Mathematics Education, Universitas Madura, Indonesia
(4) Institute of Science Innovation and Culture, RMUTK, Thailand

MailCorresponding Author

Metrics Analysis (Dimensions & PlumX)

Indexing:
Similarity:

© 2026 Nur Fauziyah, Septiana Maulidinah, Hasan Basri, Wannaporn Siripala

This study aims to describe the profile of students' mathematical representations across visual, symbolic, and verbal aspects, and to examine visualist and verbalist cognitive styles from a gender perspective. A descriptive qualitative approach was used. Four students were purposively selected, consisting of male and female students with visualist and verbalist cognitive styles from a public high school. The instrument used was the Object-Spatial and Verbal Imagery Questionnaire (OSIVQ) to classify students into visualist and verbalist cognitive styles. Representation data were collected through a mathematical representation test focusing on function composition, and were supplemented by semi-structured interviews. Data analysis was carried out through data reduction, data presentation, and conclusion drawing. The results showed that visual representations by male and female visualist and verbalist students in solving mathematical problems were presented as images. In problems without image instructions, both male and female visualist students continued to use visual representations before switching to symbolic representations. There was no variation in the visual representations used by the subjects; the images used tended to be copied from their teachers. Male students, both visualists and verbalists, used symbolic representations less systematically than female students. In symbolic representation, visual students made errors at the algebraic operations stage, resulting in symbol errors, and vice versa. All subjects used verbal representation, but to a very small extent. Verbal representation was not used to explain the steps for completing the worksheet; it was only used to write the names of the concepts. Visual students, both male and female, tended to point to pictures when explaining the work process, whereas verbal students tended to point to symbols. Female visual and verbal students were more systematic in their explanations, while male visual and verbal students were less coherent.

 

Keywords: mathematical representation, cognitive style, gender.

Keywords: Mathematical representation; cognitive style; gender

Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198. https://doi.org/10.1016/j.learninstruc.2006.03.001

Arcavi, A. (2003). The role of visual representations in the learning of mathematics. Educational Studies in Mathematics, 52 (3), 215–241. https://doi.org/10.1023/A:1024312321077

Bicer, A. (2021). Multiple representations and mathematical creativity. Thinking Skills and Creativity, 42, 100960. https://doi.org/10.1016/j.tsc.2021.100960

Birgin, O., & Eryılmaz, E. (2025). Investigation of seventh-grade students’ performance in translating among multiple representations of fractions. Thinking Skills and Creativity, 57, 101809. https://doi.org/10.1016/j.tsc.2025.101809

Björklund, C., & Palmér, H. (2022). Teaching toddlers the meaning of numbers—connecting modes of mathematical representations in book reading. Educational Studies in Mathematics, 110(3), 525–544. https://doi.org/10.1007/s10649-022-10147-3

Blazhenkova, O., & Kozhevnikov, M. (2009). The new object-spatial-verbal cognitive style model: Theory and measurement. Applied Cognitive Psychology, 23(5), 638-663. https://doi.org/10.1002/acp.1473

Çakmak Gürel, Z. (2023). Teaching mathematical modeling in the classroom: Analyzing the scaffolding methods of teachers. Teaching and Teacher Education, 132, 104253. https://doi.org/10.1016/j.tate.2023.104253

Castellanos, J. L. V., Castro, E., & Gutiérrez, J. (2009). Representations in problem solving: A case study with optimization problems. Electronic Journal of Research in Educational Psychology, 7(17), 279-308

Castro, E., Cañadas, M. C., Molina, M., & Rodríguez-Domingo, S. (2022). Difficulties in semantically congruent translation of verbally and symbolically represented algebraic statements. Educational Studies in Mathematics, 109(3), 593–609. https://doi.org/10.1007/s10649-021-10088-3

Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning: A systematic and critical review. London: Learning and Skills Research Centre.

Duval, R. (2006). A cognitive analysis of problems of comprehension in a learning of mathematics. Educational Studies in Mathematics, 61, 103–131. https://doi.org/10.1007/s10649-006-0400-z

Else-Quest, N. M., Hyde, J. S., & Linn, M. C. (2010). Cross-national patterns of gender differences in mathematics: A meta-analysis. Psychological Bulletin, 136(1), 103–127. https://doi.org/10.1037/a0018053

Fauziyah, N., & Hakim, L. El. (2025). Analysis of students’ mathematics conceptual understanding based on differences in mathematics thinking styles. Jurnal Pendidikan MIPA, 26(2), 941–970. https://doi.org/10.23960/jpmipa.v26i2.pp941-970

Gallagher, A. M., De Lisi, R., Holst, P. C., McGillicuddy-De Lisi, A. V., Morely, M., & Cahalan, C. (2000). Gender differences in advanced mathematical problem solving. Journal of Experimental Child Psychology, 75(3), 165–190. https://doi.org/10.1006/jecp.1999.2532

Ganley, C. M., & Vasilyeva, M. (2014). The role of anxiety and working memory in gender differences in mathematics. Journal of Educational Psychology, 106(1), 105–120. https://doi.org/10.1037/a0034099

Goldin, G. A. (2002). Representation in mathematical learning and problem solving. Journal of Mathematical Behavior, 17(2), 137–165.

Hasan, B. (2019). The analysis of students’ critical thinking ability with visualizer-verbalizer cognitive style in mathematics. International Journal of Trends in Mathematics Education Research, 2(3), 142–148. https://doi.org/10.33122/ijtmer.v2i3.97

Koć-Januchta, M., Höffler, T., Thoma, G. B., Prechtl, H., & Leutner, D. (2017). Visualizers versus verbalizers: Effects of cognitive style on learning with texts and pictures – An eye-tracking study. Computers in Human Behavior, 68, 170–179. https://doi.org/10.1016/j.chb.2016.11.028

Kowiyah, K., Mulyawati, I., & Umam, K. (2019). Conceptual understanding and mathematical representation analysis of realistic mathematics education based on personality types. Al-Jabar : Jurnal Pendidikan Matematika, 10(2), 201–210. https://doi.org/10.24042/ajpm.v10i2.4605

Kozhevnikov, M., Hegarty, M., & Mayer, R. E. (2002). Revising the visualizer-verbalizer dimension: Evidence for two types of visualizers. Cognition and Instruction, 20(1), 44–47. https://doi.org/10.1207/S1532690XCI2001_3

Kozhevnikov, M., Kosslyn, S., & Shephard, J. (2005). Spatial versus object visualizers: A new characterization of visual cognitive style. Memory and Cognition, 33(4), 710–726. https://doi.org/10.3758/BF03195337

Lesh, R., Post, T., & Behr, M. (1987). Representations and translations among representations in mathematics learning and problem solving. Hillsdale: Lawrence Erlbaum.

Lundvin, M., & Palmér, H. (2025). A Play-responsive approach to teaching mathematics in preschool, with a focus on representations. Education Sciences, 15(8), 999. https://doi.org/10.3390/educsci15080999

Martins, R., Viseu, F., & Rocha, H. (2023). Functional thinking: A study with 10th-grade students. Education Sciences, 13(4), 1–22. https://doi.org/10.3390/educsci13040335

Mayer, R. E. (2021). Evidence-based principles for how to design effective instructional videos. Journal of Applied Research in Memory and Cognition, 10(2), 229–240. https://doi.org/10.1016/j.jarmac.2021.03.007

Miles, M. B., Huberman, A. M., & Saldaña, J. (2016). Qualitative data analysis: A methods sourcebook (3rd ed.). SAGE Publications, Inc.

Moschkovich, J. N. (2015). Academic literacy in mathematics for english learners. Journal of Mathematical Behavior, 40, 43–62. https://doi.org/10.1016/j.jmathb.2015.01.005

Munawwir, Z., Susanto, S., & Suwito, A. (2025). Mental image and its impact on types of errors in mathematical problem solving: A case study. ETDC: Indonesian Journal of Research and Educational Review, 5(1), 513–524. https://doi.org/10.51574/ijrer.v5i1.4269

Nasrun, Prahmana, R. C. I., & Akib, I. (2023). The students’ representative processes in solving mathematical word problems. Knowledge, 3(1), 70-79. https://doi.org/10.3390/knowledge3010006

National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Reston, VA: Author.

Nugroho, M., & Suseno, I. G. (2025). Gender and language: Analyzing communication styles in argumentative writing. Journal of Communication & Public Relations, 4(1), 102–117. https://doi.org/10.37535/105004120256

Nurhajarurahmah, S. Z., & Arsyad, N. (2023). Mathematical reasoning and communication levels ability based on gender differences. Daya Matematis: Jurnal Inovasi Pendidikan Matematika, 11(3), 165. https://doi.org/10.26858/jdm.v11i3.53789

Nurrahmawati, Sa’dijah, C., Sudirman, & Muksar, M. (2021). Assessing students’ errors in mathematical translation: From symbolic to verbal and graphic representations. International Journal of Evaluation and Research in Education, 10(1), 115–125. https://doi.org/10.11591/ijere.v10i1.20819

Ozturk, A. (2025). Teacher moves for building a mathematical modeling classroom community. Education Sciences, 15(3), 173–183. https://doi.org/10.3390/educsci15030376

Pitta-Pantazi, D., & Christou, C. (2010). Spatial versus object visualisation: The case of mathematical understanding in three-dimensional arrays of cubes and nets. International Journal of Educational Research, 49(2–3), 102–114. https://doi.org/10.1016/j.ijer.2010.10.001

Post, M., & Prediger, S. (2024). Teaching practices for unfolding information and connecting multiple representations: the case of conditional probability information. Mathematics Education Research Journal, 36(1), 97–129. https://doi.org/10.1007/s13394-022-00431-z

Ramírez-Uclés, I. M., & Ramírez-Uclés, R. (2020). Gender differences in visuospatial abilities and complex mathematical problem solving. Frontiers in Psychology, 11, 191. https://doi.org/10.3389/fpsyg.2020.00191

Rau, M. A., & Matthews, P. G. (2017). How to make ‘more’ better? Principles for effective use of multiple representations to enhance students’ learning about fractions. ZDM - Mathematics Education, 49(4), 531–544. https://doi.org/10.1007/s11858-017-0846-8

Riding, R.& Rainer, S. (2014). Cognitive style & learning strategies: understanding style differences in learning and behaviour. David Fulton Publishers.

Rif’at, M., Sudiansyah, S., & Imama, K. (2024). Role of visual abilities in mathematics learning: An analysis of conceptual representation. Al-Jabar : Jurnal Pendidikan Matematika, 15(1), 87–97. https://doi.org/10.24042/ajpm.v15i1.22406

Schleppegrell, M. J. (2007). The linguistic challenges of mathematics teaching and learning: A research review. Reading and Writing Quarterly, 23(2), 139–159. https://doi.org/10.1080/10573560601158461

Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple representation. Learning and Instruction, 13(2), 141–156. https://doi.org/10.1016/S0959-4752(02)00017-8

Schoenherr, J., & Schukajlow, S. (2024). Characterizing external visualization in mathematics education research: a scoping review. ZDM - Mathematics Education, 56(1), 183–198. https://doi.org/10.1007/s11858-023-01494-3

Setyawan, F., Zuliana, E., & Ali, R. M. (2020). Conceptual understanding of visualizer and verbalizer using multiple representation. International Journal on Emerging Mathematics Education, 4(2), 53–62. https://doi.org/10.12928/ijeme.v4i2.17767

Stylianou, D. A. (2010). Teachers’ conceptions of representation in middle school mathematics. Journal of Mathematics Teacher Education, 13(4), 325-343. https://doi.org/10.1007/s10857-010-9143-y

Wang, R., Zulkifli, N. N., & Mohd Ayub, A. F. (2024). Investigating the impact of the stratified cognitive apprenticeship model on high school students’ math performance. Education Sciences, 14(8), 898. https://doi.org/10.3390/educsci14080898

Wei, W., Chen, C., & Zhou, X. (2016). Spatial ability explains the male advantage in approximate arithmetic. Spatial ability explains the male advantage in approximate arithmetic. Frontiers in Psychology, 7, 306. https://doi.org/10.3389/fpsyg.2016.00306

Weingarden, M., Karsenty, R., & Koichu, B. (2026). Realistic visual representations as mediators between everyday and mathematical discourses in heterogeneous classrooms. Journal of Mathematical Behavior, 81, 101300. https://doi.org/10.1016/j.jmathb.2025.101300

Weliweriya, N., Huynh, T., & Sayre, E. C. (2018). Standing fast: Translation among durable representations using evanescent representations in upper-division problem solving. 2017 Physics Education Research Conference Proceedings. https://doi.org/10.1119/perc.2017.pr.103

Instrumen test, turnitin, Cek AI
Kisi-kisi Instrument Tes Representasi Matematika
Angket Gaya Kognitif

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.