Main Article Content
Abstract
Representation plays a central role in mathematical problem solving, serving as a cognitive bridge between abstract concepts and concrete understanding. However, while prior studies have examined the effects of scaffolding in mathematics learning, limited attention has been given to the comparative impact of single versus multiple online representations, particularly in relation to students’ cognitive processes such as eye movement behavior. This study addresses this gap by investigating the effectiveness of online single and multiple representation scaffolding in enhancing students’ mathematical concept mastery, problem-solving performance, and eye movement patterns during problem-solving tasks. A quasi-experimental design was employed involving 300 high school students, randomly assigned to either a multiple representation scaffolding group (n = 150) or a single representation scaffolding group (n = 150). Data were analyzed using one-way MANCOVA, ANCOVA, MANOVA, and ANOVA tests. The results revealed that students who received multiple representation scaffolding outperformed their peers in mastering mathematical concepts, solving complex problems—including advanced-level tasks—and demonstrating more efficient visual processing, indicated by shorter fixation durations and rereading times. Furthermore, these students exhibited more adaptive strategies across varying question types (basic, combination, and advanced). The findings highlight the pedagogical advantage of using multiple representation scaffolding in online mathematics instruction, suggesting that it offers more comprehensive cognitive support and promotes deeper conceptual understanding. This study contributes to the growing body of research on digital scaffolding by evidencing the cognitive and performance-related benefits of multimodal representation and underscores its potential to inform the design of technology-enhanced mathematics learning environments.
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References
- 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
- Avcı, C., & Deniz, M. N. (2022). Computational thinking: early childhood teachers’ and prospective teachers’ preconceptions and self-efficacy. Education and Information Technologies, 27(8), 11689–11713. https://doi.org/10.1007/s10639-022-11078-5
- Bliss, K. M., Galluzzo, B. J., Kavanagh, K. R., & Skufa, J. D. (2019). Incorporating mathematical modeling into the undergraduate curriculum: What the GAIMME report offers faculty. Primus, 29(10), 1101–1118. https://doi.org/10.1080/10511970.2018.1488787
- Borchers, C., Fleischer, H., Yaron, D. J., McLaren, B. M., Scheiter, K., Aleven, V., & Schanze, S. (2025). Problem-solving strategies in stoichiometry across two intelligent tutoring systems: A cross-national study. Journal of Science Education and Technology, 34(2), 384-400. https://doi.org/10.1007/s10956-024-10197-7
- Brandsæter, A., & Berge, R. L. (2025). Promoting mathematical competence development through programming activities. Educational Studies in Mathematics, 119(2), 225-247. https://doi.org/10.1007/s10649-024-10380-y
- Calor, S. M., Dekker, R., van Drie, J. P., & Volman, M. L. L. (2022). Scaffolding small groups at the group level: Improving the scaffolding behavior of mathematics teachers during mathematical discussions. Journal of the Learning Sciences, 31(3), 369–407. https://doi.org/10.1080/10508406.2021.2024834
- Capone, R. (2022). Blended learning and student-centered active learning environment: A case study with STEM undergraduate students. Canadian Journal of Science, Mathematics and Technology Education, 22(1), 210–236. https://doi.org/10.1007/s42330-022-00195-5
- Capone, R., Adesso, M. G., Del Regno, F., Lombardi, L., & Tortoriello, F. S. (2021). Mathematical competencies: A case study on semiotic systems and argumentation in an Italian high school. International Journal of Mathematical Education in Science and Technology, 52(6), 896–911. https://doi.org/10.1080/0020739X.2020.1726517
- Chinofunga, M. D., Chigeza, P., & Taylor, S. (2025). How can procedural flowcharts support the development of mathematics problem-solving skills?. Mathematics Education Research Journal, 37(1), 85-123. https://doi.org/10.1007/s13394-024-00483-3
- Doruk, M., & Doruk, G. (2022). Students’ ability to determine the truth value of mathematical propositions in the context of operation meanings. International Journal of Mathematical Education in Science and Technology, 53(4), 753–786. https://doi.org/10.1080/0020739X.2020.1782494
- Faulkner, F., Breen, C., Prendergast, M., & Carr, M. (2023). Profiling mathematical procedural and problem-solving skills of undergraduate students following a new mathematics curriculum. International Journal of Mathematical Education in Science and Technology, 54(2), 220–249. https://doi.org/10.1080/0020739X.2021.1953625
- Fitzsimons, A., & Ní Fhloinn, E. (2023). The cops model for collaborative problem-solving in mathematics. Irish Educational Studies, 43(4), 1043-1060. https://doi.org/10.1080/03323315.2023.2189137
- Geraniou, E., Jankvist, U. T., Elicer, R., Tamborg, A. L., & Misfeldt, M. (2024). Towards a definition of “mathematical digital competency for teaching. ZDM - Mathematics Education, 56(4), 625–637. https://doi.org/10.1007/s11858-024-01585-9
- Haataja, E. S., Koskinen-Salmia, A., Salonen, V., Toivanen, M., & Hannula, M. S. (2025). Student visual attention during group instruction phases in collaborative geometry problem solving. Educational Studies in Mathematics, 118(3), 387-407. https://doi.org/10.1007/s10649-024-10337-1
- Herold-Blasius, R. (2024). The role of strategy keys in enhancing heuristics and self-regulation in mathematical problem-solving: A qualitative, explorative, and type-building study with primary school students. Investigations in Mathematics Learning, 1-20. https://doi.org/10.1080/19477503.2024.2430135
- Hidajat, F. A. (2024). Augmented reality applications for mathematical creativity: A systematic review. Journal of Computers in Education, 11(4), 991-1040. https://doi.org/10.1007/s40692-023-00287-7
- Hinton, V. M., & Flores, M. M. (2019). The effects of the concrete-representational-abstract sequence for students at risk for mathematics failure. Journal of Behavioral Education, 28(4), 493–516. https://doi.org/10.1007/s10864-018-09316-3
- Huang, X., Lo, C. K., He, J., Xu, S., & Kinshuk. (2024). Scaffolding-informed design of open educational resources in Chinese secondary school mathematics: Insights from multi-cycle formative evaluation. Smart Learning Environments, 11(1), 49. https://doi.org/10.1186/s40561-024-00337-2
- Iwuanyanwu, P. N., & Ogunniyi, M. B. (2020). Effects of dialogical argumentation instructional model on pre-service teachers’ ability to solve conceptual mathematical problems in physics. African Journal of Research in Mathematics, Science and Technology Education, 24(1), 129–141. https://doi.org/10.1080/18117295.2020.1748325
- Kohen, Z. (2019). Informed integration of IWB technology, incorporated with exposure to varied mathematics problem-solving skills: Its effect on students’ real-time emotions. International Journal of Mathematical Education in Science and Technology, 50(8), 1128–1151. https://doi.org/10.1080/0020739X.2018.1562119
- Kohen, Z. (2025). Structured mathematical modelling in an authentic scientific-engineering context. ZDM–Mathematics Education, 1-16. https://doi.org/10.1007/s11858-025-01654-7
- Leitner, A., & Gabel, M. (2024). Students' self-work during lectures in calculus courses–cognitive and affective effects of a small intervention. International Journal of Research in Undergraduate Mathematics Education, 1-23. https://doi.org/10.1007/s40753-024-00249-z
- Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. https://doi.org/10.1207/S15326985EP3801_6
- Martinez, B. L., Sweeder, R. D., VandenPlas, J. R., & Herrington, D. G. (2021). Improving conceptual understanding of gas behavior through the use of screencasts and simulations. International Journal of STEM Education, 8(1), 5. https://doi.org/10.1186/s40594-020-00261-0
- Nückles, M. (2021). Investigating visual perception in teaching and learning with advanced eye-tracking methodologies: Rewards and challenges of an innovative research paradigm. Educational Psychology Review, 33(1), 149–167. https://doi.org/10.1007/s10648-020-09567-5
- Paivio, A. (1986). Mental representations. Oxford University Press. https://doi.org/10.1037/0033-2909.124.3.372
- Partanen, P., Jansson, B., & Sundin, Ö. (2020). Fluid reasoning, working memory and planning ability in assessment of risk for mathematical difficulties. Educational Psychology in Practice, 36(3), 229–240. https://doi.org/10.1080/02667363.2020.1736518
- Pereda Loriente, Á., González-Calero, J. A., Tirado-Olivares, S., & del Olmo-Muñoz, J. (2025). Enhancing mathematics performance in primary education: The impact of personalized learning on fractions and decimal numbers. Education and Information Technologies, 1-31. https://doi.org/10.1007/s10639-025-13428-5
- Peretz, R., Tal, M., Akiri, E., Dori, D., & Dori, Y. J. (2023). Fostering engineering and science students’ and teachers’ systems thinking and conceptual modeling skills. Instructional Science, 51(3), 509-543. https://doi.org/10.1007/s11251-023-09625-9
- Rezat, S., Malik, S., & Leifeld, M. (2022). Scaffolding close reading of mathematical text in pre-service primary teacher education at the tertiary level: Design and evaluation. International Journal of Science and Mathematics Education, 20, 215–236. https://doi.org/10.1007/s10763-022-10309-y
- Rodríguez-Nieto, C. A., Font Moll, V., Borji, V., & Rodríguez-Vásquez, F. M. (2022). Mathematical connections from a networking of theories between extended theory of mathematical connections and onto-semiotic approach. International Journal of Mathematical Education in Science and Technology, 53(9), 2364–2390. https://doi.org/10.1080/0020739X.2021.1875071
- Rohde Poole, S. B. (2022). Designing and teaching an undergraduate mathematical modeling course for mathematics majors and minors. Primus, 32(7), 764–784. https://doi.org/10.1080/10511970.2021.1931995
- Sidenvall, J., Granberg, C., Lithner, J., & Palmberg, B. (2022). Supporting teachers in supporting students’ mathematical problem solving. International Journal of Mathematical Education in Science and Technology, 55(10), 2389-2409. https://doi.org/10.1080/0020739X.2022.2151067
- Siller, H. S., Nitzan-Tamar, O., & Kohen, Z. (2023). Scaffolding practices for modelling instruction in STEM-related contexts: Insights from expert and novice teachers. ZDM - Mathematics Education, 55(7), 1351–1364. https://doi.org/10.1007/s11858-023-01529-9
- Smit, R., Dober, H., Hess, K., Bachmann, P., & Birri, T. (2023). Supporting primary students’ mathematical reasoning practice: The effects of formative feedback and the mediating role of self-efficacy. Research in Mathematics Education, 25(3), 277–300. https://doi.org/10.1080/14794802.2022.2062780
- Smith, J. M., & Mancy, R. (2018). Exploring the relationship between metacognitive and collaborative talk during group mathematical problem-solving–what do we mean by collaborative metacognition? Research in Mathematics Education, 20(1), 14–36. https://doi.org/10.1080/14794802.2017.1410215
- Sui, C. J., Yen, M. H., & Chang, C. Y. (2024). Teachers’ perceptions of teaching science with technology-enhanced self-regulated learning strategies through the DECODE model. Education and Information Technologies, 29(17), 22813-22839. https://doi.org/10.1007/s10639-024-12715-x
- Suwarto, S., Hidayah, I., Rochmad, R., & Masrukan, M. (2023). Intuitive thinking: Perspectives on intuitive thinking processes in mathematical problem solving through a literature review. Cogent Education, 10(2), 2243119. https://doi.org/10.1080/2331186X.2023.2243119
- Tesfaw, B. K., Ayele, M. A., & Wondimuneh, T. E. (2024). Context-based problem-posing and solving instructional approach and students’ engagement in learning data handling. Cogent Education, 11(1), 2389486. https://doi.org/10.1080/2331186X.2024.2389486
- Tinungki, G. M., Hartono, P. G., Nurwahyu, B., Islamiyati, A., Robiyanto, R., Hartono, A. B., & Raya, M. Y. (2024). Exploring the team-assisted individualization cooperative learning to enhance mathematical problem solving, communication and self-proficiency in teaching non-parametric statistics. Cogent Education, 11(1), 2381333. https://doi.org/10.1080/2331186X.2024.2381333
- Toikka, S., Eronen, L., Atjonen, P., & Havu-Nuutinen, S. (2024). Combined conceptualisations of metacognitive knowledge to understand students’ mathematical problem-solving. Cogent Education, 11(1), 2357901. https://doi.org/10.1080/2331186X.2024.2357901
- Vogel, F., Kollar, I., Fischer, F., Reiss, K., & Ufer, S. (2022). Adaptable scaffolding of mathematical argumentation skills: The role of self-regulation when scaffolded with CSCL scripts and heuristic worked examples. International Journal of Computer-Supported Collaborative Learning, 17(1), 39–64. https://doi.org/10.1007/s11412-022-09363-z
- Vygotsky, L. S. (1978). Mind in society: Development of higher psychological processes. Harvard university press.
- Zhang, L., Stylianides, G. J., & Stylianides, A. J. (2024). Enhancing mathematical problem posing competence: A meta-analysis of intervention studies. International Journal of STEM Education, 11(1), 1–24. https://doi.org/10.1186/s40594-024-00507-1
References
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
Avcı, C., & Deniz, M. N. (2022). Computational thinking: early childhood teachers’ and prospective teachers’ preconceptions and self-efficacy. Education and Information Technologies, 27(8), 11689–11713. https://doi.org/10.1007/s10639-022-11078-5
Bliss, K. M., Galluzzo, B. J., Kavanagh, K. R., & Skufa, J. D. (2019). Incorporating mathematical modeling into the undergraduate curriculum: What the GAIMME report offers faculty. Primus, 29(10), 1101–1118. https://doi.org/10.1080/10511970.2018.1488787
Borchers, C., Fleischer, H., Yaron, D. J., McLaren, B. M., Scheiter, K., Aleven, V., & Schanze, S. (2025). Problem-solving strategies in stoichiometry across two intelligent tutoring systems: A cross-national study. Journal of Science Education and Technology, 34(2), 384-400. https://doi.org/10.1007/s10956-024-10197-7
Brandsæter, A., & Berge, R. L. (2025). Promoting mathematical competence development through programming activities. Educational Studies in Mathematics, 119(2), 225-247. https://doi.org/10.1007/s10649-024-10380-y
Calor, S. M., Dekker, R., van Drie, J. P., & Volman, M. L. L. (2022). Scaffolding small groups at the group level: Improving the scaffolding behavior of mathematics teachers during mathematical discussions. Journal of the Learning Sciences, 31(3), 369–407. https://doi.org/10.1080/10508406.2021.2024834
Capone, R. (2022). Blended learning and student-centered active learning environment: A case study with STEM undergraduate students. Canadian Journal of Science, Mathematics and Technology Education, 22(1), 210–236. https://doi.org/10.1007/s42330-022-00195-5
Capone, R., Adesso, M. G., Del Regno, F., Lombardi, L., & Tortoriello, F. S. (2021). Mathematical competencies: A case study on semiotic systems and argumentation in an Italian high school. International Journal of Mathematical Education in Science and Technology, 52(6), 896–911. https://doi.org/10.1080/0020739X.2020.1726517
Chinofunga, M. D., Chigeza, P., & Taylor, S. (2025). How can procedural flowcharts support the development of mathematics problem-solving skills?. Mathematics Education Research Journal, 37(1), 85-123. https://doi.org/10.1007/s13394-024-00483-3
Doruk, M., & Doruk, G. (2022). Students’ ability to determine the truth value of mathematical propositions in the context of operation meanings. International Journal of Mathematical Education in Science and Technology, 53(4), 753–786. https://doi.org/10.1080/0020739X.2020.1782494
Faulkner, F., Breen, C., Prendergast, M., & Carr, M. (2023). Profiling mathematical procedural and problem-solving skills of undergraduate students following a new mathematics curriculum. International Journal of Mathematical Education in Science and Technology, 54(2), 220–249. https://doi.org/10.1080/0020739X.2021.1953625
Fitzsimons, A., & Ní Fhloinn, E. (2023). The cops model for collaborative problem-solving in mathematics. Irish Educational Studies, 43(4), 1043-1060. https://doi.org/10.1080/03323315.2023.2189137
Geraniou, E., Jankvist, U. T., Elicer, R., Tamborg, A. L., & Misfeldt, M. (2024). Towards a definition of “mathematical digital competency for teaching. ZDM - Mathematics Education, 56(4), 625–637. https://doi.org/10.1007/s11858-024-01585-9
Haataja, E. S., Koskinen-Salmia, A., Salonen, V., Toivanen, M., & Hannula, M. S. (2025). Student visual attention during group instruction phases in collaborative geometry problem solving. Educational Studies in Mathematics, 118(3), 387-407. https://doi.org/10.1007/s10649-024-10337-1
Herold-Blasius, R. (2024). The role of strategy keys in enhancing heuristics and self-regulation in mathematical problem-solving: A qualitative, explorative, and type-building study with primary school students. Investigations in Mathematics Learning, 1-20. https://doi.org/10.1080/19477503.2024.2430135
Hidajat, F. A. (2024). Augmented reality applications for mathematical creativity: A systematic review. Journal of Computers in Education, 11(4), 991-1040. https://doi.org/10.1007/s40692-023-00287-7
Hinton, V. M., & Flores, M. M. (2019). The effects of the concrete-representational-abstract sequence for students at risk for mathematics failure. Journal of Behavioral Education, 28(4), 493–516. https://doi.org/10.1007/s10864-018-09316-3
Huang, X., Lo, C. K., He, J., Xu, S., & Kinshuk. (2024). Scaffolding-informed design of open educational resources in Chinese secondary school mathematics: Insights from multi-cycle formative evaluation. Smart Learning Environments, 11(1), 49. https://doi.org/10.1186/s40561-024-00337-2
Iwuanyanwu, P. N., & Ogunniyi, M. B. (2020). Effects of dialogical argumentation instructional model on pre-service teachers’ ability to solve conceptual mathematical problems in physics. African Journal of Research in Mathematics, Science and Technology Education, 24(1), 129–141. https://doi.org/10.1080/18117295.2020.1748325
Kohen, Z. (2019). Informed integration of IWB technology, incorporated with exposure to varied mathematics problem-solving skills: Its effect on students’ real-time emotions. International Journal of Mathematical Education in Science and Technology, 50(8), 1128–1151. https://doi.org/10.1080/0020739X.2018.1562119
Kohen, Z. (2025). Structured mathematical modelling in an authentic scientific-engineering context. ZDM–Mathematics Education, 1-16. https://doi.org/10.1007/s11858-025-01654-7
Leitner, A., & Gabel, M. (2024). Students' self-work during lectures in calculus courses–cognitive and affective effects of a small intervention. International Journal of Research in Undergraduate Mathematics Education, 1-23. https://doi.org/10.1007/s40753-024-00249-z
Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. https://doi.org/10.1207/S15326985EP3801_6
Martinez, B. L., Sweeder, R. D., VandenPlas, J. R., & Herrington, D. G. (2021). Improving conceptual understanding of gas behavior through the use of screencasts and simulations. International Journal of STEM Education, 8(1), 5. https://doi.org/10.1186/s40594-020-00261-0
Nückles, M. (2021). Investigating visual perception in teaching and learning with advanced eye-tracking methodologies: Rewards and challenges of an innovative research paradigm. Educational Psychology Review, 33(1), 149–167. https://doi.org/10.1007/s10648-020-09567-5
Paivio, A. (1986). Mental representations. Oxford University Press. https://doi.org/10.1037/0033-2909.124.3.372
Partanen, P., Jansson, B., & Sundin, Ö. (2020). Fluid reasoning, working memory and planning ability in assessment of risk for mathematical difficulties. Educational Psychology in Practice, 36(3), 229–240. https://doi.org/10.1080/02667363.2020.1736518
Pereda Loriente, Á., González-Calero, J. A., Tirado-Olivares, S., & del Olmo-Muñoz, J. (2025). Enhancing mathematics performance in primary education: The impact of personalized learning on fractions and decimal numbers. Education and Information Technologies, 1-31. https://doi.org/10.1007/s10639-025-13428-5
Peretz, R., Tal, M., Akiri, E., Dori, D., & Dori, Y. J. (2023). Fostering engineering and science students’ and teachers’ systems thinking and conceptual modeling skills. Instructional Science, 51(3), 509-543. https://doi.org/10.1007/s11251-023-09625-9
Rezat, S., Malik, S., & Leifeld, M. (2022). Scaffolding close reading of mathematical text in pre-service primary teacher education at the tertiary level: Design and evaluation. International Journal of Science and Mathematics Education, 20, 215–236. https://doi.org/10.1007/s10763-022-10309-y
Rodríguez-Nieto, C. A., Font Moll, V., Borji, V., & Rodríguez-Vásquez, F. M. (2022). Mathematical connections from a networking of theories between extended theory of mathematical connections and onto-semiotic approach. International Journal of Mathematical Education in Science and Technology, 53(9), 2364–2390. https://doi.org/10.1080/0020739X.2021.1875071
Rohde Poole, S. B. (2022). Designing and teaching an undergraduate mathematical modeling course for mathematics majors and minors. Primus, 32(7), 764–784. https://doi.org/10.1080/10511970.2021.1931995
Sidenvall, J., Granberg, C., Lithner, J., & Palmberg, B. (2022). Supporting teachers in supporting students’ mathematical problem solving. International Journal of Mathematical Education in Science and Technology, 55(10), 2389-2409. https://doi.org/10.1080/0020739X.2022.2151067
Siller, H. S., Nitzan-Tamar, O., & Kohen, Z. (2023). Scaffolding practices for modelling instruction in STEM-related contexts: Insights from expert and novice teachers. ZDM - Mathematics Education, 55(7), 1351–1364. https://doi.org/10.1007/s11858-023-01529-9
Smit, R., Dober, H., Hess, K., Bachmann, P., & Birri, T. (2023). Supporting primary students’ mathematical reasoning practice: The effects of formative feedback and the mediating role of self-efficacy. Research in Mathematics Education, 25(3), 277–300. https://doi.org/10.1080/14794802.2022.2062780
Smith, J. M., & Mancy, R. (2018). Exploring the relationship between metacognitive and collaborative talk during group mathematical problem-solving–what do we mean by collaborative metacognition? Research in Mathematics Education, 20(1), 14–36. https://doi.org/10.1080/14794802.2017.1410215
Sui, C. J., Yen, M. H., & Chang, C. Y. (2024). Teachers’ perceptions of teaching science with technology-enhanced self-regulated learning strategies through the DECODE model. Education and Information Technologies, 29(17), 22813-22839. https://doi.org/10.1007/s10639-024-12715-x
Suwarto, S., Hidayah, I., Rochmad, R., & Masrukan, M. (2023). Intuitive thinking: Perspectives on intuitive thinking processes in mathematical problem solving through a literature review. Cogent Education, 10(2), 2243119. https://doi.org/10.1080/2331186X.2023.2243119
Tesfaw, B. K., Ayele, M. A., & Wondimuneh, T. E. (2024). Context-based problem-posing and solving instructional approach and students’ engagement in learning data handling. Cogent Education, 11(1), 2389486. https://doi.org/10.1080/2331186X.2024.2389486
Tinungki, G. M., Hartono, P. G., Nurwahyu, B., Islamiyati, A., Robiyanto, R., Hartono, A. B., & Raya, M. Y. (2024). Exploring the team-assisted individualization cooperative learning to enhance mathematical problem solving, communication and self-proficiency in teaching non-parametric statistics. Cogent Education, 11(1), 2381333. https://doi.org/10.1080/2331186X.2024.2381333
Toikka, S., Eronen, L., Atjonen, P., & Havu-Nuutinen, S. (2024). Combined conceptualisations of metacognitive knowledge to understand students’ mathematical problem-solving. Cogent Education, 11(1), 2357901. https://doi.org/10.1080/2331186X.2024.2357901
Vogel, F., Kollar, I., Fischer, F., Reiss, K., & Ufer, S. (2022). Adaptable scaffolding of mathematical argumentation skills: The role of self-regulation when scaffolded with CSCL scripts and heuristic worked examples. International Journal of Computer-Supported Collaborative Learning, 17(1), 39–64. https://doi.org/10.1007/s11412-022-09363-z
Vygotsky, L. S. (1978). Mind in society: Development of higher psychological processes. Harvard university press.
Zhang, L., Stylianides, G. J., & Stylianides, A. J. (2024). Enhancing mathematical problem posing competence: A meta-analysis of intervention studies. International Journal of STEM Education, 11(1), 1–24. https://doi.org/10.1186/s40594-024-00507-1