Optimization of the motivation for success in mathematics at higher education: Evidence from novel graph-based visualization of three models

Mohamad Mustafa Hammoudi; Sofiane Grira

doi:10.29333/ejmste/13808

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Mohamad Mustafa Hammoudi ¹ ^* , Sofiane Grira ¹

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¹ Department of Mathematics and Statistics, Abu Dhabi University, Abu Dhabi, UAE^* Corresponding Author

Abstract

Using three mathematical models, this study aims to optimize students’ motivation for success in courses of mathematics at universities. The uniqueness of this study is crystalized in the novel graphical visualization of three models, which are integrated to analyze certain factors that help in optimizing students’ motivation for mathematical success. The proposed models will benefit students, educators, administrators of higher education, and societies around the world. A quantitative approach is used to design the research, which involved 366 female and 319 male students in different mathematics courses. The results show that the third, second, and first models are the top three in order. The third model accounts for 71.3% of the shift in the motivation for mathematical success. The difference in the motivation for mathematical success is explained by 66.3% in the second model and 65.0% in the first model.

Keywords

mathematical success
students’ motivation
higher education
mathematical modeling
regression analysis

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, Volume 19, Issue 11, November 2023, Article No: em2356

https://doi.org/10.29333/ejmste/13808

Publication date: 01 Nov 2023

Online publication date: 19 Oct 2023

Article Views: 940

Article Downloads: 775

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References

Abubakar, R. B., & Bada, I. A. (2012). Age and gender as determinants of academic achievements in college mathematics. Asian Journal of Natural and Applied Sciences, 1, 2.
Agtarap, R., & Miranda, A. T. (2022). The mediating effect of students’ resiliency on the relationship of self-concept and mathematics performance. Asian Journal of Education and Social Studies, 36(2), 1-10. https://doi.org/10.9734/ajess/2022/v36i2772
Anderson, R. C., & Haney, M. (2021). Reflection in the creative process of early adolescents: The mediating roles of creative metacognition, self-efficacy, and self-concept. Psychology of Aesthetics, Creativity, and the Arts, 15(4), 612. https://doi.org/10.1037/aca0000324
Berg, G. V. D., & Coetzee, L. R. (2014). Academic self-concept and motivation as predictors of academic achievement. International Journal of Educational Sciences, 6(3), 469-478. https://doi.org/10.1080/09751122.2014.11890158
Boadu, S. K., Arthur, Y. D., & Bonyah, E. (2023). Mediation and moderation effects of motivation and teaching quality on the relationship between peer tutoring and mathematics achievement. Journal of Mathematics and Science Teacher, 3(2), em039. https://doi.org/10.29333/mathsciteacher/13166
Brewer, E. W., & Burgess, D. N. (2005). Professor’s role in motivating students to attend class. Journal of Industrial Teacher Education, 42(23), 23-47.
Brezavšček, A., Jerebic, J., Rus, G., & Žnidaršič, A. (2020). Factors influencing mathematics achievement of university students of social sciences. Mathematics, 8(12), 2134. https://doi.org/10.3390/math8122134
Brophy, J. E. (2013). Motivating students to learn. Routledge.
Chao, T., Chen, J., Star, J. R., & Dede, C. (2016). Using digital resources for motivation and engagement in learning mathematics: Reflections from teachers and students. Digital Experiences in Mathematics Education, 2(3), 253-277. https://doi.org/10.1007/s40751-016-0024-6
Cheung, A. C., & Slavin, R. E. (2013). The effectiveness of educational technology applications for enhancing mathematics achievement in K-12 classrooms: A meta-analysis. Educational Research Review, 9, 88-113. https://doi.org/10.1016/j.edurev.2013.01.001
Corbiere, M., Fraccaroli, F., Mbekou, V., & Perron, J. (2006). Academic self-concept and academic interest measurement: A multi-sample European study. European Journal of Psychology of Education, 21(1), 3-15. https://doi.org/10.1007/BF03173566
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Springer. https://doi.org/10.1007/978-1-4899-2271-7
Dossi, G., Figlio, D., Giuliano, P., & Sapienza, P. (2021). Born in the family: Preferences for boys and the gender gap in math. Journal of Economic Behavior & Organization, 183, 175-188. https://doi.org/10.1016/j.jebo.2020.12.012
El-Adl, A., & Alkharusi, H. (2020). Relationships between self-regulated learning strategies, learning motivation and mathematics achievement. Cypriot Journal of Educational Sciences, 15(1), 104-111. https://doi.org/10.18844/cjes.v15i1.4461
Field, A. P., Evans, D., Bloniewski, T., & Kovas, Y. (2019). Predicting maths anxiety from mathematical achievement across the transition from primary to secondary education. Royal Society Open Science, 6(11), 191459. https://doi.org/10.1098/rsos.191459
Gogol, K., Brunner, M., Preckel, F., Goetz, T., & Martin, R. (2016). Developmental dynamics of general and school-subject-specific components of academic self-concept, academic interest, and academic anxiety. Frontiers in Psychology, 7, 356. https://doi.org/10.3389/fpsyg.2016.00356
Guo, J. P., Yang, L. Y., Zhang, J., & Gan, Y. J. (2022). Academic self-concept, perceptions of the learning environment, engagement, and learning outcomes of university students: Relationships and causal ordering. Higher Education, 83, 809-828. https://doi.org/10.1007/s10734-021-00705-8
Gupta, S., Harris, D. E., Caffier, N. M., & Caron, P. (2006). Predictors of student success in entry-level undergraduate mathematics courses. College Student Journal, 40(1), 97-108.
Hammoudi, M. M. (2019). Predictive factors of students’ motivation to succeed in introductory mathematics courses: evidence from higher education in the UAE. International Journal of Mathematical Education in Science and Technology, 50(5), 647-664. https://doi.org/10.1080/0020739X.2018.1529339
Hammoudi, M. M. (2020). Measurement of students’ mathematics motivation and self-concept at institutions of higher education: Evidence of reliability and validity. International Journal of Mathematical Education in Science and Technology, 51(1), 63-86. https://doi.org/10.1080/0020739X.2019.1670369
Hammoudi, M. M., & Grira, S. (2023). Improving students’ motivation in calculus courses at institutions of higher education: Evidence from graph-based visualization of two models. EURASIA Journal of Mathematics, Science and Technology Education, 19(1), em2209. https://doi.org/10.29333/ejmste/12771
Han, S., Capraro, R., & Capraro, M. M. (2015). How science, technology, engineering, and mathematics (STEM) project-based learning (PBL) affects high, middle, and low achievers differently: The impact of student factors on achievement. International Journal of Science and Mathematics Education, 13(5), 1089-1113. https://doi.org/10.1007/s10763-014-9526-0
House, J. D., & Telese, J. A. (2008). Relationships between students and instructional factors and algebra achievement of students in the United States and Japan: An analysis of TIMSS 2003 data. Educational Research and Evaluation, 14, 101-112. https://doi.org/10.1080/13803610801896679
Huitt, W. (2001). Motivation to learn: An overview. Educational Psychology Interactive, 12(3), 29-36.
Hvizdak, E., Prokosch, J., & Johnson, C. M. (2019). An analysis of help seeking behaviors in a required first year course. Public Services Quarterly, 15(4), 300-318. https://doi.org/10.1080/15228959.2019.1652722
Ingles, C. J., Torregrosa, M. S., Hidalgo, M. D., Nuñez, J. C., Castejón, J. L., García-Fernández, J. M., & Valle, A. (2012). Validity evidence based on internal structure of scores on the Spanish version of the self-description questionnaire-II. The Spanish Journal of Psychology, 15(1), 388-398. https://doi.org/10.5209/rev_SJOP.2012.v15.n1.37345
Jackson, C. R. (2018). Validating and adapting the motivated strategies for learning questionnaire (MSLQ) for STEM courses at an HBCU. Aera Open, 4(4), 2332858418809346. https://doi.org/10.1177/2332858418809346
Jónsdóttir, H. H., & Blöndal, K. S. (2022). The choice of track matters: Academic self-concept and sense of purpose in vocational and academic tracks. Scandinavian Journal of Educational Research, 67(4), 621-636. https://doi.org/10.1080/00313831.2022.2042843
Kulakow, S. (2020). Academic self-concept and achievement motivation among adolescent students in different learning environments: Does competence-support matter? Learning and Motivation, 70, 101632. https://doi.org/10.1016/j.lmot.2020.101632
Kushwaha, S. S. (2014). Trend in researches on mathematics achievement. IOSR Journal of Research & Method in Education, 4(6), 53-62. https://doi.org/10.9790/7388-04625362
Le, A. V., Bui, T. D., Tran, M. N., Trang Phung, T. T., & Vu, V. L. (2023). Gender gap in mathematics achievement: Vietnamese students in American mathematics competitions. Issues in Educational Research, 33(1), 137-154.
Lee, J. (2022). Unveiling the relationships among adolescents’ persistent academic possible selves, academic self-concept, self-regulation, and achievement: A longitudinal and moderated mediation study. Self and Identity, 21(4), 474-498. https://doi.org/10.1080/15298868.2021.1930578
Leng, E. Y., Baki, R., & Mahmud, R. (2010). Stability of the intrinsic motivation inventory (IMI) for the use of Malaysian form one students in ICT literacy class. EURASIA Journal of Mathematics, Science and Technology Education, 6(3), 215-226. https://doi.org/10.12973/ejmste/75241
Lishchynska, M., Palmer, C., Lacey, S., & O’Connor, D. (2023). Is motivation the key? Factors impacting performance in first year service mathematics modules. European Journal of Science and Mathematics Education, 11(1), 146-166. https://doi.org/10.30935/scimath/12529
Lohbeck, A., Nitkowski, D., & Petermann, F. (2016). A control-value theory approach: Relationships between academic self-concept, interest, and test anxiety in elementary school children. Child & Youth Care Forum, 45, 887-904. https://doi.org/10.1007/s10566-016-9362-1
Lyons, E., Mesghina, A., & Richland, L. E. (2022). Complicated gender gaps in mathematics achievement: Elevated stakes during performance as one explanation. Mind, Brain, and Education, 16(1), 36-47. https://doi.org/10.1111/mbe.12312
Marsh, H. W., & O’ Neil, R. (1984). Self description questionnaire III: The construct validity of multidimensional self-concept ratings by late adolescents. Journal of Educational Measurement, 21(2), 153-173. https://doi.org/10.1111/j.1745-3984.1984.tb00227.x
Marsh, H. W., Trautwein, U., Lüdtke, O., Köller, O., & Baumert, J. (2005). Academic self-concept, interest, grades, and standardized test scores: Reciprocal effects models of causal ordering. Child Development, 76(2), 397-416. https://doi.org/10.1111/j.1467-8624.2005.00853.x
Mejía-Rodríguez, A. M., Luyten, H., & Meelissen, M. R. (2021). Gender differences in mathematics self-concept across the world: An exploration of student and parent data of TIMSS 2015. International Journal of Science and Mathematics Education, 19(6), 1229-1250. https://doi.org/10.1007/s10763-020-10100-x
Morano, S., Markelz, A. M., Randolph, K. M., Myers, A. M., & Church, N. (2021). Motivation matters: Three strategies to support motivation and engagement in mathematics. Intervention in School and Clinic, 57(1), 15-22. https://doi.org/10.1177/1053451221994803
Nagy, G., Trautwein, U., Baumert, J., Köller, O., & Garrett, J. (2006). Gender and course selection in upper secondary education: Effects of academic self-concept and intrinsic value. Educational research and Evaluation, 12(4), 323-345. https://doi.org/10.1080/13803610600765687
Ngurah, A. A. M. I. G., & Lynch, D. P. (2013). A confirmatory factor analysis of attitudes toward mathematics inventory (ATMI). The Mathematics Educator, 15(1), 121-135.
Niss, M. (1994). Mathematics in society. Didactics of Mathematics as a Scientific Discipline, 13, 367-378.
Ostrow, K. S., & Heffernan, N. T. (2018). Testing the validity and reliability of intrinsic motivation inventory subscales within ASSISTments. In Proceedings of the International Conference on Artificial Intelligence in Education (pp. 381-394). Springer. https://doi.org/10.1007/978-3-319-93843-1_28
Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). Project on instructional processes and educational outcomes, 1-76. National Center for Research to Improve Postsecondary Teaching and Learning. https://files.eric.ed.gov/fulltext/ED338122.pdf
Preckel, F., Goetz, T., Pekrun, R., & Kleine, M. (2008). Gender differences in gifted and average-ability students: Comparing girls’ and boys’ achievement, self-concept, interest, and motivation in mathematics. Gifted Child Quarterly, 52(2), 146-159. https://doi.org/10.1177/0016986208315834
Primi, C., Bacherini, A., Beccari, C., & Donati, M. A. (2020). Assessing math attitude through the attitude toward mathematics inventory-short form in introductory statistics course students. Studies in Educational Evaluation, 64, 100838. https://doi.org/10.1016/j.stueduc.2020.100838
Ramírez Echeverry, J. J., García Carrillo, À., & Olarte Dussan, F. A. (2016). Adaptation and validation of the motivated strategies for learning questionnaire-MSLQ-in engineering students in Colombia. International Journal of Engineering Education, 32(4), 1774-1787.
Rodriguez, S., Regueiro, B., Piñeiro, I., Estévez, I., & Valle, A. (2020). Gender differences in mathematics motivation: Differential effects on performance in primary education. Frontiers in Psychology, 10, 3050. https://doi.org/10.1007/s10763-020-10100-x
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54-67. https://doi.org/10.1006/ceps.1999.1020
Saß, S., & Kampa, N. (2019). Self-concept profiles in lower secondary level–An explanation for gender differences in science course selection? Frontiers in Psychology, 10, 836. https://doi.org/10.3389/fpsyg.2019.00836
Schnitzler, K., Holzberger, D., & Seidel, T. (2021). All better than being disengaged: Student engagement patterns and their relations to academic self-concept and achievement. European Journal of Psychology of Education, 36(3), 627-652. https://doi.org/10.1007/s10212-020-00500-6
Sewasew, D., & Schroeders, U. (2019). The developmental interplay of academic self-concept and achievement within and across domains among primary school students. Contemporary Educational Psychology, 58, 204-212. https://doi.org/10.1016/j.cedpsych.2019.03.009
Shavelson, R. J., Hubner, J. J., & Stanton, G. C. (1976). Self-concept: Validation of construct interpretations. Review of Educational Research, 46(3), 407-441. https://doi.org/10.3102/00346543046003407
Simonsmeier, B. A., Peiffer, H., Flaig, M., & Schneider, M. (2020). Peer feedback improves students’ academic self-concept in higher education. Research in Higher Education, 61, 706-724. https://doi.org/10.1007/s11162-020-09591-y
Soysal, D., Bani-Yaghoub, M., & Riggers-Piehl, T. A. (2022). A machine learning approach to evaluate variables of math anxiety in STEM students. Pedagogical Research, 7(2), em0125. https://doi.org/10.29333/pr/11978
Tambunan, H. (2018). The dominant factor of teacher’s role as a motivator of students’ interest and motivation in mathematics achievement. International Education Studies, 11(4), 144-151. https://doi.org/10.5539/ies.v11n4p144
Tapia, M., & Marsh, G. E. (2002). Confirmatory factor analysis of the attitudes toward mathematics inventory [Paper presentation]. Annual Meeting of the Mid-South Educational Research Association.
Tolley, P. A., Blat, C., McDaniel, C., Blackmon, D., & Rovster, D. (2012). Enhancing the mathematics skills of students enrolled in introductory engineering courses: Eliminating the gap in incoming academic preparation. Journal of STEM Education: Innovation and Research, 13(3), 74-86.
Tossavainen, T., Rensaa, R. J., & Johansson, M. (2021). Swedish first-year engineering students’ views of mathematics, self-efficacy and motivation and their effect on task performance. International Journal of Mathematical Education in Science and Technology, 52(1), 23-38. https://doi.org/10.1080/0020739X.2019.1656827
Tran, L. T., & Nguyen, T. S. (2021). Motivation and mathematics achievement: A Vietnamese case study. Journal on Mathematics Education, 12(3), 449-468. https://doi.org/10.22342/jme.12.3.14274.449-468
Usán Supervía, P., Salavera Bordás, C., & Lorente, V. M. (2020). The mediating role of goal orientation (task) in the relationship between engagement and academic self-concept in students. International Journal of Environmental Research and Public Health, 17(22), 8323. https://doi.org/10.3390/ijerph17228323
van der Westhuizen, L., Niepel, C., Greiff, S., Fischbach, A., & Arens, A. K. (2023). The big-fish-little-pond effect on academic self-concept and interest in first-and third-grade students. Learning and Instruction, 87, 101802. https://doi.org/10.1016/j.learninstruc.2023.101802
Vorderman, C., Porkess, R., Budd, C., Dunne, R., Rahman-Hart, P. (2011). A world-class mathematics education for all young people. https://www.gloucestershire.gov.uk/media/12274/world_class_maths_report_aug11.pdf
Wang, L., & Yu, Z. (2023). Gender-moderated effects of academic self-concept on achievement, motivation, performance, and self-efficacy: A systematic review. Frontiers in Psychology, 14, 1136141. https://doi.org/10.3389/fpsyg.2023.1136141
Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92, 548-573. https://doi.org/10.1037/0033-295X.92.4.548
Wu, H., Guo, Y., Yang, Y., Zhao, L., & Guo, C. (2021). A meta-analysis of the longitudinal relationship between academic self-concept and academic achievement. Educational Psychology Review, 33, 1749-1778. https://doi.org/10.1007/s10648-021-09600-1

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APA

Hammoudi, M. M., & Grira, S. (2023). Optimization of the motivation for success in mathematics at higher education: Evidence from novel graph-based visualization of three models. Eurasia Journal of Mathematics, Science and Technology Education, 19(11), em2356. https://doi.org/10.29333/ejmste/13808

Vancouver

Hammoudi MM, Grira S. Optimization of the motivation for success in mathematics at higher education: Evidence from novel graph-based visualization of three models. EURASIA J Math Sci Tech Ed. 2023;19(11):em2356. https://doi.org/10.29333/ejmste/13808

AMA

Hammoudi MM, Grira S. Optimization of the motivation for success in mathematics at higher education: Evidence from novel graph-based visualization of three models. EURASIA J Math Sci Tech Ed. 2023;19(11), em2356. https://doi.org/10.29333/ejmste/13808

Chicago

Hammoudi, Mohamad Mustafa, and Sofiane Grira. "Optimization of the motivation for success in mathematics at higher education: Evidence from novel graph-based visualization of three models". Eurasia Journal of Mathematics, Science and Technology Education 2023 19 no. 11 (2023): em2356. https://doi.org/10.29333/ejmste/13808

Harvard

Hammoudi, M. M., and Grira, S. (2023). Optimization of the motivation for success in mathematics at higher education: Evidence from novel graph-based visualization of three models. Eurasia Journal of Mathematics, Science and Technology Education, 19(11), em2356. https://doi.org/10.29333/ejmste/13808

MLA

Hammoudi, Mohamad Mustafa et al. "Optimization of the motivation for success in mathematics at higher education: Evidence from novel graph-based visualization of three models". Eurasia Journal of Mathematics, Science and Technology Education, vol. 19, no. 11, 2023, em2356. https://doi.org/10.29333/ejmste/13808