LITERATURE REVIEW
A bibliometric analysis of the structural equation modeling in mathematics education
More details
Hide details
1
Faculty of Science and Natural Resources, University Malaysia Sabah, Kota Kinabalu, MALAYSIA
2
Hospital Universiti Malaysia Sabah, University Malaysia Sabah, Kota Kinabalu, MALAYSIA
Online publication date: 2023-10-27
Publication date: 2023-12-01
EURASIA J. Math., Sci Tech. Ed 2023;19(12):em2365
KEYWORDS
ABSTRACT
Structural equation modeling (SEM) is well-known in statistics due to its flexibility and accessibility. In the Scopus database alone, there were more than 1,500 search results related to SEM in mathematics education. However, there is a lack of scientific reviews of mathematics education that use SEM. The purpose of this study was to investigate research trends related to SEM in mathematics education. The researcher used Biblioshiny and VOSviewer to conduct bibliometric analysis on 1,017 papers that have been published in the Scopus database. The result showed that the number of publications in the research area has continuously grown over the last few decades. The US was the most prolific country in terms of publication and international collaboration. Professor Herbert W. Marsh had the most publications and citations, while the most productive journal was Frontiers in Psychology. The most current keywords include STEM, technology acceptance model, control-value theory, and computational thinking. Hence, these findings may serve as a guide for future researchers to conduct relevant research using SEM.
REFERENCES (30)
1.
Ahmi, A. (2022). Bibliometric analysis using R for non-coders: A practical handbook in conducting bibliometric analysis studies using Biblioshiny for Bibliometrix R-package.
https://www.aidi-ahmi.com/inde....
2.
Arthur, Y. D., Appiah, S. K., Amo-Asante, K., & Asare, B. (2022). Modeling student’s interest in mathematics: Role of history of mathematics, peer-assisted learning, and student’s perception. EURASIA Journal of Mathematics, Science and Technology Education, 18(10), em2168.
https://doi.org/10.29333/EJMST....
3.
Baas, J., Schotten, M., Plume, A., Côté, G., & Karimi, R. (2020). Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quantitative Science Studies, 1(1), 377-386.
https://doi.org/10.1162/QSS_A_....
4.
Baker, H. K., Kumar, S., & Pandey, N. (2020). Five decades of the Journal of Consumer Affairs: A bibliometric analysis. Wiley Online Library, 55, 293-331.
https://doi.org/10.1111/joca.1....
5.
Block, J. H., & Fisch, C. (2020). Eight tips and questions for your bibliographic study in business and management research. Management Review Quarterly, 70(3), 307-312.
https://doi.org/10.1007/S11301....
6.
Cardona, R. S. (2020). The enablers and outcomes of research productivity among junior high school mathematics teachers: A structural model. EURASIA Journal of Mathematics, Science and Technology Education, 16(11), em1901.
https://doi.org/10.29333/ejmst....
7.
Colledge, L., de Moya-Anegón, F., Guerrero-Bote, V. P., López-Illescas, C., & Moed, H. F. (2010). SJR and SNIP: Two new journal metrics in Elsevier’s Scopus. Insights, 23(3), 215.
https://doi.org/10.1629/23215.
9.
Davadas, S. D., & Lay, Y. F. (2018). Factors affecting students’ attitude toward mathematics: A structural equation modeling approach. EURASIA Journal of Mathematics, Science and Technology Education, 14(1), 517-529.
https://doi.org/10.12973/ejmst....
10.
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296.
https://doi.org/10.1016/j.jbus....
12.
Hair, J. F., Black, W. C., & Babin, B. J. (2010). Multivariate data analysis: A global perspective. Pearson Education.
13.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.
https://doi.org/10.2753/MTP106....
14.
Karakaya-Ozyer, K., & Aksu-Dunya, B. (2018). A review of structural equation modeling applications in Turkish educational science literature, 2010-2015. International Journal of Research in Education and Science, 4(1), 279-291.
https://doi.org/10.21890/ijres....
16.
Krauskopf, E. (2018). A bibliometric analysis of the Journal of Infection and Public Health: 2008-2016. Journal of Infection and Public Health, 11(2), 224-229.
https://doi.org/10.1016/J.JIPH....
17.
Lee, C.-Y., & Kung, H.-Y. (2018). Math self-concept and mathematics achievement: Examining gender variation and reciprocal relations among junior high school students in Taiwan. EURASIA Journal of Mathematics, Science and Technology Education, 14(4), 1239-1252.
https://doi.org/10.29333/ejmst....
18.
McAllister, J. T., Lennertz, L., & Atencio Mojica, Z. (2021). Mapping a discipline: A guide to using VOSviewer for bibliometric and visual analysis. Science & Technology Libraries, 41(3), 319-348.
https://doi.org/10.1080/019426....
19.
McCabe, K. O., Lubinski, D., & Benbow, C. P. (2020). Who shines most among the brightest?: A 25-year longitudinal study of elite STEM graduate students. Journal of Personality and Social Psychology, 119(2), 390-416.
https://doi.org/10.1037/PSPP00....
20.
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151(4), 264-269.
https://doi.org/10.7326/0003-4....
21.
Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. Profesional de la Información [Information Professional], 29(1), e290103.
https://doi.org/10.3145/epi.20....
22.
Phan, T. T., Duong, H. T., Do, T. T., Trinh, T. P. T., Trinh, T. H., Do, B. C., Tran, T., & Nguyen, T.-T. (2022). A bibliometric review on realistic mathematics education in Scopus database between 1972-2019. European Journal of Educational Research, 11(2), 1133-1149.
https://doi.org/10.12973/eu-je....
23.
Sakaria, D., Maat, S. M., & Mohd Matore, M. E. E. (2023). Examining the optimal choice of SEM statistical software packages for sustainable mathematics education: A systematic review. Sustainability, 15(4), 3209.
https://doi.org/10.3390/su1504....
24.
Scopus–Your Brilliance, Connected. (2022). Content policy and selection. Elsevier. www.elsevier.com/solutions/scopus/how-scopus-works/content/content-policy-and-selection.
25.
Somasundram, P. (2021). The role of cognitive factors in year five pupils’ algebraic thinking: A structural equation modelling analysis. EURASIA Journal of Mathematics, Science and Technology Education, 17(1), em1935.
https://doi.org/10.29333/ejmst....
26.
Suseelan, M., Chew, C. M., & Chin, H. (2022). Research on mathematics problem solving in elementary education conducted from 1969 to 2021: A bibliometric review. International Journal of Education in Mathematics, Science and Technology, 10(4), 1003-1029.
https://doi.org/10.46328/ijems....
28.
Wall, K. (2019). Persistence and representation of women in STEM programs. Insights on Canadian Society. Statistics Canada. www.statcan.gc.ca.
29.
Xu, X., Zhang, Q., Sun, J., & Wei, Y. (2022). A bibliometric review on latent topics and research trends in the growth mindset literature for mathematics education. Frontiers in Psychology, 13.
https://doi.org/10.3389/fpsyg.....
30.
Yin, H., & Huang, S. (2021). Applying structural equation modelling to research on teaching and teacher education: Looking back and forward. Teaching and Teacher Education, 107, 103438.
https://doi.org/10.1016/j.tate....