Mapping Mathematical Literacy Research in Elementary Education: A Bibliometric Analysis of Trends, Innovation, and Inclusive Practices

Ratih Purnamasari, Yurniwati Yurniwati, Suyono Suyono

Abstract


This study aims to map mathematical literacy research in elementary education by examining
publication trends, conceptual structures, influential documents, productive authors,
publication sources, institutional contributions, country contributions, and future research
directions related to innovation and inclusive practices. This study employed a bibliometric
approach using Scopus data from 1983 to 2026. A total of 310 documents from 196 sources
were analyzed using Biblioshiny and VOSviewer to identify annual growth, citation patterns,
keyword co-occurrence, document coupling, source productivity, institutional distribution,
and country collaboration. The findings show that this field has developed over a long period
with relatively stable growth, an annual growth rate of 4.63%, and an average citation rate of
16.44 per document. Publications increased notably after 2015, although recent citation
patterns indicate that the field is entering a more mature stage. The dominant keywords are
primary education, numeracy, mathematical literacy, literacy, and early numeracy.
Numeracy functions as a central theme, early numeracy appears as a more specific influential
theme, and mathematical literacy serves as a broader framework linking reasoning, problem
solving, interpretation, real-life contexts, assessment, curriculum, instructional innovation,
and socio-educational issues. Spaull’s article is the most influential document, while Pauline
Rose, Mike Askew, and Margaret Brown are productive authors. At the institutional level, the
University of Cambridge, University of London, and Monash University emerged as major
contributors. At the country level, the United Kingdom, Australia, Indonesia, and the United
States were important contributors. Future research should strengthen methodological
quality, digital learning innovation, inclusive practices, local contexts, and cross-country
collaboration.

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References


Ahyan, S., Turmudi, T., & Juandi, D. (2021). Bibliometric analysis of research on mathematical literacy in Indonesia. Journal of Physics:

Conference Series, 1869(1), 012120. doi:10.1088/1742-6596/1869/1/012120

Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4),

–975. doi:10.1016/j.joi.2017.08.007

Australian Curriculum, Assessment and Reporting Authority. (n.d.). National numeracy learning progression. Retrieved from

https://www.australiancurriculum.edu.au/resources/national-literacy-and-numeracy-learning-progressions/national-

numeracy-learning-progression/

Azman, H. (2016). Implementation and challenges of English language education reform in Malaysian primary schools. 3L: The

Southeast Asian Journal of English Language Studies, 22(3), 65–78. doi:10.17576/3L-2016-2203-05

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. doi:10.1162/qss_a_00019

Bradford, S. C. (1934). Sources of information on specific subjects. Engineering, 137, 85–86.

Carmichael, C., MacDonald, A., & McFarland-Piazza, L. (2014). Predictors of numeracy performance in national testing programs:

Insights from the longitudinal study of Australian children. British Educational Research Journal, 40(4), 637–659.

doi:10.1002/berj.3104

Cumming, J., Goldstein, H., & Hand, K. (2020). Enhanced use of educational accountability data to monitor educational progress of

Australian students with focus on Indigenous students. Educational Assessment, Evaluation and Accountability, 32, 29–51.

doi:10.1007/s11092-019-09310-xa

Department for Education. (2021). Mathematics programmes of study: Key stages 1 and 2. Retrieved from

https://www.gov.uk/government/publications/national-curriculum-in-england-mathematics-programmes-of-study

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. doi:10.1016/j.jbusres.2021.04.070

Edwards, A., & Warin, J. (1999). Parental involvement in raising the achievement of primary school pupils: Why bother? Oxford Review

of Education, 25(3), 325–341. doi:10.1080/030549899104017

Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact? Scientometrics, 105,

–1831. doi:10.1007/s11192-015-1645-z

Fajri, H. M., Marini, A., & Suyono. (2025). A bibliometric study on mathematical modelling in elementary schools in the Scopus database

between 1990–2024. Eu’sia Journal of Mathematics, Science and Technology Education, 21(2), em2577.

doi:10.29333/ejmste/15916

Falloon, G. (2016). An analysis of young students’ thinking when completing basic coding tasks using ScratchJr on the iPad. Journal of

Computer Assisted Learning, 32(6), 576–593. doi:10.1111/jcal.12155

Gaihre, S., Semple, S., Miller, J., Fielding, S., & Turner, S. (2014). Classroom carbon dioxide concentration, school attendance, and

educational attainment. Journal of School Health, 84(9), 569–574. doi:10.1111/josh.12183

Geiger, V., Goos, M., & Forgasz, H. (2015). A rich interpretation of numeracy for the 21st century: A survey of the state of the field. ZDM

Mathematics Education, 47, 531–548. doi:10.1007/s11858-015-0708-1

Gibbs, L., Nursey, J., Cook, J., Ireton, G., Alkemade, N., Roberts, M., Gallagher, H. C., Bryant, R., Block, K., Molyneaux, R., & Forbes, D.

(2019). Delayed disaster impacts on academic performance of primary school children. Child Development, 90(4), 1402–1412.

doi:10.1111/cdev.13200

Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences,

(46), 16569–16572. doi:10.1073/pnas.0507655102

Kadir, A., & Haryanto, H. (2023). Mathematical abilities of elementary school students: A bibliometric analysis. Proceedings Series on

Social Sciences & Humanities, 12.

Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation, 14(1), 10–25.

doi:10.1002/asi.5090140103

Lee, K., Ng, S. F., Pe, M. L., Ang, S. Y., Hasshim, M. N. A. M., & Bull, R. (2012). The cognitive underpinnings of emerging mathematical

skills: Executive functioning, patterns, numeracy, and arithmetic. British Journal of Educational Psychology, 82(1), 82–99.

doi:10.1111/j.2044-8279.2010.02016.x

Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D.

(2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care

interventions: Explanation and elaboration. PLoS Medicine, 6(7), e1000100. doi:10.1371/journal.pmed.1000100

Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of the Washington Academy of Sciences, 16(12), 317–

Mahmudin, M., Herman, T., Supriyadi, E., Iskandar, R. S. F., & Sugiarni, R. (2023). Analisis bibliometrik literasi matematika dalam

database Scopus menggunakan VOSviewer. AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 12(3), 3213.

doi:10.24127/ajpm.v12i3.6832

Mejía-Rodríguez, A. M., Luyten, H., & Meelissen, M. R. M. (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, 1229–

doi:10.1007/s10763-020-10100-x

Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106,

–228. doi:10.1007/s11192-015-1765-5

Muijs, D., & Reynolds, D. (2000). School effectiveness and teacher effectiveness in mathematics: Some preliminary findings from the

evaluation of the Mathematics Enhancement Programme (Primary). School Effectiveness and School Improvement, 11(3), 273–

doi:10.1076/0924-3453(200009)11:3;1-G;FT273

National Council of Teachers of Mathematics. (1980). An agenda for action: Recommendations for school mathematics of the 1980s.

Reston, VA: Author.

National Science and Technology Council. (2024). Federal strategic plan for advancing STEM education and cultivating STEM talent.

Washington, DC: The White House.

OECD. (2006). Assessing scientific, reading and mathematical literacy: A framework for PISA 2006. Paris, France: OECD Publishing.

doi:10.1787/9789264026407-en

OECD. (2023). PISA 2022 assessment and analytical framework. Paris, France: OECD Publishing. doi:10.1787/dfe0bf9c-en

Pranckutė, R. (2021). Web of Science (WoS) and Scopus: The titans of bibliographic information in today’s academic world.

Publications, 9(1), 12. doi:10.3390/publications9010012

Price, D. J. de S. (1963). Little science, big science. New York, NY: Columbia University Press.

Pusat Asesmen Pendidikan. (n.d.). Asesmen Kompetensi Minimum. Retrieved from

https://pusmendik.kemdikbud.go.id/an/page/asesmen_kompetensi_minimum

Rong, X. L., & Shi, T. (2001). Inequality in Chinese education. Journal of Contemporary China, 10(26), 107–124.

doi:10.1080/10670560124330

Santos, R., Santiago, A., & Cruz, C. (2024). Problem posing and problem solving in primary school: Opportunities for the development

of different literacies. Education Sciences, 14(1), 97. doi:10.3390/educsci14010097

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–

doi:10.1016/j.jbusres.2019.07.039

Spaull, N. (2013). Poverty and privilege: Primary school inequality in South Africa. International Journal of Educational Development,

(5), 436–447. doi:10.1016/j.ijedudev.2012.09.009

Susanta, A., Susanto, E., Stiadi, E., & Rusnilawati. (2023). Mathematical literacy skills for elementary school students: A comparative

study between interactive STEM learning and paper-and-pencil STEM learning. European Journal of Educational Research,

(4), 1569–1582. doi:10.12973/eu-jer.12.4.1569

ten Braak, D., Lenes, R., Purpura, D. J., Schmitt, S. A., & Størksen, I. (2022). Why do early mathematics skills predict later mathematics

and reading achievement? The role of executive function. Journal of Experimental Child Psychology, 214, 105306.

doi:10.1016/j.jecp.2021.105306

Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84,

–538. doi:10.1007/s11192-009-0146-3

Van Eck, N. J., & Waltman, L. (2023). VOSviewer manual. Retrieved from

https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.20.pdf

Waltman, L. (2016). A review of the literature on citation impact indicators. Journal of Informetrics, 10(2), 365–391.

doi:10.1016/j.joi.2016.02.007

Widiawati, H., Sujarwo, S., & Saptono, B. (2025). Numeracy literacy innovations in primary education: A bibliometric exploration of

future trends and directions. Educational Process: International Journal, 18, e2025431. doi:10.22521/edupij.2025.18.431

Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–

doi:10.1177/1094428114562629


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