• Abstract

    This study presents a hybrid systematic literature review (SLR) and bibliometric analysis aimed at examining the development, trends, and theoretical implications of statistical literacy research. Using the PRISMA protocol, 89 relevant articles published between 2002 and 2025 were analysed to address three research questions concerning the significance of statistical literacy as a future research domain, the distribution of scholarly investigations, and their theoretical and practical implications. The findings show a consistent increase in research interest over the past decade, especially after 2017, with dominant themes including statistical literacy, statistics education, and data literacy. The analysis also reveals an imbalance in research allocation, with higher education receiving disproportionate attention compared to other educational levels. Moreover, the results underscore the integrative role of statistical thinking and reasoning as essential components of statistical literacy, with growing emphasis on digital learning, real-world data contexts, and interdisciplinary approaches. This review highlights both the progress and the existing gaps in the field, providing a roadmap for future research that prioritizes inclusive, context-sensitive, and pedagogically sound models for enhancing statistical literacy in a data-driven society. In addition to thematic and theoretical insights, this study also explores the most influential journals, authors, and citation networks, providing a clearer picture of the academic landscape surrounding statistical literacy. The bibliometric data help reveal publication patterns, collaboration trends, and emerging research clusters. These findings are valuable for identifying research gaps, informing curriculum development, and fostering cross-institutional and interdisciplinary partnerships. By highlighting these dimensions, the review contributes to a deeper understanding of how the field has evolved and where it is heading.

  • References

    1. Afifah, D. S. N., & Nafi'an, M. I. (2019). An onto-semiotic approach: Analyzing of field-independent and field-dependent students' understanding in solving statistical problems. Journal of Physics: Conference Series, 1175, 012148. https://doi.org/10.1088/1742-6596/1175/1/012148
    2. Apino, E., Retnawati, H., Purbani, W., & Hidayati, K. (2024). The statistical literacy of mathematics education students: An investigation on understanding the margin of error. TEM Journal, 13(1), 293–302. https://doi.org/10.18421/TEM131-31
    3. Aziz, A. M., & Rosli, R. (2021). A systematic literature review on developing students’ statistical literacy skills. Journal of Physics: Conference Series, 1806(1). https://doi.org/10.1088/1742-6596/1806/1/012102
    4. Batur, A., & Baki, A. (2022). Lise öğrencilerinin istatistik okuryazarlık düzeyleri ile istatistik okuryazarlık öz yeterlik algıları arasındaki ilişkinin incelenmesi. Eğitim ve Bilim, 47(209), 171–205. https://doi.org/10.15390/EB.2022.9970
    5. Blackburn, H. (2015). The status of women in STEM in higher education: A review of the literature 2004–2014. Science & Technology Libraries, 34(3), 235–273. https://doi.org/10.1080/0194262X.2015.1114816
    6. Brearley, A. M., Rott, K. W., & Le, L. J. (2023). A biostatistical literacy course: Teaching medical and public health professionals to read and interpret statistics in the published literature. Journal of Statistics and Data Science Education, 31(3), 286–294. https://doi.org/10.1080/26939169.2023.2165987
    7. Buckingham, J., Wheldall, K., & Beaman-Wheldall, R. (2013). Why poor children are more likely to become poor readers: The school years. Australian Journal of Education, 57(3), 190–213. https://doi.org/10.1080/00131911.2013.795129
    8. Camilo, C., & Vaz Garrido, M. (2019). Systematic review in psychology: Challenges and guidelines. Analise Psicologica, 37(3), 391–403. https://doi.org/10.14417/ap.1546
    9. Carmichael, C., Callingham, R., Hay, I., & Watson, J. (2010). Statistical literacy in the middle school: The relationship between interest, self-efficacy and prior mathematics achievement. Australian Journal of Educational and Developmental Psychology, 10, 83–93.
    10. Chen, C., & Song, M. (2019). Visualizing a field of research: A methodology of systematic scientometric reviews. PLoS ONE, 14(10), e0223994. https://doi.org/10.1371/journal.pone.0223994
    11. Elfitra, & Siregar, T. M. (2020). Statistical literacy analysis of mathematics education students through KKNI assignments. Journal of Physics: Conference Series, 1462, 012028. https://doi.org/10.1088/1742-6596/1462/1/012028
    12. Flores, J. R., Cueva, C. E., Rodríguez, S., & Guerra, J. (2023). The use of LMS platforms in the development of statistical skills: A systematic review. Education and Information Technologies, 28(1), 103–123. https://doi.org/10.1007/s10639-022-11182-3
    13. Friedrich, A., Schreiter, S., Vogel, M., & Malone, S. (2024). What shapes statistical and data literacy research in K-12 STEM education? A systematic review of metrics and instructional strategies. International Journal of STEM Education, 11(1), 1–24. https://doi.org/10.1186/s40594-024-00517-z
    14. Gal, I., & Geige, V. (2022). Welcome to the era of vague news: A study of the demands of statistical and mathematical products in the COVID-19 pandemic media. Educational Studies in Mathematics, 111(1), 5–28. https://doi.org/10.1007/s10649-022-10151-7
    15. Gallou-Guyot, M., Rousseau, C., & Perrochon, A. (2024). The limits of systematic literature reviews – when too much information becomes deleterious. Kinesitherapie, 24(267), 60–65. https://doi.org/10.1016/j.kine.2023.11.004
    16. Garfield, J., & Ben-Zvi, D. (2007). How students learn statistics revisited: A current review of research on teaching and learning statistics. International Statistical Review, 75(3), 372–396. https://doi.org/10.1111/j.1751-5823.2007.00029.x
    17. Ghodoosi, B., West, T., Li, Q., & Dey, S. (2023). A systematic literature review of data literacy education. Journal of Business and Finance Librarianship, 28(2), 87–104. https://doi.org/10.1080/08963568.2023.2171552
    18. Hafiyusholeh, M., Budayasa, K., & Siswono, T. Y. E. (2018). Statistical literacy: High school students in reading, interpreting, and presenting data. Journal of Physics: Conference Series, 947, 012036. https://doi.org/10.1088/1742-6596/947/1/012036
    19. Hahs-Vaughn, D. L., Acquaye, H., Griffith, M. D., Jo, H., Matthews, K., & Acharya, P. (2017). Statistical literacy as a function of online versus hybrid course delivery format for an introductory graduate statistics course. Journal of Statistics Education, 25(3), 112–121. https://doi.org/10.1080/10691898.2017.1370363
    20. Hake, R. R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66(1), 64–74. https://doi.org/10.1119/1.18809
    21. Hariyanti, F., Budayasa, I. K., & Setianingsih, R. (2025). A portrait of prospective mathematics teachers’ readiness in statistical literacy of school students. Perspektivy Nauki i Obrazovania, 73(1), 190–201. https://doi.org/10.32744/pse.2025.1.12
    22. Hariyanti, F., Budayasa, I. K., & Setianingsih, R. (2025). The role of AI in enhancing statistical literacy: A systematic review in education. Multidisciplinary Reviews, 8(12), 2025376. https://doi.org/10.31893/multirev.2025376
    23. Harwell, M., Maeda, Y., Bishop, K., & Xie, A. (2017). The surprisingly modest relationship between SES and educational achievement. Journal of Experimental Education, 85(2), 197–214. https://doi.org/10.1080/00220973.2015.1123668
    24. Hasim, M. S., Daud, M. F., & Sulaiman, T. (2024). Contextual teaching and learning: Enhancing students’ statistical reasoning through real-world data. Malaysian Journal of Learning and Instruction, 21(1), 135–152. https://doi.org/10.32890/mjli2024.21.1.6
    25. Hite, C. E. (2004). Expository content area texts, cognitive style and gender: Their effects on reading comprehension. Reading Research and Instruction, 43(4), 41–74. https://doi.org/10.1080/19388070409558416
    26. Holmberg, C. (2024). Toward a better understanding of statistical significance and p-values in nursing. Nursing Forum, 59(1), 40–48. https://doi.org/10.1155/2024/7263781
    27. Hussain, S., Khan, A., & Ramzan, M. (2024). The impact of online learning platforms on students’ achievement in statistics education during COVID-19. Education and Information Technologies, 29(1), 456–470. https://doi.org/10.1007/s10639-023-11871-2
    28. Jasinska, K., Zinszer, B., Xu, Z., & Akpé, H. (2022). Home learning environment and physical development impact children's executive function development and literacy in rural Côte d'Ivoire. Cognitive Development, 62, 101149. https://doi.org/10.1016/j.cogdev.2022.101265
    29. Khan, F., Wortsman, B., Whitehead, H. L., & Jasińska, K. K. (2024). Modeling the associations between socioeconomic risk factors, executive function components, and reading among children in rural Côte d'Ivoire. Cognitive Development, 67, 101210. https://doi.org/10.1016/j.cogdev.2024.101436
    30. Lateh, A. (2024). Exploring statistical literacy deficiencies and causal associations among master and doctoral graduates in Thailand. Pakistan Journal of Life and Social Sciences, 22(1), 10–18. https://doi.org/10.57239/PJLSS-2024-22.2.00322
    31. Lestari, K. E., Risnawita, Yudhanegara, M. R., Nugraha, E. S., & Sylviani, S. (2024). Correspondence analysis on statistical literacy and gender: Embedding e-campus platform with random assignment of matched subject in explanatory analysis. BAREKENG: Jurnal Matematika dan Aplikasi, 18(3), 1975–1988. https://doi.org/10.30598/barekengvol18iss3pp1975-1988
    32. Lilly, K., & Conway, B. M. (2025). A case study of an evaluation of pen-and-paper homework and project-based learning of statistical literacy in an introductory statistics course. Journal of Statistics and Data Science Education, 00(0), 1–7. https://doi.org/10.1080/26939169.2025.2462604
    33. Lukman, L., Wahyudin, W., Suryadi, D., Dasari, D., & Prabawanto, S. (2022). Studying student statistical literacy in statistics lectures on higher education using grounded theory approach. Infinity, 11(1), 163–176. https://doi.org/10.22460/infinity.v11i1.p163-176
    34. Macfeely, S., Campos, P., & Helenius, R. (2017). Key success factors for statistical literacy poster competitions. Statistics Education Research Journal, 16(1), 68–75. https://doi.org/10.52041/serj.v16i1.224
    35. Maryati, I., Fisher, D., Yatim, S. A. M., & Mauladaniyati, R. (2024). Statistical literacy ability of students through virtual learning environment based on Moodle-Learning Management System. International Journal of Information and Education Technology, 14(1), 99–106. https://doi.org/10.18178/ijiet.2024.14.1.2029
    36. Myrberg, E., & Rosén, M. (2008). A path model with mediating factors of parents' education on students' reading achievement in seven countries. Educational Research and Evaluation, 14(6), 507–520. https://doi.org/10.1080/13803610802576742
    37. Ortiz, N. A., Capraro, M. M., & Capraro, R. M. (2018). Does it really matter? Exploring cultural relevance within a majority white classroom. Journal of Negro Education, 87(1), 66–78. https://doi.org/10.7709/jnegroeducation.87.4.0404
    38. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. PLoS Medicine, 18(3), e1003583. https://doi.org/10.1136/bmj.n71
    39. Pascual, R. F., Caballero Mariscal, D., Pinto, M., & Marín-Jiménez, A. E. (2025). Attitudes of university students toward statistics as a pathway to data literacy: A meta-analysis. Journal of Statistics and Data Science Education, 00(0), 1–18. https://doi.org/10.1080/26939169.2025.2475765
    40. Pinto, M., Caballero-Mariscal, D., García, F.-J., & Gómez-Camarero, C. (2023). A strategic approach to information literacy: Data literacy. A systematic review. Profesional de la Información, 32(6). https://doi.org/10.3145/epi.2023.nov.09
    41. Retnawati, H., Hidayati, K., Apino, E., Rafi, I., & Rosyada, M. N. (2024). Exploring influential factors and conditions shaping statistical literacy among undergraduate students in mathematics education. International Journal of Cognitive Research in Science, Engineering and Education, 12(1), 1–17. https://doi.org/10.23947/2334-8496-2024-12-1-1-17
    42. Risqi, E. N., & Ekawati, R. (2020). How is the statistical literacy of upper secondary students based on gender differences? Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika, 4(1), 53–67. https://doi.org/10.26740/jrpipm.v4n1.p53-67
    43. Riwayani, R., Istiyono, E., Supahar, S., & Soeharto, S. (2024). Analyzing students’ statistical literacy skills based on gender, grade, and educational field. International Journal of Evaluation and Research in Education, 13(1), 1–9. http://doi.org/10.11591/ijere.v13i2.26299
    44. Rodríguez-Alveal, F., Maldonado-Fuentes, A. C., & Díaz-Levicoy, D. (2024). Lexical ambiguities in statistics declared by in-training and in-service teachers. EURASIA Journal of Mathematics, Science and Technology Education, 20(4), em2422. https://doi.org/10.29333/ejmste/14359
    45. Rumsey, D. J. (2002). Statistical literacy as a goal for introductory statistics courses. Journal of Statistics Education, 10(3), 1–12. https://doi.org/10.1080/10691898.2002.11910678
    46. Schield, M. (2011). Statistical literacy: A new mission for data producers. Statistical Journal of the IAOS, 27(3–4), 173–183. https://doi.org/10.3233/SJI-2011-0732
    47. Schield, M. (2017). GAISE 2016 promotes statistical literacy. Statistics Education Research Journal, 16(1), 31–37. https://doi.org/10.52041/serj.v16i1.214
    48. Schreiter, S., Friedrich, A., Fuhr, H., & Vogel, M. (2024). Teaching for statistical and data literacy in K–12 STEM education: A systematic review on teacher variables, teacher education, and impacts on classroom practice. ZDM – Mathematics Education, 56(1), 105–122. https://doi.org/10.1007/s11858-023-01531-1
    49. Schreiter, S., Friedrich, A., Fuhr, H., Malone, S., Brünken, R., Kuhn, J., & Vogel, M. (2024). Teaching for statistical and data literacy in K-12 STEM education: A systematic review on teacher variables, teacher education, and impacts on classroom practice. ZDM – Mathematics Education, 56(1), 31–45. https://doi.org/10.1007/s11858-023-01531-1
    50. Sefriani, R., Abidin, N. Z., & Irawan, Y. (2024). Effectiveness of Edmodo in improving students’ statistical literacy: A quasi-experimental study. Journal of Educational Technology & Online Learning, 5(1), 45–59. https://doi.org/10.1080/jetol.2024.11857
    51. Sharma, S. (2017). Definitions and models of statistical literacy: A literature review. Open Review of Educational Research, 4(1), 118–133. https://doi.org/10.1080/23265507.2017.1354313
    52. Shobikhah, A., Sukestiyarno, Y. L., Agoestanto, A., & Cahyono, A. N. (2025). Bibliometrics on the development of students’ statistical literacy: A scoping review of research between the years 2000–2024. TEM Journal, 14(1), 871–886. https://doi.org/10.18421/TEM141-77
    53. Sole, M. A. (2025). An investigation designed to teach statistical thinking in the midst of the COVID-19 pandemic: Are teens living like vampires? Journal of Statistics and Data Science Education, 00(0), 1–11. https://doi.org/10.1080/26939169.2025.2455197
    54. Szomszor, M., Adams, J., Fry, R., Gebert, C., & Pendlebury, D. A. (2021). Interpreting bibliometric data. Frontiers in Research Metrics and Analytics, 5, 628703. https://doi.org/10.3389/frma.2020.628703
    55. Towse, J., Davies, R., Ball, E., James, R., Gooding, B., & Ivory, M. (2022). Lustre: An online data management and student project resource. Journal of Statistics and Data Science Education, 30(3), 266–273. https://doi.org/10.1080/26939169.2022.2118645
    56. Wahab, A., & Mahmud, A. (2018). The effectiveness of a learning module for statistical literacy. New Educational Review, 53(3), 187–200. https://doi.org/10.15804/tner.2018.53.3.16
    57. Watson, J., & Smith, C. (2022). Statistics education at a time of global disruption and crises: A growing challenge for the curriculum, classroom and beyond. Curriculum Perspectives, 42, 171–179. https://doi.org/10.1007/s41297-022-00167-7
    58. Weiland, T. (2017). Problematizing statistical literacy: An intersection of critical and statistical literacies. Educational Studies in Mathematics, 96, 33–47. https://doi.org/10.1007/s10649-017-9764-5
    59. Weiland, T., & Sundrani, A. (2022). Opportunities for K–8 students to learn statistics created by states’ standards in the United States. Journal of Statistics and Data Science Education, 30(2), 165–178. https://doi.org/10.1080/26939169.2022.2075814
    60. Wild, C. J., & Pfannkuch, M. (1999). Statistical thinking in empirical enquiry. International Statistical Review, 67(3), 223–248. https://doi.org/10.2307/1403699
    61. Zavarrone, E. (2017). Latent growth and statistical literacy. In Studies in Classification, Data Analysis, and Knowledge Organization (pp. 389–396). Springer.
    62. Zhang, P., & Han, C. (2024). Examining statistical literacy, attitudes toward statistics, and statistics self-efficacy among applied linguistics research students in China. International Journal of Applied Linguistics, 34(2), 433–449. https://doi.org/10.1111/ijal.12500
    63. Ziegler, L., & Garfield, J. (2018). Developing a statistical literacy assessment for the modern introductory statistics course. Statistics Education Research Journal, 17(2), 161–178. https://doi.org/10.52041/serj.v17i2.164

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Rodliyah, I., Budayasa, I. K., & Khabibah, S. (2025). Statistical literacy: A hybrid systematic literature review and bibliometric analysis. Multidisciplinary Reviews, 9(4), 2026171. https://doi.org/10.31893/multirev.2026171
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