Main Article Content

Abstract

Statistical literacy is an essential competence that people must face in the era of big data and Society 5.0. In Indonesia and several countries, statistics is taught as a list of competencies in mathematics subject in primary and secondary schools. This study aimed to identify whether statistical tasks in higher secondary school mathematics textbooks support statistical literacy. The qualitative data were collected via deductive content analysis, with a specific framework, toward five Compulsory Mathematics textbooks used in Indonesia. We found that statistical exercises and problems in these textbooks were dominated by data analysis type, emphasizing calculating statistics from raw data and its modification. Regarding data visualization, almost all textbooks introduced the histogram and ogive, while some also introduced the boxplot, stem-and-leaf plot, and dot plot. Improvement could be made by adding more exercises and problems related to the interpretation of statistics, evaluation of statistical results, and comparison of statistics from several data groups.


DOI: https://doi.org/10.22342/jpm.17.2.2023.247-264

Keywords

Statistical Literacy Task Textbooks Visualization

Article Details

How to Cite
Setiawan, E. P., Sukoco, H., & Agustyani, A. R. D. (2024). Developing Statistical Literacy Through Tasks: An Analysis of Secondary School Mathematics Textbooks. Jurnal Pendidikan Matematika, 17(2), 247–264. Retrieved from https://jpm.ejournal.unsri.ac.id/index.php/jpm/article/view/174

References

  1. Alajmi, A. H. (2012). How do elementary textbooks address fractions? A review of mathematics textbooks in the USA, Japan, and Kuwait. Educational Studies in Mathematics, 79(2), 239–261. https://doi.org/10.1007/s10649-011-9342-1
  2. Batanero, C., Burrill, G., & Reading, C. E. (2011). Teaching statistics in school mathematics - Challenges for teaching and teacher education. A joint ICMI/IASE study: The 18th ICMI study (1st ed.). Springer. https://doi.org/10.1007/978-94-007-1131-0
  3. Cahyono, B., & Adilah, N. (2016). Analisis soal dalam buku siswa matematika kurikulum 2013 kelas VIII semester I berdasarkan dimensi kognitif dari TIMSS. Jurnal Review Pembelajaran Matematika, 1(1), 86–98. https://doi.org/10.15642/jrpm.2016.1.1.86-98
  4. Campos, T. M. M., da Silva, C. B., & Cazorla, I. M. (2008). Statistical literacy in Brazil in high and middle school: An analysis of official documents. In C. Batanero, G. Burrill, C. Reading, & A. Rossman (Eds.), Proceedings of the ICMI Study 18 and 2008 IASE Round Table Conference. https://iase-web.org/documents/papers/rt2008/T1P6_Campos.pdf?1402524989
  5. Charalambous, C., Delaney, S., Hsu, H.-Y., & Mesa, V. (2010). A comparative analysis of the addition and subtraction of fractions in textbooks from three countries. Mathematical Thinking and Learning, 12, 117–151. https://doi.org/10.1080/10986060903460070
  6. Chick, H. L., Pfannkuch, M., & Watson, J. M. (2005). Transnumerative thinking: Finding and telling stories within data. Curriculum Matters, 1, 87–108. https://doi.org/10.18296/cm.0063
  7. Engel, J. (2017). Statistical literacy for active citizenship: A call for data science education. Statistics Education Research Journal, 16(1), 44–49. https://doi.org/10.52041/serj.v16i1.213
  8. Garfield, J., & DelMas, R. (2010). A web site that provides resources for assessing students’ statistical literacy, reasoning and thinking. Teaching Statistics, 32(1), 2–7. https://doi.org/https://doi.org/10.1111/j.1467-9639.2009.00373.x
  9. Giani, Zulkardi, & Hiltrimartin, C. (2015). Analisis tingkat kognitif soal-soal buku teks matematika kelas VII berdasarkan taksonomi Bloom. Jurnal Pendidikan Matematika, 9(2), 78–98. https://doi.org/10.22342/jpm.9.2.2125.78 - 98
  10. Hardin, J., Hoerl, R., Horton, N. J., Nolan, D., Baumer, B., Hall-Holt, O., Murrell, P., Peng, R., Roback, P., Temple Lang, D., & Ward, M. D. (2015). Data science in statistics curricula: Preparing students to “think with data.” The American Statistician, 69(4), 343–353. https://doi.org/10.1080/00031305.2015.1077729
  11. Jatisunda, M. G., Nahdi, D. S., & Suciawati, V. (2020). Kemampuan Literasi Statistika Mahasiswa Adminitrasi Publik. SJME (Supremum Journal of Mathematics Education), 4(2), 134–146. https://doi.org/10.35706/sjme.v4i2.3488
  12. Jones, D. L., & Basyal, D. (2019). An analysis of the statistics content in Nepali school textbooks. Mathematics Education Forum Chitwan, 4(4), 21–34. https://doi.org/10.3126/mefc.v4i4.26356
  13. Jones, D. L., Brown, M., Dunkle, A., Hixon, L., Yoder, N., & Silbernick, Z. (2015). The statistical content of elementary school mathematics textbooks. Journal of Statistics Education, 23(3), 1–22. https://doi.org/10.1080/10691898.2015.11889748
  14. Jones, D. L., & Jacobbe, T. (2014). An analysis of the statistical content in textbooks for prospective elementary teachers. Journal of Statistics Education, 22(3), 1–12. https://doi.org/10.1080/10691898.2014.11889713
  15. Jones, G. A., Thornton, C., Langrall, C., Mooney, E., Perry, B., & Putt, I. (2000). A framework for characterizing children’s statistical thinking. Mathematical Thinking and Learning, 2(4), 269–307. https://doi.org/10.1207/S15327833MTL0204_3
  16. Khaerunnisa, E., & Pamungkas, A. S. (2017). Profil kemampuan literasi statistis mahasiswa jurusan pendidikan matematika Universitas Sultan Ageng Tirtayasa. AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 6(2), 246–255. https://doi.org/10.24127/ajpm.v6i2.970
  17. Marriott, J., Davies, N., & Gibson, L. (2009). Teaching, learning and assessing statistical problem solving. Journal of Statistics Education, 17(1), 1–18. https://doi.org/10.1080/10691898.2009.11889503
  18. Montoya, S. (2018). Defining literacy. GAML Fifth Meeting. https://gaml.uis.unesco.org/wp-content/uploads/sites/2/2018/12/4.6.1_07_4.6-defining-literacy.pdf
  19. Peres, R. S., Dionisio Rocha, A., Leitao, P., & Barata, J. (2018). IDARTS – Towards intelligent data analysis and real-time supervision for industry 4.0. Computers in Industry, 101, 138–146. https://doi.org/10.1016/j.compind.2018.07.004
  20. Pickle, M. C. C. (2012). Statistical content in middle grades mathematics textbooks. https://digitalcommons.usf.edu/etd
  21. Porciúncula, M., Samá, S., de Arimatéa Rocha, C., & de Carvalho, J. I. F. (2018). Every citizen needs to know statistics! What are we doing? Brazilian research in statistics education. In A. J. Ribeiro, L. Healy, R. E. de S. R. Borba, & S. H. A. A. Fernandes (Eds.), Mathematics Education in Brazil : Panorama of Current Research (pp. 249-263). Springer International Publishing. https://doi.org/10.1007/978-3-319-93455-6_13
  22. Purnama, A., Wijaya, T., Dewi, S., & Zulfah, Z. (2020). Analisis buku siswa matematika SMA dari Indonesia dan China pada materi peluang dan statistik. Jurnal Cendekia : Jurnal Pendidikan Matematika, 4, 813–822. https://doi.org/10.31004/cendekia.v4i2.305
  23. Reys, B. J., Reys, R. E., & Chavez, O. (2004). Why mathematics textbooks matter. Educational Leadership, 61(5), 61–66. https://www.researchgate.net/publication/234571079
  24. Roh, Y., Heo, G., & Whang, S. E. (2021). A survey on data collection for machine learning: A big data - AI integration perspective. IEEE Transactions on Knowledge and Data Engineering, 33(4), 1328–1347. https://doi.org/10.1109/TKDE.2019.2946162
  25. Ross, S. M. (2010). Introductory Statistics. In S. M. Ross (Ed.), Introductory Statistics (Third Edition). Academic Press. https://doi.org/10.1016/B978-0-12-374388-6.00019-3
  26. Schield, M. (2004). Statistical Literacy Curriculum Design. www.StatLit.org/pdf/2004SchieldIASE.pdf
  27. Setiawan, E. P. (2019). Analisis muatan literasi statistika dalam buku teks matematika Kurikulum 2013. Pythagoras: Jurnal Pendidikan Matematika, 14(2), 163–177. https://doi.org/10.21831/pg.v14i2.28558
  28. Setiawan, E. P. (2020). Introducing statistical inference to senior high school students: a textbook analysis. Journal of Physics: Conference Series, 1663(1), 012014. https://doi.org/10.1088/1742- 6596/1663/1/012014
  29. Setiawan, E. P., & Sukoco, H. (2021). Exploring first year university students’ statistical literacy: A case on describing and visualizing data. Journal on Mathematics Education, 12(3), 427–448. https://doi.org/10.22342/JME.12.3.13202.427-448
  30. Shaughnessy, J. M. (2007). Research on statistical learning and reasoning. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 957–1009). Information Age Publishing.
  31. Shaughnessy, J. M., & Pfannkuch, M. (2002). How faithful is Old Faithful? Statistical thinking: A story of variation and prediction. The Mathematics Teacher, 95(4), 252–259. https://doi.org/10.5951/MT.95.4.0252
  32. Shield, M., & Dole, S. (2013). Assessing the potential of mathematics textbooks to promote deep learning. Educational Studies in Mathematics, 82(2), 183–199. https://doi.org/10.1007/s10649- 012-9415-9
  33. Sotos, A. E. C., Vanhoof, S., Van den Noortgate, W., & Onghena, P. (2007). Students’ misconceptions of statistical inference: A review of the empirical evidence from research on statistics education. Educational Research Review, 2(2), 98–113. https://doi.org/10.1016/j.edurev.2007.04.001
  34. Thompson, D., Senk, S., & Johnson, G. (2012). Opportunities to learn reasoning and proof in high school mathematics textbooks. Journal for Research in Mathematics Education, 43, 253–295. https://doi.org/10.5951/jresematheduc.43.3.0253
  35. Toasa, R., Maximiano, M., Reis, C., & Guevara, D. (2018). Data visualization techniques for real-time information — A custom and dynamic dashboard for analyzing surveys’ results. 2018 13th Iberian Conference on Information Systems and Technologies (CISTI), 1–7. https://doi.org/10.23919/CISTI.2018.8398641
  36. Tran, D., & Tarr, J. E. (2018). Examination of bivariate data tasks in US high school textbooks through the statistical investigation and cognitive demands frameworks. International Journal of Science and Mathematics Education, 16(8), 1581–1603. https://doi.org/10.1007/s10763-017-9851-1
  37. Vanhoof, S., Castro Sotos, A. E., Onghena, P., Verschaffel, L., Van Dooren, W., & Van den Noortgate, W. (2006). Attitudes toward statistics and their relationship with short-and long-term exam results. Journal of Statistics Education, 14(3), null-null. https://doi.org/10.1080/10691898.2006.11910588
  38. Walker, H. M. (1951). Statistical literacy in the social sciences. The American Statistician, 5(1), 6–12. https://doi.org/10.1080/00031305.1951.10481912
  39. Weiland, T. (2017). Problematizing statistical literacy: An intersection of critical and statistical literacies. Educational Studies in Mathematics, 96(1), 33–47. https://doi.org/10.1007/s10649- 017-9764-5
  40. Yang, D. C., Tseng, Y. K., & Wang, T. L. (2017). A comparison of geometry problems in middle-grade mathematics textbooks from Taiwan, Singapore, Finland, and the United States. Eurasia Journal of Mathematics, Science and Technology Education, 13(7), 2841–2857. https://doi.org/10.12973/eurasia.2017.00721a
  41. Yanık, H. B., Özdemir, G., & Çevirgen, A. (2017). Ortaokul matematik ders kitaplarında yer alan veri işlemeye yönelik görevlerin incelenmesi. İnönü Üniversitesi Eğitim Fakültesi Dergisi, 18(2), 45–61. https://doi.org/10.17679/inuefd.323407
  42. Yaqoob, I., Hashem, I. A. T., Gani, A., Mokhtar, S., Ahmed, E., Anuar, N. B., & Vasilakos, A. V. (2016). Big data: From beginning to future. International Journal of Information Management, 36(6, Part B), 1231–1247. https://doi.org/10.1016/j.ijinfomgt.2016.07.009

Similar Articles

1 2 3 > >> 

You may also start an advanced similarity search for this article.