READING AND WRITING THE WORLD WITH CHILDREN: STATISTICAL THINKING AND MULTIVARIATE DATA

Authors

  • ROBERTA SCHNORR BUEHRING Universidade Federal de Santa Catarina UFSC
  • REGINA CÉLIA GRANDO Universidade Federal de Santa Catarina - UFSC https://orcid.org/0000-0002-2775-0819

DOI:

https://doi.org/10.52041/serj.v22i2.446

Keywords:

Statistical Education; Civic Statistics; Multivariate data; Childhood

Abstract

This article reports on research in which a teacher and researcher from a Brazilian public school conducts civic statistics teaching practices with multivariate data, based on Engel’s (2017) and on Freire’s (1989) reading of the world. The research with seven- and eight-year-old children illustrates the complexity of statistical thinking that starts from examining real data from the virtual comparison tool Dollar Street on how people live in the world. The aim is to understand how children invest in a multivariate dataset of images, texts, coded symbols, and locations to draw conclusions about reality. During the progression of the research, the broader issue of promoting the learning and use of statistical language was encountered. The outcomes highlight the potential for using multivariate data from meaningful contexts and personal experiences to expand children’s awareness of themselves and of the world through statistics.

References

Ben-Zvi, D. (2018). Foreword. In A. Leavy, M. Meletiou-Mavrotheris & E. Paparistodemou (Eds.), Statistics in early childhood and primary education: Supporting early statistical and probabilistic thinking (pp. vii–viii). Springer. https://doi.org/10.1007/978-981-13-1044-7

Brandt, D. (2009). Writing over reading: New directions in mass literacy. In M. Baynham & M. Prinsloo (Eds), The future of literacy studies (pp. 54–74). Palgrave Macmillan. https://doi.org/10.1057/9780230245693_2

Buehring, R. S. (2021). Movimentos de Pensamento Estatístico na Infância: entre viver e contar histórias. 296 f. Tese (Doutorado) - Curso de Educação Científica e Tecnológica, CED, Universidade Federal de Santa Catarina, Florianópolis, 2021

Cochran-Smith, M., & Lytle, S. L. (1999). Relationships of knowledge of practice: Teacher learning in communities. Review of Research in Education, 24, 249–305. https://doi.org/10.2307/1167272

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

Engel, J., & Ridgway, J. (2022). Back to the future: Rethinking the purpose and nature of statistics education. In J. Ridgway (Ed.), Statistics for empowerment and social engagement: Teaching civic statistics to develop informed citizens (pp. 17–36). Springer.

Figgou, L., & Pavlopoulos, V. (2015). Social psychology: Research methods. In J. D. Wright (Ed.), International Encyclopedia of the Social & Behavioral Sciences (2nd ed., pp. 544–552). Elsivier

Freire, P. (1987). Pedagogia do oprimido (17th ed.). Paz e Terra.

Freire, P. (1989). A importância do Ato de Ler: em três artigos que se completam (23rd ed.). Cortez.

Freire, P. (1997). Professora sim, tia não: Cartas a quem ousa ensinar. Olho d’água.

Gal, I. (2002). Adult’s statistical literacy: Meanings, components, responsibilities. International Statistical Review, 70(1). https://doi.org/10.2307/1403713

Gapminder. (2020). Banco de Dados [Dollar Street]. https://www.gapminder.org/dollar-street/matrix

Garfield, J. (2002). The challenge of developing statistical reasoning. Journal of Statistics Education, 10(3). https://doi.org/10.1080/10691898.2002.11910676

Gaviria Rojas, W. A., Diamos, A. S., Kini K. J., Kanter, D. & Reddi, V. J. (2022). The Dollar Street dataset: Images representing the geographic and socioeconomic diversity of the world. In Track on Datasets and Benchmarks. Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS 2022). https://openreview.net/pdf?id=qnfYsave0U4

Higgins, C. (2018). Schwab’s challenge and the unfulfilled promise of action research. In P. Smeyers & M. Depaepe (Eds.), Educational research: Ethics, social justice, and funding dynamics (pp. 163–173). Springer.

hooks, b. (2020). Ensinando pensamento crítico: Sabedoria prática. Editora Elefante.

Kazak, S., Fujita, T., & Pifarre Turmo, M. P. (2023). Students’ informal statistical inferences through data modeling with a large multivariate dataset. Mathematical Thinking and Learning, 25(1), 23–43. https://doi.org/10.1080/10986065.2021.1922857

Konold, C., Higgins, T., Russell, S. J., & Khalil, K. (2015). Data seen through different lenses. Educational Studies in Mathematics, 88, 305–325. https://doi.org/10.1007/s10649-013-9529-8

Makar, K., Fry, K., & English, L. (2023). Primary students’ learning about citizenship through data science. ZDM–Mathematics Education. https://doi.org/10.1007/s11858-022-01450-7

Rinehart, R. E., Barbour, K. N., & Pope, C. C. (2014). Proem: Engaging contemporary ethnography across the disciplines. In R. E. Rinehart, K. N. Barbour, & C. C. Pope (Eds.), Ethnographic worldviews: Transformations and social justice (pp. 1–11). Springer.

Rosling, H., Rosling, O., & Rönnlund, A. R. (2020). Factfulness: o hábito libertador de só ter opiniões baseadas em fatos (4th ed.). Record.

Siegle, D. (2021). When pictures are worth a 1,000 words: Addressing global stereotypes with Dollar Street. Gifted Child Today, 44(2), 107–110. https://doi.org/10.1177/1076217520988776

Soares, M. (2004). Letramento: um tema em três gêneros. Autentica Editora.

Souza, de Oliveira L., Lopes, C., & Fitzallen, N. (2020). Creative insubordination in statistics teaching: Possibilities to go beyond statistical literacy. Statistics Education Research Journal, 19(1), 73–91. https://doi.org/10.52041/serj.v19i1.120

Street, B. V. (1997). Social literacies. Encyclopedia of language and education: Literacy, Volume 2 Literacy (pp–141). https://doi.org/10.1007/978-94-011-4540-4_15

Street, B. V. (2013). Políticas e práticas de letramento na Inglaterra: uma perspectiva de letramentos sociais como base para uma comparação com o Brasil. Caderno Cedes, Campinas, v. 33, n. 89, p. 51-71, jan.-abr. 2013. http://www.cedes.unicamp.br

Szwarcwald, C. L., Boccolini, C. S., da Silva de Almeida, W., Filho, A. M. S, & Malta, D. C.(2022). COVID-19 mortality in Brazil, 2020–21: Consequences of the pandemic inadequate management. Archives of Public Health, 80, Article 255. https://doi.org/10.1186/s13690-022-01012-z

Watson, J. (2006). Statistical literacy at school: Growth and goals. Lawrence Erlbaum. https://doi.org/10.1111/j.1751-5823.2007.00015_12.x

Watson, J. (2009). The influence of variation and expectation on the developing awareness of distribution. Statistics Education Research Journal, 8(1), 32–61. https://doi.org/10.52041/serj.v8i1.45622a22a

Downloads

Published

2023-07-31

Issue

Section

Early Statistical and Probabilistic Thinking