Published 2022-12-21
Keywords
- Análisis de datos,
- educación superior,
- razonamiento estadístico,
- transnumeración
- Data analysis,
- higher education,
- statistical reasoning,
- transnumeration
How to Cite
Copyright (c) 2022
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Abstract
Transnumeration, as a type of statistical reasoning, allows the nature of statistical data to be assessed from different perspectives, the most suitable types of analysis according to the purposes of a study, as well as the representations that communicate the results of an investigation to different users and its many implications. This paper presents the results of an interview conducted with a postgraduate student in the area of Education, to identify the different transnumeration strategies used and their meaning, in the performance of different statistical analyses. An adaptation of the task-centered interview technique was made, which was based on the analysis plan defined by the student for her thesis work, and from this plan, with the help of the interviewer, different transnumerative alternatives were explored. Among the most relevant results, we have that the different transnumerative techniques used by the student interviewed allowed her to reevaluate the nature of the variables considered in her analysis and the possibilities of transforming them. The interviewee also had the opportunity to review and reinforce the original criteria of her analysis plan and the underlying statistical principles. It is concluded that the statistical reasoning implemented through transnumeration must be flexible and allow the exploration of different possibilities of analysis and representation, which assist the potentialization of the results of an investigation. The importance of transnumerative thinking is highlighted as a factor that allows to link the different stages of the research cycle conceptually and operationally.
References
- Alonso-Arroyo, A., Spotti Lopes Fujita, M., Gil-Leiva, I., y Pandiella, A. (2016). Protocolo verbal: análisis de la producción científica, 1941-2013. Informação & Sociedade, 26(2), 61-76.
- Burrill, G., y Biehler, R. (2011). Fundamental statistical ideas in the school curriculum and in training teachers. En C. Batanero, G. Burril y C. Reading (eds.), Teaching Statistics in school Mathematics-Challenges for teaching and teacher education: A joint ICMI/IASE study (pp. 57-69). Springer.
- BA [British Academy for the Humanities and Social Sciences] (2015). Count us in: Quatitative skills for a new generation.
- Cazorla, I. M., Cardoso Utsumi, M., y Ferreira Monteiro, C. E. (2021). Dos dados brutos à informação: o papel das técnicas transnumerativas no ensino de Estatística. Educação Matemática Pesquisa, 23(4), 109-139.
- Chick, H. L. (2004). Tools for transnumeration: Early stages in the art of data representation. En I. Putt, R. Faragher y M. McLean (eds.), Mathematics education for the third millennium: Towards 2010. Proceedings of the Twenty-seventh Annual Conference of the Mathematics Education Research Group of Australasia (pp. 167-174). MERGA.
- Chick, H. L., Pfannkuch, M., y Watson, J. M. (2005). Transnumerative thinking: Finding and telling stories within data. Curriculum Matters, (1), 86-108.
- Eudave Muñoz, D. (2007). El aprendizaje de la estadística en estudiantes universitarios de profesiones no matemáticas. Educación Matemática, 19(2), 41-66.
- Garfield, J., y Ben-Zvi, D. (2007). How students learn Statistics revisited: A current review of tesearch on teaching and learning Statistics. International Statistical Review, 75(3), 372-396.
- Goldin, G. A. (2000). A scientific perspective on structured, task-based interviews in Mathematics educational research. En A. E. Kelly y R. A. Lesh, Handbook of research design in Mathematics and Science education (pp. 517-545). Lawrence Erlbaum Associates.
- Kerlinger, F. N., y Lee, H. B. (2002). Investigación del comportamiento. McGraw-Hill.
- Maher, C. A., y Sigley, R. (2014). Task-based interviews in Mathematics education. En S. Lerman (ed.), Encyclopedia of Mathematics education. Springer.
- Ramos, L. (2019). La educación estadística en el nivel universitario: retos y oportunidades. Revista Digital de Investigación en Docencia Universitaria, 13(2), 67-82.
- Salcedo, A., González, J., y González, J. (2021). Lectura e interpretación de gráficos estadísticos, ¿cómo lo hace el ciudadano? Revista Paradigma, 42(ext.1), 61-88.
- Wild, C. J., y Pfannkuch, M. (1999). Statistics thinking in empirical enquiry. International Statistical Review, 67(3), 223-265.