Using Eurostat data to teach statistics to prospective primary teachers: on how the context of the task may promote their social awareness

Author:

Ubilla Francisca M.ORCID,Gorgorió NúriaORCID

Abstract

AbstractThe concept of statistical sense provides an understanding of the goals of statistics education and helps to clarify the design of activities that promote the development of statistical literacy, reasoning and thinking. The new approaches to statistics in schools mean special attention must be paid to teacher training. This training should enable them to develop their statistical sense while awakening their social awareness. Drawing on the idea of the cycle of learning from data, we developed an activity based on data extracted from EUROSTAT, with the goal being to find out how the social issues underlying the data might play a role in the development of a socially critical stance among prospective teachers. We also wanted to find out how the complexity of the data presented might interfere with a satisfactory resolution of the cycle of learning from data. In general, we observed that when the data were socially relevant and closely related to their interests, the activity generated opportunities for the development of their social awareness. However, the development of the cycle may have been constrained by the difficulties they encountered when handling data with characteristics typical of civic statistics. We conclude that not all the contexts that accompany the cycle of learning from data promote social awareness in the same way and that the data representations associated with the cycle must be aligned with the prospective teachers’ prior statistical knowledge.

Funder

Ministerio de Ciencia, Innovación y Universidades

Agencia Nacional de Investigación y Desarrollo

Ministerio de Ciencia e Innovación

Universitat Autònoma de Barcelona

Publisher

Springer Science and Business Media LLC

Subject

General Mathematics,Education

Reference38 articles.

1. Arnold (2013). Statistical Investigative Questions - An Enquiry into Posing and Answering Investigative Questions from Existing Data [Doctoral Thesis]. University of Auckland. https://researchspace.auckland.ac.nz/handle/2292/21305.

2. Arnold, P., & Franklin, C. (2021). What makes a good statistical question? Journal of Statistics and Data Science Education, 29(1), 122–130. https://doi.org/10.1080/26939169.2021.1877582

3. Bargagliotti, A., Franklin, C., Arnold, P., Gould, R., Johnson, S., Perez, L., & Spangler, D. (2020). Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II): A Framework for Statistics and Data Science Education. American Statistical Association. Retrieved from https://www.amstat.org/asa/files/pdfs/GAISE/GAISEIIPreK-12_Full.pdf

4. Cobb, G. W., & Moore, D. S. (1997). Mathematics, statistics, and teaching. The American Mathematical Monthly, 104(9), 801–823. https://doi.org/10.2307/2975286

5. Cohen, L., Manion, L., & Morrison, K. (2007). Research methods in education (6th ed.). Routledge Falmer.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3