文章基本信息

标题：The Use of Algorithmic Models to Develop Secondary Teachers’ Understanding of the Statistical Modeling Process
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作者：Andrew Zieffler ; Nicola Justice ; Robert delMas 等
期刊名称：Journal of Statistics Education
电子版ISSN：1069-1898
出版年度：2021
卷号：29
期号：1
页码：131-147
DOI：10.1080/26939169.2021.1900759
出版社：American Statistical Association
摘要：Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers’ preparation for and experiences teaching statistical modeling have focused on probabilistic models. Subsequently, much of the research literature related to the teachers’ understanding has focused on probabilistic models. This study explores the extent to which secondary statistics teachers appear to understand ideas of statistical modeling, specifically the processes of model building and evaluation, when introduced using classification trees, a type of algorithmic model. Results of this study suggest that while teachers were able to read and build classification tree models, they experienced more difficulty when evaluating models. Further research could continue to explore possible learning trajectories, technology tools, and pedagogical approaches for using classification trees to introduce ideas of statistical modeling.
关键词：Algorithmic models ; Classification trees ; Data science education ; Statistics education research ; Statistical modeling ; Teacher development