Transforming Curriculum and Building Capacity in K-12 Data Science Education

被引:9
作者
Weiland, Travis [1 ]
Engledowl, Christopher [1 ]
机构
[1] Univ Houston, Houston, TX 77004 USA
来源
HARVARD DATA SCIENCE REVIEW | 2022年 / 4卷 / 04期
关键词
data science education; data literacy; statistics education; teacher education; doctoral student education; educational policy; curriculum standards; PEDAGOGICAL CONTENT KNOWLEDGE; STATISTICAL LITERACY;
D O I
10.1162/99608f92.7fea779a
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The recently released and updated Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education (GAISE II; Bargagliotti et al., 2020) provides guidance as to how teachers can support the development of data literacy for all students in the pre-K-12 curriculum. However, to truly meet the vision of the GAISE II report and to support all students in developing data literacy for today's societies, significant transformations need to be made to the educational system as a whole to build capacity for such development. In this article we discuss the current state of the K-12 curriculum focusing on the mathematics curriculum where statistics and data concepts are most frequently situated, presenting some challenges and exciting examples. We then discuss areas of need for capacity building that must come at all levels, including: K-12 school curriculum, K-12 teacher professional development, K-12 teacher preparation, statistics and data science education research, and policies. We also provide a set of recommendations for building capacity to develop the data literacy of all students through the teaching of data science and statistics concepts and practices in the K-12 mathematics curriculum to support democratic equity through engaged citizenship.
引用
收藏
页数:20
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