工作(物理)
选择(遗传算法)
过程(计算)
管理科学
社会学
公共关系
心理学
计算机科学
知识管理
政治学
机械工程
操作系统
工程类
人工智能
经济
作者
Ellen B. Mandinach,Kim Schildkamp
标识
DOI:10.1016/j.stueduc.2020.100906
摘要
This special issue explores the complexity and interconnectedness of the many components of data-based decision making. The selection of papers represents many countries (i.e., Belgium, The Netherlands, New Zealand, Norway, and the United States), theories, methods, and foci. All the papers seek to explicate how data are used at the different level of the system, ranging from students, teachers, schools, and districts. Together these papers offer a view of the current data-based decision making landscape, including in- and pre-service professional development, district and school organizational capacity, the data use process (from goal setting to collaborative instructional decision making), and effects on student achievement. The intent of the special issue is to stimulate future work in terms of impact on research, theory, policy, and practice.
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