论证(复杂分析)
学习科学
课程
学习理论
数学教育
概念学习
计算机科学
科学的本质
主动学习(机器学习)
心理学
科学教育
数据科学
体验式学习
人工智能
教育学
化学
生物化学
作者
Christopher Smith,Marianne Wiser,Charles Anderson,Joseph Krajcik
标识
DOI:10.1080/15366367.2006.9678570
摘要
The purpose of this article is to suggest ways of using research on children's reasoning and learning to elaborate on existing national standards and to improve large-scale and classroom assessments. The authors suggest that learning progressions—descriptions of successively more sophisticated ways of reasoning within a content domain based on research syntheses and conceptual analyses—can be useful tools for using research on children's learning to improve assessments. Such learning progressions should be organized around central concepts and principles of a discipline (i.e., its big ideas) and show how those big ideas are elaborated, interrelated, and transformed with instruction. They should also specify how those big ideas are enacted in specific practices that allow students to use them in meaningful ways, enactments the authors describe as learning performances. Learning progressions thus can provide a basis for ongoing dialogue between science learning researchers and measurement specialists, leading to the development of assessments that use both standards documents and science learning research as resources and that will give teachers, curriculum developers, and policymakers more insight into students' scientific reasoning. The authors illustrate their argument by developing a learning progression for an important scientific topic—matter and atomic-molecular theory—and using it to generate sample learning performances and assessment items.
科研通智能强力驱动
Strongly Powered by AbleSci AI