R&D: Cumulative Learning using Embedded Assessment Results (CLEAR)

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• 批准号: 0822388
• 负责人: Marcia Linn
• 金额: $ 359.98万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0822388&HistoricalAwards=false
• 关键词: R& Cumulative; Learning; using; Embedded

Cumulative Learning using Embedded Assessment Results (CLEAR) focuses on the challenge of using assessment of relevant STEM content to improve K-12 teaching and learning. CLEAR takes advantage of new technologies and research findings to investigate ways that science assessments can both capture and contribute to cumulative, integrated learning of standards-based concepts in middle school courses. The project will research new forms of assessment that document students' accumulation of knowledge and also serve as learning events. CLEAR will use cohort and randomized classroom comparisons to determine what combinations of instruction and assessment enable middle school students to gain cumulative understanding of energy concepts in science. CLEAR will study whether the project's approach when used in one course impacts progress in the next. The project will put design principles from across the field to the test by determining which instruction and assessment strategies encourage cumulative understanding and help learners develop integrated ideas about science.Intellectual Merit. There is an urgent need to develop accurate student assessments that measure cumulative knowledge while eliminating the disruptions caused by tests. By measuring students' developing understanding and ongoing efforts to make sense of new materials, the project will be able to foster coherent understanding. The project will do this by making assessment an integral part of computer-based curricula.Broader Impacts. By aligning assessment and instruction around the goal of promoting understanding, the project will demonstrate how to improve learning outcomes for any STEM course. The project will also make courses more effective and efficient by converting assessment from a time-wasting, curriculum-limiting chore into an integral part of learning that fosters the accumulation of concepts across topics and grades. The results of the proposed research will have an important bearing on the design of effective electronic media on promoting student learnig. The project is designed to have a major impact by undertaking the kind of careful, statistically valid research design that leads to reproducible results that can support policy. The project will be able to tailor instruction to specific learners, increasing the impact on students at risk for failure. The partners will continue their practice of widely dissemi-nating findings, materials, and open source software through reviewed papers, popular articles, talks, workshops, a website, and newsletters. The project is led by Marcia C. Linn, Robert Tinker, Kathy Benemann, Hee Sun Lee, Ou Lydia Liu, & James Slotta

使用嵌入式评估结果（清晰）的累积学习重点是使用相关STEM含量评估来改善K-12教学的挑战。明确利用新技术和研究结果来研究科学评估既可以捕捉并促进基于标准的中学课程概念的累积，综合学习的方法。该项目将研究新的评估形式，以记录学生的知识积累，并作为学习事件。 Clear将使用队列和随机的课堂比较来确定哪些教学和评估的组合使中学生能够累积对科学能量概念的理解。 Clear将研究项目在一门课程中使用的方法是否会影响下一步的进度。该项目将通过确定哪种指导和评估策略鼓励累积理解并帮助学习者发展有关科学的综合思想。迫切需要制定准确的学生评估，以衡量累积知识，同时消除测试引起的中断。通过衡量学生发展新材料的理解和持续的努力，该项目将能够促进连贯的理解。该项目将通过使评估成为基于计算机的课程的组成部分来实现这一目标。通过围绕促进理解目标的评估和指导，该项目将演示如何改善任何STEM课程的学习成果。该项目还将通过从浪费时间，限制课程的琐事转换为学习组成部分的评估来提高课程，从而促进跨主题和等级的概念的积累。拟议研究的结果将与有效电子媒体的设计有关促进学生学习的设计具有重要意义。 该项目旨在通过采取那种仔细的，统计上有效的研究设计来产生重大影响，从而导致可重现的结果可以支持政策。该项目将能够为特定的学习者量身定制教学，从而增加对有失败风险的学生的影响。合作伙伴将通过审核，流行的文章，演讲，研讨会，网站和新闻通讯来继续他们的实践，以广泛的传播发现，材料和开源软件。该项目由Marcia C. Linn，Robert Tinker，Kathy Benemann，Hee Sun Lee，Ou Lydia Liu和James Slotta领导