Collaborative Research: Modeling Assessment to Enhance Teaching and Learning

协作研究：评估建模以加强教学

• 批准号: 1621265
• 负责人: Mark Wilson
• 金额: $ 97.5万
• 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: 2016
• 资助国家: 美国
• 起止时间: 2016-12-01 至 2022-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1621265&HistoricalAwards=false
• 关键词: Collaborative; Research; Modeling; Assessment; Enhance

Although many in education advocate for evidence-based teaching, implementation of such practices is often quite difficult for teachers. Assessment and accountability data are commonly used for system-level reforms, but are seldom designed to help teachers guide day-to-day instructional decision-making. More useful assessment systems should deliver actionable information to assist in guiding instructional decisions, communicate the development of student knowledge, and integrate various forms of data to assist teachers. Such systems must be logistically feasible to implement, provide suitable grounds for interpreting information about achievement, and exist in a teacher community interested in ongoing feedback about student learning.This project will modify an existing assessment system (BEAR Assessment System) to provide ongoing, instructionally productive evidence to teachers about student learning and to link student work products and formative assessments with summative assessments in models that generate useful estimates of student growth. To design and test the assessment system, researchers will study teacher integration of assessment tools with instruction via classroom observations, video records, and interviews. Feedback from teachers and observations of their assessment practices will inform revisions to the assessment system. Multiple iterations will focus on how best to represent and display assessment results for tracking individual and group learning. Researchers will investigate new psychometric models that link information from student classroom work, responses to formative assessments, and summative evaluations to provide more reliable estimates of student learning.The Discovery Research PreK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools (RMTs). Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.

尽管许多教育倡导循证教学的倡导者，但对于教师来说，实施这种做法通常很难。评估和问责制数据通常用于系统级改革，但很少旨在帮助教师指导日常的教学决策。更有用的评估系统应提供可行的信息，以帮助指导教学决策，传达学生知识的发展以及整合各种形式的数据以帮助教师。这种系统在逻辑上必须是可行的，才能实施，为解释有关成就的信息提供适当的理由，并存在于对持续的有关学生学习的反馈感兴趣的教师社区中。该项目将修改现有的评估系统（熊评估系统），以向教师提供有关学生学习的持续，教学生产性的证据，并将学生学习产品和组成的成长性评估与学生的成长相关联。为了设计和测试评估系统，研究人员将通过课堂观察，视频记录和访谈来研究评估工具的教师整合。教师的反馈和对评估实践的观察将为评估系统的修订提供信息。多次迭代将集中于如何最好地代表和显示跟踪个人和小组学习的评估结果。 Researchers will investigate new psychometric models that link information from student classroom work, responses to formative assessments, and summative evaluations to provide more reliable estimates of student learning.The Discovery Research PreK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools (RMTs). DRK-12计划中的项目基于STEM教育和先前的研发工作的基础研究，这些研究为拟议项目提供了理论和经验的理由。