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.

尽管许多教育界人士提倡循证教学，但实施这种做法对教师来说往往相当困难。评估和问责数据通常用于系统级改革，但很少旨在帮助教师指导日常教学决策。更有用的评估系统应该提供可操作的信息，以协助指导教学决策，传达学生知识的发展，并整合各种形式的数据来帮助教师。此类系统必须在逻辑上可行，能够为解释成绩信息提供适当的依据，并且存在于对学生学习的持续反馈感兴趣的教师社区中。该项目将修改现有的评估系统（BEAR 评估系统），以提供持续的、指导性的评估向教师提供有关学生学习的有效证据，并将学生作业产品和形成性评估与模型中的总结性评估联系起来，从而生成对学生成长的有用估计。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教师将评估工具与教学相结合。教师的反馈和对其评估实践的观察将为评估系统的修订提供信息。多次迭代将重点关注如何最好地表示和显示评估结果以跟踪个人和小组学习。研究人员将研究新的心理测量模型，将学生课堂作业的信息、对形成性评估的反应以及总结性评估联系起来，以提供更可靠的学生学习评估。Discovery Research PreK-12 计划 (DRK-12) 旨在显着增强学生的学习和学习能力。通过研究和开发创新资源、模型和工具 (RMT)，由 preK-12 学生和教师教授科学、技术、工程和数学 (STEM)。 DRK-12 计划中的项目建立在 STEM 教育基础研究以及先前的研究和开发工作的基础上，为拟议项目提供理论和实证依据。