权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Collaborative Research: Modeling Assessment to Enhance Teaching and Learning

协作研究：评估建模以加强教学

基本信息

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

项目摘要

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.

虽然许多教育界人士提倡循证教学，但教师往往很难实施这种做法。评估和问责数据通常用于系统层面的改革，但很少用于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，以帮助指导教学决策，沟通学生知识的发展，并整合各种形式的数据，以帮助教师。这样的系统必须在逻辑上可行的实施，提供适当的理由来解释有关成就的信息，并存在于对学生学习的持续反馈感兴趣的教师群体中。（BEAR评估系统）提供持续的，为教师提供关于学生学习的有效证据，并将学生作业产品和形成性评估与总结性评估联系起来这些模型可以对学生的成长做出有用的估计。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评估工具与教学的整合。教师的反馈和对他们的评估做法的观察将为评估制度的修订提供信息。多个迭代将集中于如何最好地表示和显示评估结果，以跟踪个人和小组的学习。研究人员将调查新的心理测量模型，这些模型将学生课堂作业的信息、对形成性评估的反应和总结性评估联系起来，以提供更可靠的学生学习评估。发现研究PreK-12项目（DRK-12）旨在显著提高PreK-12学生和教师对科学、技术、工程和数学（STEM）的学习和教学，通过研究和开发创新资源、模型和工具（RMT）。DRK-12计划中的项目建立在STEM教育的基础研究和先前的研究和开发工作的基础上，这些研究和开发工作为拟议项目提供了理论和经验依据。