COLLABORATIVE RESEARCH: WIDER: Improving Undergraduate Education Through Community Building and Adoption of an Evidence-based Practice to Evaluate Undergraduate Research

合作研究：更广泛：通过社区建设和采用循证实践来评估本科研究来改善本科教育

• 批准号: 1347681
• 负责人: Jill Singer
• 金额: $ 65.9万
• 依托单位: SUNY College at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1347681&HistoricalAwards=false
• 关键词: COLLABORATIVE; RESEARCH; WIDER; Improving; Undergraduate

This project is testing, refining, and disseminating a promising evidence-based model for guiding effective undergraduate research. The model is based on five years of data. Additional testing and refinement activity are underway to ensure applicability across diverse institutional settings. The project will create and provide the resources needed to support successful implementation at any undergraduate institution. Through collaborations with the Council on Undergraduate Research (CUR) and the Science Education Resource Center SERC) at Carleton College, the project intends to foster national communities of STEM scholars who are trained and motivated to sustain and expand this model. The model is designed to ensure that the student learning outcomes from participation in undergraduate research are as strong as possible. It deliberately generates formative guidance during the research through a series of quantitative, built-in formative evaluations conducted over the duration of each research experience. Evaluation is a central component of this model. The model emphasizes multiple progress assessments by both faculty and students across a wide range of desirable outcomes, so that the evaluation process provides essential information used by both students and faculty to advance learning objectives. The design approach transcends specific STEM disciplines. This transcendent feature offers an opportunity to aggregate impact results across a series of undergraduate research experiences. The model's built-in evaluation feature will provide summary data on student learning that could be used to inform resource allocation decisions.

该项目正在测试，完善和传播一个有前途的基于证据的模型，以指导有效的本科研究。 该模型基于五年的数据。 正在进行其他测试和精炼活动，以确保各种机构环境的适用性。该项目将创建并提供支持任何本科机构成功实施所需的资源。 通过与卡尔顿学院（Carleton College）的科学教育资源中心（CUR）和科学教育资源中心委员会的合作，该项目打算培养经过培训和动力维持和扩展这种模型的STEM学者社区。 该模型旨在确保学生对本科研究的学习成果尽可能强大。它通过在每种研究经验的持续时间内进行的一系列定量，内置的形成性评估，故意在研究期间产生形成性指导。评估是该模型的核心组成部分。该模型强调教师和学生在广泛理想的结果中的多次进步评估，因此评估过程提供了学生和教师使用的基本信息，以提高学习目标。 设计方法超越了特定的茎学科。 这项超然功能提供了一个机会，可以在一系列本科研究经验中汇总影响结果。 该模型的内置评估功能将提供有关学生学习的摘要数据，可用于为资源分配决策提供信息。