Collaborative Research: Expanding a National Network for Automated Analysis of Constructed Response Assessments to Reveal Student Thinking in STEM

合作研究：扩大构建反应评估自动分析的国家网络，以揭示学生在 STEM 中的思维

• 批准号: 1322851
• 负责人: Michelle Smith
• 金额: $ 18.8万
• 依托单位: University of Maine
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2019-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1322851&HistoricalAwards=false
• 关键词: Collaborative; Research; Expanding; National; Network

This project is being conducted by a large team across 6 institutions that is building on already developed open-ended constructed response versions of well-established concept inventories that can be accurately assessed with already created computer automated analysis resources. The computer-automated analyses are able to predict human ratings of students' work on these topics and have demonstrated higher inter-rater reliability than a group of trained expert human graders. Constructed response assessments reveal more about student thinking and the persistence of misconceptions than do multiple-choice questions, but require more analysis on the part of the educator. In past work, items designed to identify important disciplinary constructs were created based on prior research. The items were then administered via online course management systems where students entered responses. Lexical and statistical analysis software was used to predict expert ratings of student responses. To date, the work has focused primarily in the fields of biology and chemistry in biological contexts. The current project is leveraging the previous research on Automated Assessment of Constructed Response (AACR), and extending the work to other institutions and other STEM disciplines. The specific goals of this project are to: 1. Create a community web portal for the Automated Assessment of Constructed Response (AACR) assessments to expand and deepen collaborations among STEM education researchers, thus providing the infrastructure for expanding the community of researchers and supporting the adoption and implementation of the innovative instructional materials by instructors at other institutions. 2. Propagate the innovations by providing instructors with professional development and long-term, ongoing support to use the assessments. This includes information about common student conceptions revealed by the questions, instructional materials for addressing conceptual barriers, and the opportunity to join a community of practitioners who are using the AACR questions and exchanging materials. 3. Expand the basic research to create and validate AACR questions in introductory chemistry, chemical engineering, and statistics. 4. Engage in ongoing project evaluation for continuous quality improvement and to document the challenges and successes the project encounters. 5. Lay the foundation for sustainability by providing interfaces for e-text publishers, Learning Management System vendors, and Massively Open Online Courses as potential revenue streams to operate and maintain the online infrastructure.Intellectual Merit:Improving STEM education requires valid and reliable instruments that provide insight into student thinking. The automated analysis of constructed response assessments have the potential to assess "big ideas" in STEM in a richer, more multi-faceted manner than multiple-choice instruments. This project is extending the number of these items and provide an online community where instructors may obtain, score, and contribute to the library of items and resources necessary for their analyses. Broader Impacts:The web portal is extending the use of the products created in this project to instructors nationwide. In addition it is providing the foundation for a national collaboration of science and engineering educators interested in developing deeper conceptual assessment tools and supports and mentors postdoctoral research fellows, and graduate research assistants in STEM education research.

这个项目是由一个跨越6个机构的大型团队进行的，他们建立在已经开发的开放式构建响应版本的完善概念清单上，这些清单可以用已经创建的计算机自动分析资源进行准确评估。计算机自动分析能够预测学生在这些主题上的工作的人类评分，并且已经证明了比一组训练有素的专家评分更高的评分者之间的可靠性。与多项选择题相比，建构反应评估更能揭示学生的思维和误解的持久性，但需要教育者进行更多的分析。在过去的工作中，旨在识别重要学科结构的项目是基于先前的研究创建的。这些项目随后通过在线课程管理系统进行管理，学生可以在其中输入回答。使用词汇和统计分析软件来预测专家对学生回答的评分。迄今为止，这项工作主要集中在生物学背景下的生物学和化学领域。目前的项目正在利用之前对构建反应自动评估（AACR）的研究，并将工作扩展到其他机构和其他STEM学科。该项目的具体目标是：1。为构建反应自动评估（AACR）评估创建一个社区门户网站，以扩大和深化STEM教育研究人员之间的合作，从而为扩大研究人员社区提供基础设施，并支持其他机构的教师采用和实施创新的教学材料。2. 通过为教师提供专业发展和长期持续的支持来推广创新。这包括通过问题揭示的学生的共同概念的信息，解决概念障碍的教学材料，以及加入使用AACR问题和交换材料的从业者社区的机会。3. 扩展基础研究，创建和验证入门化学、化学工程和统计学中的AACR问题。4. 参与正在进行的项目评估，以实现持续的质量改进，并记录项目遇到的挑战和成功。5. 通过为电子文本出版商、学习管理系统供应商和大规模开放在线课程提供接口，作为运营和维护在线基础设施的潜在收入来源，为可持续性奠定基础。智力优势：改善STEM教育需要有效可靠的工具来洞察学生的思维。与多项选择工具相比，构建反应评估的自动化分析有可能以更丰富、更多方面的方式评估STEM中的“大创意”。这个项目正在扩展这些项目的数量，并提供一个在线社区，教师可以在那里获得、评分，并为他们的分析提供必要的项目和资源库。更广泛的影响：门户网站正在将这个项目中创建的产品的使用扩展到全国的教师。此外，它还为有兴趣开发更深层次概念评估工具的科学和工程教育工作者的全国合作提供了基础，并支持和指导博士后研究人员，以及STEM教育研究的研究生研究助理。