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: 1323162
• 负责人: Kevin Haudek
• 金额: $ 288.57万
• 依托单位: Michigan State University
• 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 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1323162&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.

该项目由6个机构的一个大型团队进行，该团队正在建立已经开发的开放式结构响应版本的成熟概念清单，可以用已经创建的计算机自动分析资源进行准确评估。 计算机自动化分析能够预测对学生在这些主题上的工作的人类评分，并且比一组训练有素的专家人类评分员表现出更高的评分员间可靠性。建构反应评估比多项选择题更能揭示学生的思维和误解的持续性，但需要教育者进行更多的分析。在过去的工作中，旨在确定重要学科结构的项目是根据先前的研究创建的。然后，这些项目通过在线课程管理系统进行管理，学生们可以输入答案。词汇和统计分析软件被用来预测学生的反应专家评级。到目前为止，工作主要集中在生物学和生物学背景下的化学领域。目前的项目是利用以前的研究自动评估的构造响应（AACR），并将工作扩展到其他机构和其他STEM学科。本项目的具体目标是：1.为建构反应自动评估（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使用评估，以推广创新。这包括有关问题所揭示的常见学生概念的信息，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，以创建和验证AACR问题，介绍化学，化学工程和统计学。4.参与持续的项目评估，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，为可持续发展奠定基础，作为运营和维护在线基础设施的潜在收入来源。智力优势：改善STEM教育需要有效和可靠的工具，以洞察学生的思维。对结构化反应评估的自动分析有可能以比多项选择工具更丰富、更多方面的方式评估STEM中的“大想法”。该项目正在扩大这些项目的数量，并提供一个在线社区，教师可以获得，评分，并为他们的分析所需的项目和资源库作出贡献。更广泛的影响：该门户网站正在将该项目中创建的产品的使用范围扩大到全国各地的教员。此外，它还为有兴趣开发更深入的概念评估工具的科学和工程教育工作者的全国合作提供基础，并支持和指导博士后研究员和STEM教育研究的研究生研究助理。