Metacognition and Misconceptions: Using Web-Based Writing Exercises in Gateway STEM Courses

这个项目旨在通过提高本科生的元认知技能和概念理解来服务于国家利益，这些本科生通常在基础科学、技术、工程和数学(STEM)课程中苦苦挣扎。众所周知，学生在STEM课程中遇到的困难，如电路分析和工程静力学，往往是因为学生无法准确地识别他们的知识差距，并制定和遵循缩小这些差距的策略。这一过程是展示高级元认知技能的一种手段。该项目将在电路分析导论本科课程中实施以写作为中心的新方法，以帮助学生建立心理模型，克服误解，并提高元认知技能。电路分析入门课程将要求学生利用物理世界中抽象现象的准确心理模型。学生经常带着错误的抽象现象心理模型进入这类课程。因此，概念的改变对于内容的掌握是必要的。这个项目将加深对如何设计简答式写作练习的理解，这些练习要求学生考虑常见的误解问题。为了促进深度反思，并提供即时和个性化的反馈，写作练习将被评估为能够促进概念变化和元认知技能发展的能力。反馈既是即时的，又是个性化的，这一事实尤其值得注意，因为众所周知，当反馈是及时的、针对给定学生的准确解释时，反馈是最有效的。为了实现即时和个性化的大规模反馈系统，写作练习将作为利用自然语言处理最新进展的基于网络的应用程序来实施。为了确保本项目开发的软件具有广泛的适用性，来自全国多个学科的教师将使用研究团队开发的基于网络的模板，在其STEM基础课程中实施基于概念的写作练习。除了有助于更深入地理解如何在STEM基础课程中最好地使用简答式写作以及增加此类课程的留存率外，该项目还将培训本科生和研究生实施使用人工智能算法实现的软件系统。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生的STEM教育的有效性。通过参与的学生学习路径，该计划支持有前景的实践和工具的创建、探索和实施。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to serve the national interest by enhancing the metacognitive skill and conceptual understanding of undergraduate students who typically struggle in foundational Science, Technology, Engineering, and Mathematics (STEM) courses. It is well known that student difficulties in STEM courses such as electric circuit analysis and engineering statics often arise from an inability of the student to accurately identify their knowledge gaps and to develop and follow strategies to close these gaps. This process is a means of exhibiting advanced metacognitive skill. The project will implement a novel writing-centric approach in an introductory circuit analysis undergraduate course to help students build mental models, overcome misconceptions, and enhance metacognitive skill. The introductory circuit analysis course will require students to utilize accurate mental models of abstract phenomena in the physical world. Students often enter such courses with faulty mental models of abstract phenomena. As such, conceptual change is necessary for content mastery.The project will develop a deeper understanding of how to design short-answer writing exercises that require the student to consider problems in which misconceptions are common. Promoting deep reflection and providing instantaneous and personalized feedback, the writing exercises will be evaluated for their ability to enable both conceptual change and metacognitive skill development. The fact that the feedback is to be both immediate and individualized is particularly notable as feedback is known to be most effective when it is timely and targets the precise interpretation of a given student. To achieve an instantaneous and personalized feedback system that works at-scale, the writing exercises will be implemented as web-based applications that leverage recent advances in Natural Language Processing (NLP). To ensure the software developed in this project is broadly applicable, instructors from multiple disciplines across the country will use the web-based templates developed by the research team to implement conceptual-based writing exercises in their foundational STEM courses. In addition to contributing to a deeper understanding of how to best employ short answer writing in STEM foundational courses as well as increasing retention in such courses, this project will train undergraduate and graduate students in implementing software systems made possible with algorithms employing artificial intelligence. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.