Supporting Science Learning and Teaching in Middle School Classrooms through Automated Analysis of Students' Writing

通过自动分析学生写作来支持中学课堂的科学学习和教学

• 批准号: 2010351
• 负责人: Rebecca Passonneau
• 金额: $ 147.73万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2010351&HistoricalAwards=false
• 关键词: Supporting; Science; Learning; Teaching; Middle

This project will develop a novel, automated technology to provide middle-school students and their teachers with real-time feedback about students’ written explanations of physics phenomena. The use of evidence to build scientific explanations is a central practice by which scientific knowledge is generated and learned. Students often do not understand what a scientific explanation is and frequently write incomplete, non-causal accounts of scientific phenomenon. Teachers often have difficulties in helping students write explanations, as it is complex and time-consuming. Working in groups of three or four and experimenting with designing a roller coaster, students will learn about key principles in physics such as the conservation of energy and the laws concerning forces and motion. Each student will be provided with a digital journal. The prompts and information in the journal will structure the roller coaster activities (supported 6-8 weeks of instruction) and provide the students with a place to record their written ideas and explanations. At the close of several rounds of experimentation and analysis, students will write causal explanations for their current design. Through the use of the wise crowd automated assessment system, students will receive feedback on their writing. (The automated wise crowd model uses a content assessment of the explanations of experts as the foundation for analyzing and providing feedback to students.) Teachers will also use information from the system to facilitate full class discussions and individualized support. Project research and development activities will result in a fully developed and tested mechanism for providing feedback for students’ science explanations. Through automated support of the content analysis of student writing across multiple assignments, the project innovations will allow teachers to more fully integrate writing into their assignments. Ultimately, the project can help students understand how scientific explanations are developed and justified and make them more critical consumers of scientific knowledge so they can make better informed decisions about scientific issues in everyday life. The project will use a design-based research approach in developing the automated system using wise-crowd analysis and in assessing the impacts of the system on student learning and teacher classroom practices. Four research questions will guide the research: (1) How does feedback from the wise crowd system affect students’ written explanation of scientific phenomenon?; (2) How do students with different levels of prior knowledge and reading comprehension benefit from automated feedback and teacher scaffolding?; (3) How do teachers use automated assessment and aggregated summaries of students’ explanations during instruction?; and (4) In what ways does scaffolding from the wise crowd system and feedback from teachers support students’ written explanations of learning? Through the four-year project, an iterative development process will include the design of the system and testing of two iterations of the system; research of student responses across the progression of roller coaster design and written assignments; and use of some validated and custom instruments to assess student understanding of key forces and assessment of student abilities to use data to evaluate claims. Classroom studies will use video data and researcher field notes to help understand how teachers facilitated the use of the wise-crowd system. Research will culminate in testing of the final version of the wise crowd system. Using a quasi-experimental design, classes will be randomly assigned to the treatment or comparison conditions. Findings will advance knowledge in the field about the best ways to integrate content assessment and feedback from the automated system with classroom and individual support from teachers to optimize learning for students. Materials and results generated from the project will be broadly disseminated, resulting in significant impacts for researchers and practitioners.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. 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.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.

该项目将开发一种新颖的自动化技术，为中学生和他们的老师提供有关学生对物理现象的书面解释的实时反馈。使用证据来建立科学解释是科学知识产生和学习的核心实践。学生往往不明白什么是科学解释，经常写不完整的，非因果关系的科学现象的帐户。 教师往往很难帮助学生写解释，因为它是复杂和耗时的。在三个或四个小组工作，并设计一个过山车的实验，学生将学习物理学的关键原则，如能量守恒和有关力和运动的法律。 每个学生都将获得一份电子期刊。日志中的提示和信息将组织过山车活动（支持6-8周的教学），并为学生提供一个记录他们的书面想法和解释的地方。在几轮实验和分析结束时，学生将为他们当前的设计写因果解释。 通过使用智能人群自动评估系统，学生将收到他们的写作反馈。(The自动智能人群模型使用专家解释的内容评估作为分析和向学生提供反馈的基础。教师还将使用系统中的信息来促进全班讨论和个性化支持。项目研究和开发活动将产生一个充分发展和测试的机制，为学生的科学解释提供反馈。 通过自动支持学生在多个作业中的写作内容分析，该项目的创新将使教师能够更充分地将写作融入到他们的作业中。 最终，该项目可以帮助学生了解科学解释是如何发展和合理的，使他们更挑剔的科学知识消费者，使他们能够在日常生活中对科学问题做出更明智的决定。这项计划将采用以设计为本的研究方法，以明智的人群分析方法开发自动化系统，并评估系统对学生学习和教师课堂实践的影响。本研究将围绕四个问题展开：（1）智慧人群系统的反馈如何影响学生对科学现象的书面解释？(2)具有不同先验知识和阅读理解水平的学生如何从自动反馈和教师支架中受益？(3)教师在教学中如何使用自动评估和学生解释的汇总摘要？（4）智慧人群系统的脚手架和教师的反馈以何种方式支持学生的书面学习解释？通过为期四年的项目，迭代开发过程将包括系统的设计和系统的两个迭代的测试;在过山车设计和书面作业的进展中研究学生的反应;以及使用一些经过验证的和定制的工具来评估学生对关键力量的理解和评估学生使用数据评估索赔的能力。 课堂研究将使用视频数据和研究人员现场笔记，以帮助了解教师如何促进使用智慧人群系统。研究将在测试智慧人群系统的最终版本时达到高潮。 使用准实验设计，班级将被随机分配到治疗或比较条件。调查结果将推进该领域的知识，了解如何将自动化系统的内容评估和反馈与教师的课堂和个人支持相结合，以优化学生的学习。该项目产生的材料和成果将被广泛传播，对研究人员和从业人员产生重大影响。发现研究preK-12计划（DRK-12）旨在通过研究和开发创新资源，模型和工具，显着提高preK-12学生和教师的科学，技术，工程和数学（STEM）的学习和教学。DRK-12项目中的项目建立在STEM教育的基础研究以及为拟议项目提供理论和经验依据的先前研究和开发工作的基础上。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Design of Real-time Scaffolding of Middle School Science Writing Using Automated Techniques

利用自动化技术进行中学科学写作实时支架设计

• 发表时间: 2022
• 期刊: ICLS2022 Proceedings
• 作者: Singh, Purushartha;Gnesdilow, Dana;Cang, Xuesong;Baker, Samantha;Goss, William;Kim, ChanMin;Passonneau, Rebecca J.;Puntambekar, Sadhana
• 通讯作者: Puntambekar, Sadhana

A Semantic Feature-Wise Transformation Relation Network for Automatic Short Answer Grading

• DOI: 10.18653/v1/2021.emnlp-main.487
• 发表时间: 2021
• 作者: Zhaohui Li;Yajur Tomar;R. Passonneau

Automated support to scaffold students' written explanations in science

自动支持学生的科学书面解释

• 发表时间: 2022
• 期刊: Proceedings of the 23rd International Conference on Artificial Intelligence in Education
• 作者: Singh, Purushartha;Passonneau, Rebecca J.;Wasih, Mohammed;Cang, Xuesong;Kim, ChanMin;Puntambekar, Sadhana
• 通讯作者: Puntambekar, Sadhana

Foundations for AI-Assisted Formative Assessment Feedback for Short-Answer Tasks in Large-Enrollment Classes

大招生班级简答任务人工智能辅助形成性评估反馈的基础

• 发表时间: 2022
• 期刊: 1th International Conference on Teaching Statistics: Bridging the Gap: Empowering and Educating Today’s Learners in Statistics
• 作者: Lloyd, Susan;Beckman, Matthew D.;Pearl, Dennis K.;Passonneau, Rebecca J.;Li, Zhaohui;Wang, Zekun
• 通讯作者: Wang, Zekun

Combining Student and Teacher Feedback for Effective Science Writing

结合学生和教师的反馈进行有效的科学写作

• 发表时间: 2022
• 期刊: Proceedings of International Conference of the Learning Sciences 2022
• 作者: Goss, William;Singh, Purushratha;Puntambekar, Sadhana;Gnesdilow, Dana;Kim, ChanMin;Passonneau, Rebecca J.
• 通讯作者: Passonneau, Rebecca J.