Collaborative Research: Supporting Teachers in Responsive Instruction for Developing Expertise in Science

合作研究：支持教师进行响应式教学以发展科学专业知识

基本信息

批准号：
1813713
负责人：
Marcia Linn
金额：
$ 260.47万
依托单位：
University of California-Berkeley
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1813713&HistoricalAwards=false
关键词：
Collaborative Research Supporting Teachers Responsive

项目摘要

Many teachers want to adapt their instruction to meet student learning needs, yet lack the time to regularly assess and analyze students' developing understandings. The Supporting Teachers in Responsive Instruction for Developing Expertise in Science (STRIDES) project takes advantage of advanced technologies to support science teachers to rapidly respond to diverse student ideas in their classrooms. In this project students will use web-based curriculum units to engage with models, simulations, and virtual experiments to write multiple explanations for standards-based science topics. Advanced technologies (including natural language processing) will be used to assess students' written responses and summaries their science understanding in real-time. The project will also design planning tools for teachers that will make suggestions relevant research-proven instructional strategies based on the real-time analysis of student responses. Research will examine how teachers make use of the feedback and suggestions to customize their instruction. Further we will study how these instructional changes help students develop coherent understanding of complex science topics and ability to make sense of models and graphs. The findings will be used to refine the tools that analyze the student essays and generate the summaries; improve the research-based instructional suggestions in the planning tool; and strengthen the online interface for teachers. The tools will be incorporated into open-source, freely available online curriculum units. STRIDES will directly benefit up to 30 teachers and 24,000 students from diverse school settings over four years. The Discovery Research K-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 instructional innovations. 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. Leveraging advances in natural language processing methods, the project will analyze student written explanations to provide fine-grained summaries to teachers about strengths and weaknesses in student work. Based on the linguistic analysis and logs of student navigation, the project will then provide instructional customizations based on learning science research, and study how teachers use them to improve student progress. Researchers will annually conduct at least 10 design or comparison studies, each involving up to 6 teachers and 300-600 students per year. Insights from this research will be captured in automated scoring algorithms, empirically tested and refined customization activities, and data logging techniques that can be used by other research and curriculum design programs to enable teacher customization.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.

许多老师想调整他们的教学以满足学生的学习需求，但缺乏时间定期评估和分析学生发展的理解。支持教师发展科学专业知识的响应式教学（STRIDES项目）利用高级技术来支持科学教师在课堂上迅速回应各种学生的想法。在这个项目中，学生将使用基于Web的课程单元与模型，模拟和虚拟实验互动，以编写有关基于标准的科学主题的多个解释。高级技术（包括自然语言处理）将用于评估学生的书面回答，并实时概括他们的科学理解。该项目还将为教师设计计划工具，以根据学生回答的实时分析提出相关的研究预先教学策略。研究将研究教师如何利用反馈和建议来自定义其教学。此外，我们将研究这些教学变化如何帮助学生对复杂的科学主题以及理解模型和图形的能力建立连贯的理解。这些发现将用于完善分析学生论文并产生摘要的工具；在计划工具中改善基于研究的教学建议；并加强教师的在线界面。这些工具将被合并到开源的，可以免费提供的在线课程单元中。在四年内，大步将直接受益于来自不同学校环境的30名教师和24,000名学生。 Discovery Research K-12计划（DRK-12）旨在通过教学创新的研究和开发来显着增强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计划中的项目基于STEM教育和先前的研发工作的基础研究，这些研究为拟议项目提供了理论和经验的理由。利用自然语言处理方法的进步，该项目将分析学生书面解释，以向教师提供有关学生工作中优势和劣势的细粒度摘要。基于学生导航的语言分析和日志，该项目将根据学习科学研究提供教学自定义，并研究教师如何利用它们来改善学生的进步。研究人员每年将至少进行10种设计或比较研究，每年最多涉及6名教师和300-600名学生。这项研究的见解将在自动评分算法，经过经验测试和完善的自定义活动以及数据记录技术中被捕获，这些技术可以被其他研究和课程设计计划使用，以启用教师的自定义。该奖项反映了NSF的法定任务，并通过使用基础的智力来评估了NSF的法定任务，并具有评估的评估。