Collaborative Research: DRK-12: Changing Culture in Robotics Classroom

合作研究：DRK-12：改变机器人课堂文化

• 批准号: 1418199
• 负责人: Robin Shoop
• 金额: $ 110.78万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1418199&HistoricalAwards=false
• 关键词: Collaborative; Research; DRK; 12; Changing

Computational and algorithmic thinking are new basic skills for the 21st century. Unfortunately few K-12 schools in the United States offer significant courses that address learning these skills. However many schools do offer robotics courses. These courses can incorporate computational thinking instruction but frequently do not. This research project aims to address this problem by developing a comprehensive set of resources designed to address teacher preparation, course content, and access to resources. This project builds upon a ten year collaboration between Carnegie Mellon's Robotics Academy and the University of Pittsburgh's Learning Research and Development Center that studied how teachers implement robotics education in their classrooms and developed curricula that led to significant learning gains. This project will address the following three questions:1.What kinds of resources are useful for motivating and preparing teachers to teach computational thinking and for students to learn computational thinking?2.Where do teachers struggle most in teaching computational thinking principles and what kinds of supports are needed to address these weaknesses?3.Can virtual environments be used to significantly increase access to computational thinking principles?The project will augment traditional robotics classrooms and competitions with Robot Virtual World (RVW) that will scaffold student access to higher-order problems. These virtual robots look just like real-world robots and will be programmed using identical tools but have zero mechanical error. Because dealing with sensor, mechanical, and actuator error adds significant noise to the feedback students' receive when programming traditional robots (thus decreasing the learning of computational principles), the use of virtual robots will increase the learning of robot planning tasks which increases learning of computational thinking principles. The use of RVW will allow the development of new Model-Eliciting Activities using new virtual robotics challenges that reward creativity, abstraction, algorithms, and higher level programming concepts to solve them. New curriculum will be developed for the advanced concepts to be incorporated into existing curriculum materials. The curriculum and learning strategies will be implemented in the classroom following teacher professional development focusing on computational thinking principles. The opportunities for incorporating computationally thinking principles in the RVW challenges will be assessed using detailed task analyses. Additionally regression analyses of log-files will be done to determine where students have difficulties. Observations of classrooms, surveys of students and teachers, and think-alouds will be used to assess the effectiveness of the curricula in addition to pre-and post- tests to determine student learning outcomes.

计算和算法思维是21世纪的新基本技能。不幸的是，美国很少有K-12学校提供重要的课程来解决这些技能。但是，许多学校确实提供机器人课程。这些课程可以结合计算思维指导，但经常不使用。该研究项目旨在通过开发旨在解决教师准备，课程内容和资源访问的全面资源来解决这个问题。 该项目建立在卡内基·梅隆（Carnegie Mellon）的机器人学院与匹兹堡大学的学习研究与发展中心之间的十年合作，该研究中心研究了教师如何在课堂上实施机器人教育并开发了导致大量学习成就的课程。该项目将解决以下三个问题：1。哪些资源对于激励和准备教师教授计算思维和学生学习计算思维的方法有用吗？2.教师在教导计算思维原理中需要最大的挣扎，以及需要哪种支持来解决这些弱点，以解决这些弱点？3.可用来实现竞争的范围，以增强竞赛的范围，并增加了训练室的范围，并将其访问训练室的范围（增强式的训练室），并访问了传统的训练营）脚手架学生访问高阶问题。这些虚拟机器人看起来像现实世界的机器人，并将使用相同的工具进行编程，但机械错误为零。因为处理传感器，机械和执行器错误会为学生在对传统机器人进行编程时的接收（从而减少计算原理的学习）时增加噪音，因此使用虚拟机器人的使用将增加对机器人计划任务的学习，从而增加计算思维原理的学习。 RVW的使用将允许使用新的虚拟机器人技术开发新的模型活动活动，以奖励创造力，抽象，算法和更高级别的编程概念来解决它们。将开发新的课程，以便将高级概念纳入现有的课程材料中。 在教师专业发展以计算思维原则为重点的教师专业发展之后，课程和学习策略将在课堂上实施。将使用详细的任务分析评估将计算思维原理纳入RVW挑战的机会。另外，将对日志文件进行回归分析，以确定学生在哪里遇到困难。 除了确定学生学习成果外，还将使用教室的观察，学生和教师的调查以及思考的观察来评估课程的有效性。