ITR: Collaborative Research: Putting a Face on Cognitive Tutors: Bringing Active Inquiry into Active Problem Solving

ITR：协作研究：认知导师的面孔：将主动探究引入主动问题解决中

• 批准号: 0205506
• 负责人: Michelene Chi
• 金额: $ 32.15万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0205506&HistoricalAwards=false
• 关键词: ITR; Collaborative; Research; Putting; Face

EIA-0205301Albert CorbettCarnegie-Mellon UniversityITR: Collaborative Research: Putting a Face on Cognitive Tutors:Bringing Active Inquiry into Active Problem SolvingCollaborative project with:0205506Michelene ChiUniversity of PittsburghThis project builds on a growing body of research concerning effective learning and tutoring strategies. The project involves constructing and evaluating educational technology that emulates human tutors by integrating a state-of-the art educational technology called Cognitive Tutors with a innovative interactive questioning environment called Synthetic Interviews to produce an inactive learning environment that rivals the effectiveness of human tutors. Cognitive tutors are built around a cognitive model of problem solving knowledge and provide precisely the support students need to complete problems successfully. Used alone, cognitive tutors do not support the help-seeking and meta-cognitive skills that characterize active learners. By incorporating a novel interactive communication technology called Synthetic Interviews, an Active Learning Environment is offered that rivals the effectiveness of human tutors in supporting deep student learning. Synthetic Interviews allow learners to engage in active inquiry by providing the means for conversing in-depth with an individual. Synthetic Interviews permit knowledge capture in a new form providing utility similar to an expert system but a development effort approaching the simple video taping of a conversation. The Active Learning Environment serves as a research tool to examine both computational and pedagogical challenges and also as an educational environment in classrooms and homes. In particular, the domains of knowledge that are constructed around this learning environment are mathematics and biology courses. The project promises to make important contributions to cognitive science, computer science and educational practice including the following: 1) The analysis of student questions during synthetic interviews will contribute to basic cognitive models of the functional relationship between declarative conceptual knowledge and procedural problem solving knowledge, 2) This project will integrate cognitive models of student knowledge and tutorial dialogue structure. More generally, the project will help define a design and engineering process for intelligent learning environments, 3) The research will inform the design of more effective computer-based learning environments. 4) The research and the active learning environment can support improved professional development both for pre-service and in-service teachers. The Active Learning Environments for mathematics and biology that are developed in this project promise to directly improve educational practice nationally. Current generation cognitive mathematics tutors are already in use in about 2% of middle schools and high schools around the country. The demand for effective mathematics and science education continues to grow. States are increasing mathematics graduation requirements and instituting assessments that govern student graduation and school evaluations. If Active Learning Environments are more effective than current generation Cognitive Tutors, they promise to rapidly enter widespread classroom use.

EIA-0205301阿尔伯特Corbettgie-Mellon大学ITR：合作研究：把一个面孔上的认知导师：把积极的调查到积极的问题解决合作项目：0205506米凯琳ChiUniversity of Bennburg这个项目建立在一个越来越多的研究机构有关有效的学习和辅导策略。该项目涉及构建和评估教育技术，通过将最先进的教育技术（称为认知导师）与创新的互动提问环境（称为合成面试）相结合，模仿人类导师，以产生一种与人类导师的有效性相媲美的非活动学习环境。认知导师是建立在解决问题的知识的认知模型，并提供准确的支持学生需要成功地完成问题。单独使用，认知导师不支持寻求帮助和元认知技能的特点积极的学习者。通过结合一种名为合成面试的新型交互式通信技术，提供了一种主动学习环境，可以与人类导师在支持深度学生学习方面的有效性相媲美。综合面试通过提供与个人深入交谈的手段，使学习者能够积极参与调查。合成面试允许知识捕获在一个新的形式提供类似于专家系统的实用程序，但一个简单的视频录制的对话的发展努力。主动学习环境作为一种研究工具来研究计算和教学的挑战，也作为教室和家庭的教育环境。特别是，围绕这种学习环境构建的知识领域是数学和生物课程。该项目有望对认知科学、计算机科学和教育实践做出重要贡献，包括：1）综合访谈中学生问题的分析将有助于陈述性概念知识和程序性问题解决知识之间的功能关系的基本认知模型，2）该项目将整合学生知识的认知模型和指导对话结构。更一般地说，该项目将有助于定义智能学习环境的设计和工程过程，3）该研究将为更有效的基于计算机的学习环境的设计提供信息。4)研究和积极的学习环境可以支持职前和在职教师的专业发展。本项目开发的数学和生物学主动学习环境有望直接改善全国的教育实践。目前，全国大约2%的中学和高中已经使用了这一代认知数学导师。对有效的数学和科学教育的需求继续增长。各州正在提高数学毕业要求，并制定管理学生毕业和学校评估的评估。如果主动学习环境比当前一代的认知导师更有效，它们将迅速进入广泛的课堂使用。