DIP: Collaborative Research: A Personalized Cyberlearning System Based on Cognitive Science

DIP：协作研究：基于认知科学的个性化网络学习系统

• 批准号: 1124535
• 负责人: Richard Baraniuk
• 金额: $ 57.02万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1124535&HistoricalAwards=false
• 关键词: DIP; Collaborative; Research; Personalized; Cyberlearning

Investigators from Rice University and Duke University will build a Personalized Cyberlearning System, designed around three principles from cognitive science (retrieval practice, spacing, and enhanced feedback), that leverages advances in machine learning and makes use of an existing instructional content material and problem set database aimed at undergraduate engineering students. The system will use artificial intelligence methods to optimize practice and feedback for students. Research will seek to advance knowledge, in a real-world setting, about a range of issues concerning how feedback facilitates learning, how individual differences come in to play, as well as those more specifically aimed at the development of the learning technology system itself.The project is important as part of the effort to harness the vast quantities of information on the web to personalize instruction for a wide range of learners. Moreover, the development of such cyberlearning technologies holds promise for opening up STEM education for motivated self-learners while also allowing access to a large volume of material for a range of students who might not otherwise have it.

来自莱斯大学和杜克大学的研究人员将建立一个个性化的网络学习系统，该系统围绕认知科学的三个原则（检索实践，间隔和增强反馈）设计，利用机器学习的进步，并利用现有的教学内容材料和针对本科工程专业学生的问题集数据库。该系统将使用人工智能方法来优化学生的练习和反馈。研究将寻求在现实世界的背景下，推进有关反馈如何促进学习的一系列问题的知识，个体差异如何发挥作用，以及那些更具体地针对学习技术系统本身的发展。该项目是重要的，作为努力利用网络上的大量信息，为广泛的学习者提供个性化教学的一部分。此外，这种网络学习技术的发展有望为有动力的自学者开放STEM教育，同时也允许一系列学生获得大量材料，否则他们可能无法获得这些材料。