AutoMentor: Virtual Mentoring and Assessment in Computer Games for STEM Learning

AutoMentor：STEM 学习计算机游戏中的虚拟指导和评估

• 批准号: 0918409
• 负责人: David Shaffer
• 金额: $ 350万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0918409&HistoricalAwards=false
• 关键词: AutoMentor; Virtual; Mentoring; Assessment; Computer

The project builds on existing research and extends it to include a computational model of participation in a community of practice. The products include an automated mentoring system that uses natural language conversations to help students learn about science and technology and an assessment/analysis protocol to quantify students' STEM behavior. It extends automated tutoring with an automated mentoring technology, AutoMentor, and combines it with Epistemic Network Analysis. AutoMentor is implemented in Land Science, a multi-player urban planning game, and tested by the Massachusetts Audubon Society with approximately 700 middle school aged students either in after-school or in-school programs. Pioneering work drawn from three partner institutions inform the design of the system. These include intelligent tutoring (Graesser, University of Memphis), assessment (Mislevy, University of Maryland), and game-based learning (Shaffer, University of Wisconsin-Madison). The core technologies are supported by expertise in computer science, science content, measurement, and STEM educational programming. The project has the potential to transform all three core areas by providing a fully implementable system that supports student learning substantive content through immersion in a STEM processes. The PIs anticipate that this will be integral to learning systems of the future.

该项目以现有研究为基础，并将其扩展到包括参与实践社区的计算模型。 这些产品包括一种自动指导系统，该系统使用自然语言对话来帮助学生了解科学技术以及评估/分析协议，以量化学生的STEM行为。 它通过自动指导技术（汽车）扩展了自动补习，并将其与认知网络分析相结合。 Automentor在一家多人城市规划游戏的Land Science中实施，并由马萨诸塞州奥杜邦协会（Massachusetts Audubon Society）进行了测试，约有700名中学年龄的学生在课后或学校课程中进行了测试。 从三个合作伙伴机构绘制的开创性工作为系统的设计提供了信息。 其中包括智能辅导（孟菲斯大学的Graesser），评估（Mislevy，马里兰大学）和基于游戏的学习（威斯康星大学麦迪逊分校）。 核心技术得到了计算机科学，科学内容，测量和STEM教育计划方面的专业知识的支持。 该项目有可能通过提供完全可实施的系统来改变这三个核心领域，该系统支持学生通过沉浸在STEM过程中学习实质性内容的系统。 PI预计这将是未来学习系统不可或缺的一部分。