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Investigating An Intelligent Cyberlearning System For Interactive Museum-based Sustainability Modeling

Investigating An Intelligent Cyberlearning System For Interactive Museum-based Sustainability Modeling
研究基于交互式博物馆的可持续性建模的智能网络学习系统
批准号:
1114655
负责人:
James Lester
金额:
$71.34万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-15 至 2013-08-31

项目摘要

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中文摘要
翻译
该项目将在博物馆为中学观众开发一个智能网络学习平台原型,以测试和评估虚拟学习技术的使用。该测试的内容侧重于可持续发展问题,使学生能够对地球生态系统中特定的保护决策,能源使用,人类健康和人口增长之间的关系有一个适合年龄的理解。原型网络学习系统将展示用户如何通过与环境因素的显示进行交互来学习科学主题,这些环境因素使他们能够探索可能将一种现有状态和条件改变为另一种状态和条件的社会,经济和技术力量的影响。该系统将使用户能够了解这些要素的相互关系,使他们能够改变条件,然后观察他们所作的改变对初始模型中所列条件的影响。原型智能网络学习系统将提供一个独特的集成,一个复杂的基于代理的建模仿真的环境,社会和经济现象与三个先进的学习技术:基于游戏的学习系统,智能辅导系统和叙事为中心的学习系统。该项目的游戏和叙事方面体现在多点触摸表面计算表上的3D显示的交互式时间旅行焦点中,用户将扮演环境科学家的角色,他们负责帮助地球成为一个繁荣的绿色星球。他们将回到过去,并有机会对任何一系列选择做出不同的决定。在他们做出决定后,他们将及时向前旅行,看看他们决定的结果。所有的互动都将被用来动态地产生他们的时间旅行冒险。智能教学系统将跟踪用户在模拟世界中的问题解决活动。当用户做出决定时,智能辅导系统将推断他们对关键环境概念的理解水平。考虑到当前解决问题的目标(例如,减少绿色室内气体)和环境的当前状态(例如,气候状况,地球人口,工厂排放),智能辅导系统将利用其对常见环境误解的知识,帮助学生通过可持续性叙述取得进展。智能辅导系统将从基于代理的模拟接收更新的状态,然后将通过虚拟人向用户提供解释性评论和建议,这些评论和建议是关于他们所做决定的结果的因果关系。类似地,在决策过程中,用户将能够请求建议,相同的计算框架将驱动虚拟人的建议生成功能。该项目将设计、开发、部署和评估一个可持续性智能网络学习平台原型,支持独立但有指导的科学主题探索。由于所有用户的互动都将伴随着一位虚拟环境科学家,他将讲述他们的旅程并提供解决问题的建议,因此用户将获得丰富的学习机会,支持独立探究,但也提供了对复杂科学主题的指导探索。通过关注校外环境中的小组学习体验,虚拟环境科学家将回答一些问题,这些问题将使用户群体参与协作,以了解可持续发展的丰富相互关系。该项目将展示智能网络学习系统的变革潜力,该系统将基于代理的建模与基于游戏的学习,智能辅导系统以及校外以叙事为中心的学习相结合,使用户能够以全新的方式体验科学。
英文摘要
This project will develop a prototype intelligent cyberlearning platform for middle school audiences at a museum location to test and evaluate the use of virtual learning technologies. The content for this test is focused on sustainability issues that enable students to develop an age-appropriate understanding of the relationships between specific conservation decisions, energy use, human health, and population growth within Earth's ecosystem. The prototype cyberlearning system will demonstrate how users can learn about science topics by interacting with a display of environmental factors that enable them to explore the impact of social, economic, and technological forces that may change one existing state and condition to another. The system will enable users to understand the interrelationships of those elements by enabling them to change conditions and then observing the effect of the changes they make on the conditions presented in the initial model. The prototype intelligent cyberlearning system will provide a unique integration of a sophisticated agent-based modeling simulation of environmental, social, and economic phenomena with three advanced learning technologies: game-based learning systems, intelligent tutoring systems, and narrative-centered learning systems. The game-based and narrative aspects of the project are embodied in the interactive time-travel focus of the 3D display on a multi-touch surface computing table in which users will play the role of environmental scientists who have been charged with helping earth become a thriving green planet. They will go back in time and be given the opportunity to make different decisions on any range of options. After they make their decisions, they will travel forward in time to see the results of their decisions. All of the interactions will be used to dynamically generate their time-travel adventures. The intelligent tutoring system will track user's problem-solving activities in the simulated world. As users make decisions, the intelligent tutoring system will draw inferences about their level of understanding of key environmental concepts. Given the current problem-solving goal (e.g., reduce green house gases) and the current state of the environment (e.g., climatological state, earth's population, factory emissions), the intelligent tutoring system will draw on its knowledge of common environmental misconceptions to assist students as they progress through the sustainability narratives. The intelligent tutoring system will receive the updated state from the agent-based simulation, which will then provide explanatory commentary and advice through the virtual human to the users about the causal connections underlying the results of the decisions they have made. Similarly, during the course of decision-making, users will be able to request advice, and the same computational framework will drive the virtual human's advice generation functionalities.The project will design, development, deploy, and evaluate a prototype intelligent cyberlearning platform for sustainability that supports independent, but guided, exploration of science topics. Because all users interactions will be accompanied by a virtual environmental scientist who will narrate their journeys and offer problem-solving advice, users will be afforded rich learning opportunities that support independent inquiry but also provided guided exploration of complex science topics. With a focus on group learning experiences in the out-of-school setting, the virtual environmental scientist will answer questions that will engage groups of users in a collaborative effort to understand the rich interrelationships of sustainability. The project will demonstrate the transformative potential of intelligent cyberlearning systems that integrate agent-based modeling with game-based learning, intelligent tutoring systems, and narrative-centered learning in an out-of-school setting to enable users to experience science in fundamentally new ways.
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