Investigating An Intelligent Cyberlearning System For Interactive Museum-based Sustainability Modeling
Investigating An Intelligent Cyberlearning System For Interactive Museum-based Sustainability Modeling
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
中文摘要
该项目将在博物馆为中学观众开发一个原型智能网络学习平台,以测试和评估虚拟学习技术的使用。这项测试的内容集中在可持续性问题上,使学生能够对特定的保护决策、能源使用、人类健康和地球生态系统内的人口增长之间的关系进行适合年龄的理解。原型网络学习系统将演示用户如何通过与环境因素的展示互动来学习科学主题,这些环境因素使他们能够探索社会、经济和技术力量的影响,这些力量可能会改变一种现有状态和条件。该系统将使用户能够了解这些要素的相互关系,使它们能够改变条件,然后观察它们对初始模型中提出的条件所作的改变的影响。原型智能网络学习系统将提供基于复杂智能体的环境、社会和经济现象的建模模拟与三种先进学习技术的独特集成:基于游戏的学习系统、智能辅导系统和以叙事为中心的学习系统。该项目基于游戏和叙事的方面体现在3D显示器的互动时间旅行焦点上,该3D显示器位于多点触摸表面计算台上,用户将在其中扮演环境科学家的角色,他们负责帮助地球成为一个蓬勃发展的绿色星球。他们将回到过去,并有机会就任何范围的选择做出不同的决定。在他们做出决定后,他们会及时向前旅行,看看他们的决定的结果。所有的互动都将被用来动态地生成他们的时空旅行冒险。智能辅导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,智能教学系统将根据他们对关键环境概念的理解程度进行推断。鉴于当前的问题解决目标(例如减少温室气体排放)和环境的当前状态(例如气候状态、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来帮助学生在可持续发展叙述中取得进展。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关于他们所做决策结果背后的因果联系的解释性评论和建议。同样,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发展的智能网络学习平台原型,支持对科学主题的独立但有指导的探索。由于所有用户互动都将由一位虚拟环境科学家陪同,他将讲述他们的旅程并提供解决问题的建议,用户将获得丰富的学习机会,支持独立探究,同时也提供对复杂科学主题的指导探索。以校外环境中的小组学习体验为重点,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合作努力,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、智能辅导系统和校外环境中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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