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

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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.