Research Assistant Intern 0927
January 08, 2009
Project Name
Intelligent Guided Experiential Learning (IGEL)
Project Description
The overarching goal of IGEL is to develop pedagogical models and implement intelligent support for learning in immersive learning environments. In previous work, we have addressed problems related to teaching interpersonal skills and cultural awareness. Our current focus is on ICT’s UrbanSim application, a game-based environment for teaching counterinsurgency and stability-focused operations. Specifically, we seek to teach UrbanSim players to consider potentially unintended or unanticipated effects of actions they take in the environment. Our approach involves asking users for their predicted outcomes and later asking them to compare those predictions with actual outcomes. The IGEL system queries and interprets results from an agent-based social simulation called PsychSim that drives the events of UrbanSim, then uses natural language generation techniques to present feedback to the learner to support reflection on their actions.
Job Description
We are seeking a graduate student (or advanced undergraduate) summer intern to work on the pedagogical algorithms that provide feedback and explanations in the IGEL/UrbanSim environment. The applicant will work with advanced artificial intelligence modules that model human behavior and interact in sometimes surprising ways. This will require:
• Studying and assessing the social simulation models that drive UrbanSim.
• Implementing new reflective tutoring tactics that pose questions to the learner about their choices and giving feedback on their choices.
• Developing natural language generation templates and models to support interaction with the learner (within our existing framework).
• Learning the programming practices and expectations of ICT programmers.
• Writing reports, documenting ideas, and presenting to IGEL team members.
Requirements:
• Required: Experience working with artificial intelligence systems (the more advanced classes taken and experience, the better).
• Required: Strong knowledge of Java, working knowledge of C++ and XML.
• Highly preferred: Experience with Eclipse, SVN, and Trac.
• Preferred: Publications in the areas of AI, intelligent tutoring systems, or educational technology. Experience working hands-on with users of computer-based learning environments.