Krittaya Leelawong, Yingbin Wang, Gautam Biswas, Nancy Vye, and John Bransford
Vanderbilt University, Nashville, TN 37235
Daniel Schwartz
Stanford University, Stanford CA 94305
Abstract: This Paper describes the use of qualitative reasoning mechanisms in designing a teachable agent that learns water-quality monitoring from middle school students. Students explicitly teach the computer agent to solve problems using concept maps, which help to construct knowledge without becoming involved in sophisticated programming activities. Once taught, the agent attempts to answer questions using qualitative reasoning schemes that are intuitive and easy to apply. Students can reflect on the agent's responses, and then revise and refine this knowledge through visual interfaces. Preliminary studies have demonstrated the effectiveness of the approach.