Metacognitive tutoring for inquiry-driven modeling

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Joyner, David A.
Goel, Ashok K.
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Over the past several decades, many K-12 classes have moved to use open, inquiry-based approaches to science instruction; research has shown some benefits from these approaches. However, there also exist significant challenges in teaching scientific modeling and inquiry, some based on their nature as metacognitive skills and others based on the general difficulty in providing guided instruction in open-ended exploratory learning contexts. To address these challenges, this dissertation presents a metacognitive tutoring system that teaches students an authentic process of inquiry-driven scientific modeling within an exploratory science learning environment. The design of the metacognitive tutoring system is informed by the literature on the process of scientific modeling and inquiry in both education and science, and it draws from AI theories of metacognition and intelligent tutoring. The tutoring system monitors the performance of teams of students in an open inquiry task in ecology. The system provides feedback on demand about how well the team is doing in investigating and explaining the system, and it also intervenes when errors in the process are observed or when new abilities are demonstrated. To evaluate this system, a controlled experiment was conducted with 237 students in a middle school life science classroom. In one condition, teams of students completed the activity without the tutoring system enabled, while in the other condition teams interacted with the tutoring system during part of their inquiry and modeling process. Evaluations of this experiment have shown that students who interact with the tutoring system improved in their attitudes toward scientific inquiry and careers in science, and that teams that interact with the tutoring system generate better explanations of ecological phenomena.
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