Intelligent Tutoring System Using Decision Based Learning for Thermodynamic Phase Diagrams
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Abstract
Students learn when they connect new information to existing understanding or when they modify existing understanding to accept new information. Most current teaching methods focus on trying to get students to solve problems in a manner identical to that of an expert. This study investigates the effectiveness of assessing student understanding related to context specific problem solving decisions, prescribing feedback based on the assessment, and improving student understanding to the point where they can make correct decisions. Students were given a refrigeration problem unlike their prior problems and were asked to draw the cycle on a T-v diagram using a tutor system. Every group tested (a total of 373 students) showed a significant improvement in their understanding (p < 0.0001, Cohen’s d > 0.8) using a single 40 minute tutor activity
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This article is published as Hagge, Matthew, Mostafa Amin-Naseri, John K. Jackman, Enruo Guo, Stephen B. Gilbert, Gloria Starns, LeAnn Faidley. "Intelligent Tutoring System Using Decision Based Learning for Thermodynamic Phase Diagrams." Advances in Engineering Education 6, no. 1 (2017). Posted with permission.