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Computer environments for children: a reflection on theories of learning and education
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CHI '86 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Improvement of the acquisition of knowledge by informing feedback
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The Architecture of Cognition
The Psychology of Human-Computer Interaction
The Psychology of Human-Computer Interaction
Mindstorms: children, computers, and powerful ideas
Mindstorms: children, computers, and powerful ideas
Limitations of Student Control: Do Students Know When They Need Help?
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ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
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Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
User Modeling and User-Adapted Interaction
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Enhancing the automatic generation of hints with expert seeding
International Journal of Artificial Intelligence in Education - Special issue on Best of ITS 2010
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Feedback during learning is critical for evaluating new skills. Computer-based tutoring systems have the potential to detect errors and to guide students by providing informative feedback, but few studies have evaluated the real impact of different types of feedback. This article presents results of such a study using the Geometry Tutor for building geometry proofs. It was found that feedback about the goal structure of geometry problems led to better performance than feedback about the reasons for error or than simply being told that an error had occurred. This goal feedback allows students to correct the incorrect action more often than other types of feedback. Also, the goal feedback group continued to deal advantageously with problems when the feedback was subsequently removed. A simulation model, based on Anderson's (1983) ACT* theory and an analogical learning system, presents a preliminary model of the effects of these different feedback types. The model indicates that the advantage of goal-directed feedback is a reflection of its immediate application to the problem, whereas feedback about reasons for the error does not provide any direction to the correct error. According to the model, the feedback allows the student to construct a correct representation of the goal tree involved in various types of proofs more readily than feedback that is not immediately relevant to the current problem.