Conference Paper

The Andes Physics Tutoring System: Five Years of Evaluations.

Conference: Artificial Intelligence in Education - Supporting Learning through Intelligent and Socially Informed Technology, Proceedings of the 12th International Conference on Artificial Intelligence in Education, AIED 2005, July 18-22, 2005, Amsterdam, The Netherlands
Source: DBLP

ABSTRACT Andes is a mature intelligent tutoring system that has helped hundreds of students improve their learning of university physics. It replaces pencil and paper problem solving homework. Students continue to attend the same lectures, labs and recitations. Five years of experimentation at the United States Naval Academy indicates that it significantly improves student learning. This report describes the evaluations and what was learned from them.

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Available from: Joel A. Shapiro, Jul 10, 2015
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    • "Developing such skills requires investment of time and lots of practice. Although Intelligent tutoring systems (ITSs) have proven to be effective in engaging learners and providing personalized learning process through the use of a student model [3] [4] [5] [6] [7] [8], there are a number of missing elements that seem necessary to stimulate desired learning outcomes, such as narrative context, rules, goals, rewards, and multisensory cues [1]. Serious games evolved as a field that combines education with game aspects which allows learning to be more motivating and appealing [9]. "
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    • "Intelligent tutoring systems (ITSs) are interactive educational systems that are built by combining from artificial intelligence techniques, and concepts from the learning sciences. These systems proved to be beneficial for learning in several domains, from programming languages [4] and middle school math [5], to physics [6] and military applications [7]. Unfortunately, because of interoperability issues, ITSs cannot be loaded into most educational platforms that are currently available and that require dedicated nonstandard frameworks. "
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    • "Adding self-explanation prompts to a Cognitive Tutor has been shown to increase the learners' understanding of how domain principles apply in problem solving (Aleven and Koedinger 2002; Roy and Chi 2005; cf. Van Lehn et al. 2005). While there is an extensive body of research on worked examples, their use within a tutored problem-solving environment (e.g., a Cognitive Tutor) has not been tested until very recently (McLaren et al. 2007; Schwonke et al. 2007). "
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