Abstract
This study compares the relative utility of an intelligent tutoring system that uses procedure-based hints to a version that uses worked-out examples for learning college level physics. In order to test which strategy produced better gains in competence, two versions of Andes were used: one offered participants graded hints and the other offered annotated, worked-out examples in response to their help requests. We found that providing examples was at least as effective as the hint sequences and was more efficient in terms of the number of problems it took to obtain the same level of mastery.
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Ringenberg, M.A., VanLehn, K. (2006). Scaffolding Problem Solving with Annotated, Worked-Out Examples to Promote Deep Learning. In: Ikeda, M., Ashley, K.D., Chan, TW. (eds) Intelligent Tutoring Systems. ITS 2006. Lecture Notes in Computer Science, vol 4053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11774303_62
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DOI: https://doi.org/10.1007/11774303_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35159-7
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