Towards Adaptive Worked-Out Examples in an Intelligent Tutoring System
Pages 94 - 99
Abstract
Worked-out examples (WOEs) have been shown to be effective for learning, but they need to be adapted to student characteristics. We experimented with three versions of our Intelligent Tutoring System for Computer Science, one that does not include WOEs, and two that differ as concerns WOE length and content. We found that shorter WOEs are more effective for advanced students, whereas novice students learned the same, no matter the presence or length of the WOE.
References
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Chen, X., Mitrovic, A., Matthews, M.: Learning from worked examples, erroneous examples and problem solving: towards adaptive selection of learning activities. IEEE Transact. Learn. Technol. (2019).
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Di Eugenio, B., Chen, L., Green, N., Fossati, D., AlZoubi, O.: Worked out examples in computer science tutoring. In: 16th International Conference on Artificial Intelligence in Education. Memphis, TN, short paper, July 2013
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Published In
Jun 2019
459 pages
ISBN:978-3-030-23206-1
DOI:10.1007/978-3-030-23207-8
© Springer Nature Switzerland AG 2019.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 25 June 2019
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