Scaffolding problem solving with annotated, worked-out examples to promote deep learning

Michael A. Ringenberg; Kurt VanLehn

doi:10.1007/11774303_62

Scaffolding problem solving with annotated, worked-out examples to promote deep learning

Michael A. Ringenberg, Kurt VanLehn

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

30 Scopus citations

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.

Original language	English (US)
Title of host publication	Intelligent Tutoring Systems - 8th International Conference, ITS 2006, Proceedings
Publisher	Springer Verlag
Pages	625-634
Number of pages	10
ISBN (Print)	3540351590, 9783540351597
DOIs	https://doi.org/10.1007/11774303_62
State	Published - 2006
Externally published	Yes
Event	8th International Conference on Intelligent Tutoring Systems, ITS 2006 - Jhongli, Taiwan, Province of China Duration: Jun 26 2006 → Jun 30 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4053 LNCS

Other

Other	8th International Conference on Intelligent Tutoring Systems, ITS 2006
Country/Territory	Taiwan, Province of China
City	Jhongli
Period	6/26/06 → 6/30/06

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/11774303_62

Cite this

Ringenberg, M. A., & VanLehn, K. (2006). Scaffolding problem solving with annotated, worked-out examples to promote deep learning. In Intelligent Tutoring Systems - 8th International Conference, ITS 2006, Proceedings (pp. 625-634). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4053 LNCS). Springer Verlag. https://doi.org/10.1007/11774303_62

Scaffolding problem solving with annotated, worked-out examples to promote deep learning. / Ringenberg, Michael A.; VanLehn, Kurt.
Intelligent Tutoring Systems - 8th International Conference, ITS 2006, Proceedings. Springer Verlag, 2006. p. 625-634 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4053 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ringenberg, MA & VanLehn, K 2006, Scaffolding problem solving with annotated, worked-out examples to promote deep learning. in Intelligent Tutoring Systems - 8th International Conference, ITS 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4053 LNCS, Springer Verlag, pp. 625-634, 8th International Conference on Intelligent Tutoring Systems, ITS 2006, Jhongli, Taiwan, Province of China, 6/26/06. https://doi.org/10.1007/11774303_62

Ringenberg MA, VanLehn K. Scaffolding problem solving with annotated, worked-out examples to promote deep learning. In Intelligent Tutoring Systems - 8th International Conference, ITS 2006, Proceedings. Springer Verlag. 2006. p. 625-634. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11774303_62

Ringenberg, Michael A. ; VanLehn, Kurt. / Scaffolding problem solving with annotated, worked-out examples to promote deep learning. Intelligent Tutoring Systems - 8th International Conference, ITS 2006, Proceedings. Springer Verlag, 2006. pp. 625-634 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Scaffolding problem solving with annotated, worked-out examples to promote deep learning

Abstract

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