Erroneous examples as desirable difficulty

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

  • Deanne M. Adams
  • Bruce M. McLaren
  • Richard E. Mayer
  • George Goguadze
  • Seiji Isotani
Erroneous examples, an unusual and challenging form of learning material, are arguably a type of desirable difficulty for students that could lead to deeper learning. In a series of studies we have done over the past three years involving web-based math instruction, the learning benefits of erroneous examples we have observed occured on delayed tests, as occurs in the desirable difficulties literature. This short paper briefly reviews the literature, summarizes our results, and speculates on how an adaptive version of our materials could better leverage desirable difficulties theory and lead to deeper student learning.
Original languageEnglish
Title of host publicationArtificial Intelligence in Education : 16th international conference, AIED 2013, Memphis, TN, USA, July 9-13, 2013 ; proceedings
EditorsH.C. Lane, K. Yacef, J. Mostow, P. Pavlik
Number of pages4
Place of PublicationBerlin
PublisherSpringer Verlag
Publication date2013
Pages803-806
ISBN (print)978-3-642-39111-8
ISBN (electronic)978-3-642-39112-5
DOIs
Publication statusPublished - 2013
Event16th International Conference on Artificial Intelligence in Education - AIED 2013 - Memphis, United States
Duration: 09.07.201313.07.2013
Conference number: 16
https://sites.google.com/a/iis.memphis.edu/aied-2013-conference/

    Research areas

  • Mathematics - Adaptation of problems, Decimals, Erroneous examples, Interactive problem solving, Mathematics education, Self-explanation

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