Erroneous examples as desirable difficulty

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

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.
OriginalspracheEnglisch
TitelArtificial Intelligence in Education : 16th international conference, AIED 2013, Memphis, TN, USA, July 9-13, 2013 ; proceedings
HerausgeberH.C. Lane, K. Yacef, J. Mostow, P. Pavlik
Anzahl der Seiten4
ErscheinungsortBerlin
VerlagSpringer Verlag
Erscheinungsdatum2013
Seiten803-806
ISBN (Print)978-3-642-39111-8
ISBN (elektronisch)978-3-642-39112-5
DOIs
PublikationsstatusErschienen - 2013
Veranstaltung16th International Conference on Artificial Intelligence in Education - AIED 2013 - Memphis, USA / Vereinigte Staaten
Dauer: 09.07.201313.07.2013
Konferenznummer: 16
https://sites.google.com/a/iis.memphis.edu/aied-2013-conference/

DOI

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