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. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Adams, D. M., McLaren, B. M., Mayer, R. E., Goguadze, G., & Isotani, S. (2013). Erroneous examples as desirable difficulty. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7926 LNAI, pp. 803–806). Springer Verlag. https://doi.org/10.1007/978-3-642-39112-5_117
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