Di Lonardo Burr, S.M., Douglas, H., Vorobeva, M. et al. (1 more author) (2020) Refuting misconceptions: computer tutors for fraction arithmetic. Journal of Numerical Cognition, 6 (3). pp. 355-377. ISSN 2363-8761
Abstract
Fractions, known to be difficult for both children and adults, are especially prone to misconceptions and erroneous strategy selection. The present study investigated whether a computer tutor improves fraction arithmetic performance in adults and if supplementing problem solving with erroneous examples is more beneficial than problem solving alone. Seventy-five undergraduates solved fraction arithmetic problems using a computer tutoring system we designed. In a between-subjects design, 39 participants worked with a problem-solving tutor that was supplemented with erroneous examples and 36 participants worked with a traditional problem-solving tutor. Both tutors provided hints and feedback. Overall, participants improved after the tutoring interventions, but there were no significant differences in gains made by the two conditions. For students with low prior knowledge about fraction arithmetic, the numerical gains were higher in the erroneous-example group than the problem-solving group, but this effect was not significant. Thus, computer tutors are useful tools for improving fraction knowledge. While erroneous examples may be particularly beneficial for students with low prior knowledge who may hold more misconceptions, more research is needed to make this conclusion.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | fractions; fraction misconceptions; educational technology; example-tracing tutor |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Dec 2023 14:24 |
Last Modified: | 08 Dec 2023 14:24 |
Status: | Published |
Publisher: | Leibniz Institute for Psychology (ZPID) |
Refereed: | Yes |
Identification Number: | 10.5964/jnc.v6i3.310 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:206221 |