Fraction Errors in a Digital Mathematics Environment: Latent Class and Transition Analysis
This article is a preprint and has not been certified by peer review [What does this mean?].
Author(s) / Creator(s)
Karamarkovich, Sarah Marina
Rutherford, Teomara
Abstract / Description
Student struggles with fractions are well documented, and due to fractions’ importance to later mathematics achievement, identification of the errors students make when solving fraction problems is an area of interest for both researchers and teachers. Within this study, we examine data on student fraction problem errors in pre- and post-quizzes in a digital mathematics environment. Students (N=1,431) were grouped by prevalence of error types using latent class analysis. Three different classes of error profiles were identified in the pre-quiz data. A latent transition analysis was then used to determine if class membership and class structure changed from pre- to post-quiz. In both pre- and post-quiz, there was a class of students who appeared to be guessing and a class of students who performed well. One class structure was consistent with the idea that early fraction learners rely heavily on whole number principles. Identification of co-occurrence of and changes to fraction errors has implications for curricular design and pedagogical decisions, especially in light of movements toward personalized learning systems.
Keyword(s)
fraction errors elementary mathematics latent class analysis latent transition analysisPersistent Identifier
Date of first publication
2018
Publisher
ZPID (Leibniz Institute for Psychology Information)
Citation
Karamarkovich, S. M. & Rutherford, T. (2018). Fraction errors in a digital mathematics environment: Latent class and transition analysis [Preprint].
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Author(s) / Creator(s)Karamarkovich, Sarah Marina
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Author(s) / Creator(s)Rutherford, Teomara
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PsychArchives acquisition timestamp2018-10-31T09:55:43Z
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Made available on2018-10-31T09:55:43Z
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Date of first publication2018
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Abstract / DescriptionStudent struggles with fractions are well documented, and due to fractions’ importance to later mathematics achievement, identification of the errors students make when solving fraction problems is an area of interest for both researchers and teachers. Within this study, we examine data on student fraction problem errors in pre- and post-quizzes in a digital mathematics environment. Students (N=1,431) were grouped by prevalence of error types using latent class analysis. Three different classes of error profiles were identified in the pre-quiz data. A latent transition analysis was then used to determine if class membership and class structure changed from pre- to post-quiz. In both pre- and post-quiz, there was a class of students who appeared to be guessing and a class of students who performed well. One class structure was consistent with the idea that early fraction learners rely heavily on whole number principles. Identification of co-occurrence of and changes to fraction errors has implications for curricular design and pedagogical decisions, especially in light of movements toward personalized learning systems.en_US
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Review statusnotReviewed
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SponsorshipSupport for this research was provided in part by the National Science Foundation, grant number 1544273 and based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No DGE-1746939.en_US
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CitationKaramarkovich, S. M. & Rutherford, T. (2018). Fraction errors in a digital mathematics environment: Latent class and transition analysis [Preprint].en_US
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/732
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.925
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Language of contentengen_US
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PublisherZPID (Leibniz Institute for Psychology Information)en_US
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Keyword(s)fraction errorsen_US
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Keyword(s)elementary mathematicsen_US
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Keyword(s)latent class analysisen_US
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Keyword(s)latent transition analysisen_US
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Dewey Decimal Classification number(s)150
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TitleFraction Errors in a Digital Mathematics Environment: Latent Class and Transition Analysisen_US
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DRO typepreprinten_US