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Is academic tracking related to gains in learning competence? Using propensity score matching and differential item change functioning analysis for better understanding of tracking implications

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    SYSNO ASEP0537321
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleIs academic tracking related to gains in learning competence? Using propensity score matching and differential item change functioning analysis for better understanding of tracking implications
    Author(s) Martinková, P. (CZ)
    Hladká, Adéla (UIVT-O) SAI, ORCID, RID
    Potužníková, E. (CZ)
    Article number101286
    Source TitleLearning and Instruction. - : Elsevier - ISSN 0959-4752
    Roč. 66, April 2020 (2020)
    Number of pages11 s.
    Languageeng - English
    CountryGB - United Kingdom
    KeywordsAcademic tracking ; Learning competence ; Propensity score matching ; Differential item functioning in change ; Instructional sensitivity
    Subject RIVBB - Applied Statistics, Operational Research
    OBOR OECDStatistics and probability
    R&D ProjectsGBP402/12/G130 GA ČR - Czech Science Foundation (CSF)
    Způsob publikováníOpen access
    Institutional supportUIVT-O - RVO:67985807
    UT WOS000525859000003
    EID SCOPUS85075745856
    DOI10.1016/j.learninstruc.2019.101286
    AnnotationThis study analyzes gains in cognitive components of learning competence with respect to cohorts based on ability tracking in a Czech longitudinal study. Propensity score matching is used to form parallelized samples of academic and non-academic track students and to eliminate the effect of selective school intake. We applied regression models on the total scores to test for the overall track effect. Furthermore, we analyze scores and gains on the subscores and check for differential item functioning in Grade 6 and in change to Grade 9. While after 3 years, no significant difference between the two tracks was apparent in the total learning competence score, we did, however, find significant differences in some subscores and in the functioning of some items. We argue that item-level analysis is important for deeper understanding of the tracking implications and may provide the basis for more precise evidence-based decisions regarding the tracking policy.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2021
    Electronic addresshttp://hdl.handle.net/11104/0315047
Number of the records: 1