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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 ASEP 0537321 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název 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 Tvůrce(i) Martinková, P. (CZ)
Hladká, Adéla (UIVT-O) SAI, ORCID, RID
Potužníková, E. (CZ)Číslo článku 101286 Zdroj.dok. Learning and Instruction. - : Elsevier - ISSN 0959-4752
Roč. 66, April 2020 (2020)Poč.str. 11 s. Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Klíč. slova Academic tracking ; Learning competence ; Propensity score matching ; Differential item functioning in change ; Instructional sensitivity Vědní obor RIV BB - Aplikovaná statistika, operační výzkum Obor OECD Statistics and probability CEP GBP402/12/G130 GA ČR - Grantová agentura ČR Způsob publikování Open access Institucionální podpora UIVT-O - RVO:67985807 UT WOS 000525859000003 EID SCOPUS 85075745856 DOI 10.1016/j.learninstruc.2019.101286 Anotace This 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. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2021 Elektronická adresa http://hdl.handle.net/11104/0315047
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