Reference : Methodological Issues in Value-Added Modeling: An International Review from 26 Countries
Scientific journals : Article
Social & behavioral sciences, psychology : Education & instruction
http://hdl.handle.net/10993/39893
Methodological Issues in Value-Added Modeling: An International Review from 26 Countries
English
Levy, Jessica mailto [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Luxembourg Centre for Educational Testing (LUCET) >]
Brunner, Martin [University of Potsdam]
Keller, Ulrich mailto [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Luxembourg Centre for Educational Testing (LUCET) >]
Fischbach, Antoine mailto [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Luxembourg Centre for Educational Testing (LUCET) >]
Aug-2019
Educational Assessment, Evaluation and Accountability
Springer
Yes
International
1874-8597
1874-8600
Norwell
Germany
[en] Value-added modeling ; Literature review ; Primary and secondary education ; Teacher effectiveness ; School effectiveness
[en] Value-added (VA) modeling can be used to quantify teacher and school effectiveness by estimating the effect of pedagogical actions on students’ achievement. It is gaining increasing importance in educational evaluation, teacher accountability, and high-stakes decisions. We analyzed 370 empirical studies on VA modeling, focusing on modeling and methodological issues to identify key factors for improvement. The studies stemmed from 26 countries (68% from the USA). Most studies applied linear regression or multilevel models. Most studies (i.e., 85%) included prior achievement as a covariate, but only 2% included noncognitive predictors of achievement (e.g., personality or affective student variables). Fifty-five percent of the studies did not apply statistical adjustments (e.g., shrinkage) to increase precision in effectiveness estimates, and 88% included no model diagnostics. We conclude that research on VA modeling can be significantly enhanced regarding the inclusion of covariates, model adjustment and diagnostics, and the clarity and transparency of reporting.
http://hdl.handle.net/10993/39893
10.1007/s11092-019-09303-w
http://link.springer.com/article/10.1007/s11092-019-09303-w
FnR ; FNR10921377 > Adelheid Hu > CALIDIE > Capitalising on Linguistic Diversity in Education > 15/01/2017 > 14/07/2023 > 2016

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