| Reference : Value-Added Modelling in Primary and Secondary School: An Integrative Review of 674 P... |
| Scientific congresses, symposiums and conference proceedings : Unpublished conference | |||
| Social & behavioral sciences, psychology : Education & instruction | |||
| http://hdl.handle.net/10993/31958 | |||
| Value-Added Modelling in Primary and Secondary School: An Integrative Review of 674 Publications | |
| English | |
Levy, Jessica  [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Luxembourg Centre for Educational Testing (LUCET) >] | |
| Keller, Ulrich [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Luxembourg Centre for Educational Testing (LUCET) >] | |
| Brunner, Martin [University of Potsdam] | |
| Fischbach, Antoine [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Luxembourg Centre for Educational Testing (LUCET) >] | |
| Dec-2017 | |
| Yes | |
| International | |
| London International Conference on Education | |
| from 11-12-2017 to 14-12-2017 | |
| University of Cambridge | |
| Cambridge | |
| United Kingdom | |
| [en] Value-added (VA) modelling aims to quantify the effect of pedagogical actions on students’ achievement, independent of students’ backgrounds (e.g., [1]); in other words, VA strives to model the added value of teaching. VA is typically used for teacher and/or school accountability (e.g., [2]). Although, VA models have gained popularity in recent years—a substantial increase of publications is to be observed over the last decade—, there is no consensus on how to calculate VA, nor is there a consensus whether and which covariates should be included in the statistical models (e.g., [3]).
The aim of the present study is to conduct a to date non-existent integrative review on VA modelling in primary and secondary education. Starting with an exhaustive literature research in the ERIC, Scopus, PsycINFO, and Psyndex databases, we reviewed and thoroughly classified 674 VA publications from 32 different countries. Half of the studies investigated VA models at teacher level; the remaining looked at school or principal level. 370 studies used empirical data to calculate VA models. Most of these studies explained their covariates, but approximately 15% did not specify the model. Most studies used prior achievement as a covariate, but cognitive and/or motivational student data were almost never taken into consideration. Moreover, most of the studies did not adjust for methodological issues such as missing data or measurement error. To conclude, given the high relevance of VA—it is primarily used for high-stakes decisions— more transparency, rigor and consensus are needed, especially concerning methodological details. References [1] Braun, H. I. (2005). Using student progress to evaluate teachers: A primer on value-added models. Princeton, NJ: Educational Testing Service. [2] Sanders, W. L. (2000). Value-added assessment from student achievement data: Opportunities and hurdles. Journal of Personnel Evaluation in Education, 14(4), 329–339. [3] Newton, X., Darling-Hammond, L., Haertel, E., & Thomas, E. (2010). Value-added modeling of teacher effectiveness: An exploration of stability across models and contexts. Education Policy Analysis Archives, 18(23). | |
| http://hdl.handle.net/10993/31958 | |
| FnR ; FNR10921377 > Adelheid Hu > CALIDIE > Capitalising On Linguistic Diversity In Education > 15/01/2017 > 14/07/2023 > 2015 |
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