How prior information from national assessments can be used when designing experimental studies without a control group

Open Access
Authors
Publication date 2023
Journal Journal of Writing Research
Volume | Issue number 14 | 3
Pages (from-to) 447-469
Number of pages 23
Organisations
  • Faculty of Social and Behavioural Sciences (FMG) - Psychology Research Institute (PsyRes)
  • Faculty of Social and Behavioural Sciences (FMG) - Research Institute of Child Development and Education (RICDE)
Abstract
National assessments yield a description of the proficiency level in a domain while accounting for differences between tasks. For instance, in writing assessments the level of proficiency is typically evaluated with a variety of topics and multiple tasks. This enables generalizations from specific tasks to a domain. In (quasi-)experimental research, however, writing skills are often evaluated with a single task. Yet, conclusions about the effectiveness of the treatment are formulated on the level of the domain, which is, euphemistically put, quite a stretch. Although conclusions drawn about the effect of the treatment are specific to the task administered, they are often generalized to the domain without any form of reservation. This raises the question whether we can use the results of national assessments about differences between tasks in the analyses of experimental studies. In this paper, we demonstrate how the information of a baseline data set can be used as a kind of control condition in the analysis of an experimental study.
Document type Article
Note Funding Information: Code for the analyses and a simulated data set is availabe on GitHub at https://github.com/vandenman/Priors-Education Publisher Copyright: © This article is published under Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported license
Language English
Published at https://doi.org/10.17239/jowr-2023.14.03.05
Other links https://github.com/vandenman/Priors-Education https://www.scopus.com/pages/publications/85150286178
Downloads
JoWR_2022_volx_nrx_VandenBergh_et_al (Final published version)
Permalink to this page
Back