The rapid advancements in generative artificial intelligence have opened new avenues for enhancing various aspects of research, including the design and evaluation of survey questionnaires. However, the recent pioneering applications have not considered questionnaire pretesting. This article explores the use of GPT models as a useful tool for…

Until now, the conventional approach using two distinct groups, experimental and control, continues to dominate research, especially education research. Researchers, particularly those who are active in this domain, readily recognise this pattern when surveying literature. This article explores the use of the Solomon four-group design as a…

We consider estimating the effect of a treatment on a given outcome measured on subjects tested both before and after treatment assignment in observational studies. A vast literature compares the competing approaches of modelling the post-test score conditionally on the pre-test score versus modelling the difference, namely, the gain score. Our…

Analyzing heterogeneous treatment effects (HTEs) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and preintervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…

Flipped learning's widespread adoption and multiple meta-analyses notwithstanding, there exists a scarcity of analyses scrutinizing its comprehensive influence on language learning results. This meta-analysis assesses flipped learning's impact on language learning outcomes vis-à-vis non-flipped instruction, encompassing distinct moderators…