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Jianping Shen; Huang Wu – Educational Administration Quarterly, 2025
Principal leadership has been widely regarded as a powerful catalyst for school improvement and student learning. This article presents a multivariate meta-analysis of 42 empirical studies, published between 2000 and 2020, that examined the effects of principal leadership on student achievement in the United States. The focus is on the conceptual…
Descriptors: Principals, Leadership Styles, Academic Achievement, Correlation
David Broska; Michael Howes; Austin van Loon – Sociological Methods & Research, 2025
Large language models (LLMs) provide cost-effective but possibly inaccurate predictions of human behavior. Despite growing evidence that predicted and observed behavior are often not "interchangeable," there is limited guidance on using LLMs to obtain valid estimates of causal effects and other parameters. We argue that LLM predictions…
Descriptors: Artificial Intelligence, Observation, Prediction, Correlation
Huibin Zhang; Zuchao Shen; Walter L. Leite – Journal of Experimental Education, 2025
Cluster-randomized trials have been widely used to evaluate the treatment effects of interventions on student outcomes. When interventions are implemented by teachers, researchers need to account for the nested structure in schools (i.e., students are nested within teachers nested within schools). Schools usually have a very limited number of…
Descriptors: Sample Size, Multivariate Analysis, Randomized Controlled Trials, Correlation
Steven Glazerman; Larissa Campuzano; Nancy Murray – Evaluation Review, 2025
Randomized experiments involving education interventions are typically implemented as cluster randomized trials, with schools serving as clusters. To design such a study, it is critical to understand the degree to which learning outcomes vary between versus within clusters (schools), specifically the intraclass correlation coefficient. It is also…
Descriptors: Educational Experiments, Foreign Countries, Educational Assessment, Research Design