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…

Meta-analytic studies of second language (L2) learning typically employ a classic approach to meta-analysis. Although the classic approach can clarify findings, a multivariate, multilevel meta-analysis (3M) approach increases transparency by accounting for (a) dependencies in the evidence presented by primary studies, (b) methodological…

This research aims to propose a bibliometric map of studies on the use of STEM in education. This study used publication co-citation analysis, author co-citation analysis, and word frequency analysis methods to reveal the structure and transformation of STEM literature. Descriptive data such as the distribution of studies in the field by country,…

The clustered observational study (COS) design is the observational study counterpart to the clustered randomized trial. In a COS, a treatment is assigned to intact groups, and all units within the group are exposed to the treatment. However, the treatment is non-randomly assigned. COSs are common in both education and health services research. In…

Introduction: The What Works Clearinghouse (WWC) reviews rigorous research on educational interventions with a goal of identifying "what works" and making that information accessible to educators and policymakers. The WWC has historically prioritized internal validity over external validity in rating the quality of research. One critique…

Although educational research and evaluation generally occur in multilevel settings, many analyses ignore cluster effects. Neglecting the nature of data from educational settings, especially in non-randomized experiments, can result in biased estimates with long-term consequences. Our manuscript improves the availability and understanding of…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

MOOCs (massive open online courses) have attracted considerable attention from researchers. Fueled by constant change and developments in educational technology, the trends of MOOCs have varied greatly over the years. To detect and visualize the developments and changes in MOOC research, 4,652 articles published between 2009 and 2021 were…

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…

The present study contributes to the development of effective measures to evaluate classroom climate, especially in elementary education where these remain limited. In addition, it addresses a typical "flaw" of several studies by approaching classroom climate as a group-level construct rather than an individual characteristic. Following…

Background: Counts are familiar outcomes in education research settings, including those involving tests of interventions. Clustered data commonly occur in education research studies, given that data are often collected from students within classrooms or schools. There is a wide array of distributions and models that can be used for clustered…

The "Information Systems Education Journal" has published uninterrupted since 2003. Over its publication history, it has covered myriad topics related to information systems education including model curriculum, outcomes assessment, online learning, capstone courses, service learning, data analytics, and cybersecurity, just to name a…

Poor program implementation constitutes one explanation for null results in trials of educational interventions. For this reason, researchers often collect data about implementation fidelity when conducting such trials. In this article, we document whether and how researchers report and measure program fidelity in recent cluster-randomized trials.…

Conducting mixed methods research studies has the potential to help researchers who represent special education to address relatively complex questions compared to monomethod research studies. Therefore, it is important to determine the prevalence of mixed methods research studies in special education, especially because the prevalence rate…

The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and…