This dissertation examined classification outcome differences among four popular individual supervised machine learning (ISML) models (logistic regression, decision tree, support vector machine, and multilayer perceptron) when predicting minor class membership within imbalanced datasets. The study context and the theoretical population sampled…

Using data from multiple informants has long been considered best practice in education. However, multiple informants often disagree on similar constructs, complicating decision-making. Polynomial regression and response-surface analysis (PRA) is often used to test the congruence effect between multiple informants on an outcome. However, PRA…

Despite federal and state laws and regulations that require states and local districts to provide English language learners (ELLs) with support services, prior research has indicated that ELLs are, in general, lagging behind non-ELLs in academic achievement. An unanswered question is whether the initial designation of students as ELL influences…

Higher education institutions choose to invest in upward reclassification for their athletics program with anticipation of generating increased revenue and exposure for their school; however, this could have a detrimental effect on their student-athletes' academic progress. This study examined the relationship between four classifications of…

With the implementation of RTI, educators are attempting to find models that are the best fit for their schools. The problem solving and standard protocol models are the two most common. This study of 65 students examines a new model, the dynamic skills protocol implemented in an elementary school starting in their fourth quarter of kindergarten…

With its critical assessments of scientific evidence on the effectiveness of education programs, policies, and practices (referred to as "interventions"), and a range of products summarizing this evidence, the What Works Clearinghouse (WWC) is an important part of the Institute of Education Sciences' strategy to use rigorous and relevant…