The importance of retention rate for higher education institutions has encouraged data analysts to present various methods to predict at-risk students. Their objective is to provide timely information that may enable educators to channel the most effective remedial treatments towards precisely targeted students in an efficient manner. The present…

Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…

This retrospective study evaluates early semester predictors of whether or not community college students will successfully complete blended or hybrid courses. These predictors are available to faculty by the fourth week of the semester. Success is defined as receiving a grade of C- or higher. Failure is defined as a grade below a C- or a…

School dropout is a growing concern across Latin America because of its negative social and economic consequences. Identifying who is likely to drop out, and therefore could be targeted for interventions, is a well-studied prediction problem in countries with strong administrative data. In this paper, we use new data in Guatemala and Honduras to…

The main purpose of the paper is to estimate the efficiency of a big public university in Italy using individual student-level data, modeling exogenous variables in human capital formation through a heteroscedastic stochastic frontier approach. Specifically, a production function for tertiary education has been estimated with emphasis on…

It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…

While prior studies have examined the efficacy of career and technical education (CTE) courses on high school students' outcomes, there is little knowledge on timing of these courses and a potential link to student outcomes. We asked if the timing of these courses predicted differences in the likelihood of dropout and on-time high school…

Although the importance of primary schools in the long term is of interest in educational effectiveness research, few studies have examined the long-term effects of schools over the past decades. In the present study, long-term effects of primary schools on the educational positions of students 2 and 4 years after starting secondary education are…

With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…

Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…

We use data from Washington State to examine two stages of the teacher pipeline: the placement of prospective teachers into student teaching assignments and the hiring of prospective teachers into their first teaching positions. We find that prospective teachers are likely to complete their student teaching near their college and hometowns but…

We use data from Washington State to examine two stages of the teacher pipeline: the placement of prospective teachers in student teaching assignments; and the hiring of prospective teachers into their first teaching positions. We find that prospective teachers are likely to complete their student teaching near their college and hometowns, but…

The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…

Authors of previous research have reported that U.S. English language learner (ELL) students participate in school-sponsored music ensembles (band, orchestra, and choir) at a lower rate than their native-English-speaking peers (non-ELLs). The current study examined this phenomenon using a nationally representative sample of U.S. 10th graders (14-…

We use data from Washington State to examine two distinct stages of the teacher pipeline: the placement of prospective teachers in student teaching assignments; and the hiring of prospective teachers into their first teaching positions. We find that prospective teachers are likely to complete their student teaching near their college and…