The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…

Because studies examining youth drug use often have data with a high proportion of zeros, they often do not meet the assumptions for univariate or linear regression analyses that are typically used. We demonstrate the use of zero-inflated negative binomial regression models to address excessive zeros in drug use frequency on perceptions of…

How important are learning strategies or personal attributes for learning outside of domain-specific knowledge or twenty-first-century transversal skills when predicting academic success in higher education? To address this question, we conducted a longitudinal study among 1,681 students at one of the leading universities in Hungary. Students took…

Objective: The purpose of this research study is to examine the use of the Andersen Behavioral Model of Health Services Use in predicting how health impacts the academic performance of college students through predisposing, enabling, and need factors. Participants: Data were collected from 428 college students attending a large university in the…

The aim of the study is to identify variables that explain students' academic performance, determine their relative importance, and consequently, develop an index to distinguish advantaged and disadvantaged schools in pursuit of educational equality. By using this index, we intend to build a model for evaluating schools' overall performance based…

This paper introduces a novel approach to identify at-risk students with a focus on output interpretability through analyzing learning activities at a finer granularity on a weekly basis. Specifically, this approach converts the predicted output from the former weeks into meaningful probabilities to infer the predictions in the current week for…

This paper analyzes the dataset collected from students participating in the Boy With A Ball (BWAB) program, a faith-based community outreach group, through the Hemingway Measure of Adult Connectedness©, a questionnaire measuring the social connectedness of adolescents. This paper first approaches the data in the conventional method provided by…

This paper will demonstrate how we used state-level longitudinal data to model reading growth trajectories. Using data from large scale assessments that were vertically linked across grades in Hawaii, we utilized a multilevel regression framework to develop growth models to study students' reading performance trajectories during their elementary…

Purpose: This study aims to investigate the feasibility of developing general predictive models for using the learning management system (LMS) data to predict student performances in various courses. The authors focused on examining three practical but important questions: are there a common set of student activity variables that predict student…

Purpose: We aim to identify the most accurate model for predicting adolescent (Grade 9) reading difficulties (RD) in reading fluency and reading comprehension using 17 kindergarten-age variables. Three models (neural networks, linear, and mixture) were compared based on their accuracy in predicting RD. We also examined whether the same or a…

Guided by Astin's I-E-O model and critical quantitative inquiry, we examined institutional environments that contributed to belongingness, especially for students from different racial groups, college generation statuses, and the intersection of both. Using multiple linear regression analyses, we analyzed data from 7,888 students and found that…

Improving graduation rates is one of the biggest missions in many universities across the country and it is surely the case on the campus of this institution. The work here presents a statistical tool box to use early academic performance as a predictor for graduation with logistic regression and machine learning techniques. The methods described…

With the increasing adoption of Learning Management Systems (LMS) in colleges and universities, research in exploring the interaction data captured by these systems is promising in developing a better learning environment and improving teaching practice. Most of these research efforts focused on course-level variables to predict student…

The purpose of this research was to examine the relationship between selected factors from two of the domains within the Socio-Ecological Outcomes (SEO) model as defined by Wood and Harris (2013) and African American male community college students' academic success. Namely, this study assessed whether any relationships existed among the selected…

Liberal Arts programs are often characterized by their open curriculum. Yet, the abundance of courses available and the highly personalized curriculum are often overwhelming for students who must select courses relevant to their academic interests and suitable to their academic background. This paper presents the course recommender system that we…