The world's move to a global economy has an impact on the high rate of student academic failure. Higher education, as the affected party, is considered crucial in reducing student academic failure. This study aims to construct a prediction (predictive model) that can forecast students' time to graduation in developing countries such as Indonesia,…

Completion of remedial mathematics has been identified as one of the keys to college success. However, completion rates in remedial mathematics have been low and are of much debate across America. This study leverages machine learning techniques in trying to predict and understand completion rates in remedial mathematics. The purpose of this study…

This article will address predictors of success for online students. A survey questionnaire was used to gather data concerning online students' social and educational readiness levels at a four-year private university in the Midwestern United States. Of the 4,050 potential participants, 250 (6.23%) responded to the survey. Stepwise regression…

Higher education institutions face heightened accountability for student success. As such, higher education relies heavily on big data to predict student outcomes. This process is problematic because predictive models are developed on historical data, are deficit based, and are focused on student factors, neglecting institutional factors. The…

Predicting student's successful completion of academic programs and the features that influence their performance can have a significant effect on improving students' completion, and graduation rates and reduce attrition rates. Therefore, identifying students are at risk, and the courses where improvements in content, delivery mode, pedagogy, and…

This study investigates the alignment of a predictive model created to categorize first semester students by risk level of not completing their studies with the faculty identification of students displaying risk behaviours of the same cohort at Mohawk College. Data created by Finnie et al. (2017), is compared to a sample of first semester students…

Despite the overwhelming evidence that higher education data are nested at various levels, single-level techniques such as regression and analysis of variance are commonly used to investigate student outcomes. This is problematic as a mismatch in methodology and research questions can lead to biased parameter estimates. The purpose of this study…

In this study, a model on the high school students' school burnout was tested, and the model's prediction of retained and promoted students was investigated. The school burnout model, in this sense, included the variables of grade point average (GPA), school burnout, perceived social support, stress, perfectionism, academic procrastination, and…

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…

This study assessed the feasibility of using precollege success indicators to identify at-risk students at a large 4-year public research university in the Midwest. Retention data from students who participated in an established student success program were examined. The findings affirm that the initial admissions assessment identifying at-risk…

In this paper, we evaluate the complete undergraduate co-enrollment network over a decade of education at a large American public university. We provide descriptive and exploratory analyses of the network, demonstrating that the co-enrollment networks evaluated follow power-law degree distributions similar to many other large-scale networks; that…

The 1st step in successfully intervening with students who may fail a course is to identify them as early as possible in the semester. The objective of this study was to create a model to predict student performance in FDSC 4304, the required capstone Food Chemistry class, using academic performance in prerequisite courses as potential predictors.…

The purpose of this study was to use a comprehensive framework to examine academic, psychosocial, noncognitive, and other background factors that are related to retention at a large, public four-year institution in the southeastern United States. Specifically, the study examined what factors are most important in predicting first-to-second year…