This study aims to employ the supervised machine learning algorithms to examine factors that negatively impacted academic performance among college students on probation (underperforming students). We used the Knowledge Discovery in Databases (KDD) methodology on a sample of N = 6514 college students spanning 11 years (from 2009 to 2019) provided…

The study investigated the joint contribution of the self-regulated learning (SRL) and individual differences approaches to the prediction of university students' grade point average (GPA) obtained at three separate time points throughout their degree (3 years). We assessed cognitive (i.e., previous academic performance, cognitive ability, and…

Predictors of academic success at university are of great interest to educators, researchers and policymakers. With more students studying online, it is important to understand whether traditional predictors of academic outcomes in face-to-face settings are relevant to online learning. This study modelled self-regulatory and demographic predictors…

The present study examined demographic and academic predictors of astronomy performance among a cohort of N=1909 community college students enrolled in astronomy courses in a large suburban community college during a four-year time frame, 2015-2019. The theoretical framework was based upon a deconstructive approach for predicting community college…

In this paper, we study how well SAT scores, high school GPA, and undergraduate precalculus grades relate to undergraduate calculus grades at a 4-year private nonprofit university that does not have a placement exam. In addition, we compare the success in calculus of two groups of students, both of whom require two semesters to pass calculus. The…

Intelligent Tutoring Systems (ITS) are computer-based learning environments that aim to imitate to the greatest possible extent the behavior of a human tutor in their capacity as a pedagogical and subject expert. One of the major challenges of these systems is to know how to adapt the training both to changing requirements of all kinds and to…

Graduate admission has become critical for quality assurance. An innovative solution is needed to achieve efficiency and consistency in the admission process at institutions. However, the existing research is lack of a simple practical method for informed decision-making for admissions. We develop a multi-criteria decision-making (MCDM) model to…

In this longitudinal study, we investigate how demographic, cognitive and meta-cognitive variables affect students' success in chemistry and physics exams in two Science-Technology-Engineering-Mathematics undergraduate courses, biology and engineering. Independent variables include high school final examination performance, chemistry and physics…

This study introduces data mining methods to accounting education scholarship to explore the relationship between accounting students' current academic performance (grades), demographic information, pre-university entrance scores and predicted academic performance. It adopts a C4.5 classification algorithm based on decision-tree analysis to…

Structural equation modelling was used to investigate the predictive associations between kindergarten developmental, socio-behavioural, and biotic influences on third grade achievement among a nationally representative sample of low-SES children. The findings validate the understanding that developmental and learning trajectories start early in…

Over the past decade, low graduation and retention rates have plagued higher education institutions. To help students graduate on time and achieve optimal learning outcomes, many institutions provide advising services supported by educational technologies. Accurate grade prediction is an integral part of these services such as degree planning…

This study examines the effect of race/ethnicity, immigrant status and the role of school belonging on the academic achievement of Mexican, Filipino, and white students. We focus on school belonging and peer influences in concert with immigrant generational status and family income to predict students' academic achievement at the end of 9th grade.…

Education systems produce a large number of valuable data for all stakeholders. The processing of these educational data and making studies on the future of education based on the data reveal highly meaningful results. In this study, an insight was tried to be developed on the educational data collected from ninth-grade students by using data…

In this study, we examine children's National Assessment Program--Literacy and Numeracy (NAPLAN) achievement predictors, which may enable or limit their numeracy performance and assess the relative importance of the predictor variables. Our data source was the NAPLAN numeracy results of Queensland schools from 2014 to 2017. Years 3 and 5…

A successful first year is of vital importance to academic achievement in higher education. How can we identify those students at risk at a very early stage, i.e. even before they have entered university? This study focuses on three pre-university factors, namely academic self-efficacy, self-regulated learning, in terms of autonomous motivation…