Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

Educational data mining is an emerging interdisciplinary research area involving both education and informatics. It has become an imperative research area due to many advantages that educational institutions can achieve. Along these lines, various data mining techniques have been used to improve learning outcomes by exploring large-scale data that…

As we examine the pandemic's impact on higher education, we can see that many previously traditional teaching and learning frameworks have been invalidated, and the need for new teaching and learning approaches has increased. This indicates that the traditional frameworks for higher education may no longer be effective. Consequently, there is a…

This quantitative, causal-comparative study aims to examine the academic performance of all third-grade students who participated in after-school tutoring from English Language Arts (ELA) in comparison to those who did not, using the results from the 2022-2023 Mississippi Academic Assessment Program English Language Arts (MAAP ELA) assessment. The…

Purpose: This paper defines and assesses student learning patterns under the influence of problem-based learning (PBL) and their classification into a reasonable minimum number of classes. Study utilizes PBL implemented in an undergraduate Statistics and Operations Research course for techno-management students at a private university in India.…

The continual use of suspension and expulsion remains an unsettling concern for many educational stakeholders. With some guidance from the federal government, states have begun to address the issue of discipline disproportionality through policy reform that restrict the use of suspension and expulsion for certain student groups (e.g.,…

This paper examines performance differences among demographic groups on the ETS Major Field Test in Business. The study employs the Blinder-Oaxaca decomposition technique to analyze the test score differentials by gender and racial minority status. This technique decomposes the difference into two parts: an endowment effect (or explained portion)…

As institutions cope with the difficult task of managing scarce resources to support student learning, college writing centers, like other student services, need to be able to articulate and, at times, quantify the benefits they offer the populations they serve. This study examined outcomes associated with visiting the writing center at one…

Despite the increasing awareness of basic needs insecurity and its adverse impacts on students' academic achievement and wellbeing, the racial and social inequities in these experiences remain a critical issue requiring scholarly attention. Using the #RealCollege Survey Dataset, this study investigates the prevalence of basic needs insecurity…

Using data from 11 institutions, the authors investigate enrollments in intermediate microeconomics to determine characteristics of successful and unsuccessful students and follow the retake behavior of unsuccessful students. Successful students are significantly different from unsuccessful ones, and unsuccessful students differ by type…

Choosing a major field of study is important, and so is the selection of a specialized concentration that is aligned with an individual's career aspirations. In this paper, we explore a relatively newer concentration in the area of business, namely business analytics. The field of analytics has seen a rapid growth in recent years and enrollment in…

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…

This study attempts to predict secondary school students' performance in English and Mathematics subjects using data mining (DM) techniques. It aims to provide insights into predictors of students' performance in English and Mathematics, characteristics of students with different levels of performance, the most effective DM technique for students'…

The importance of family background in determining a student's academic achievement has long been acknowledged by researchers. Nonetheless, the effect of schooling on this relationship has also been widely investigated. Some studies have shown that family background plays a far stronger role while the effect of schooling is minimal; others have…

The technological capacity that now exists to gather and store large amounts of data has improved access to information related to the academic performance, demographic profile and welfare needs of young people in a school. Improvements in data management techniques, statistical data analysis and software packages have made retrieving and…