Data showing what students earn after attending higher education institutions have become increasingly available, bolstering calls from policymakers and advocates that government financial aid programs should be tied to those outcomes. Often overlooked, however, is that these data and policies usually reflect the earnings of only students who…

Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…

This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…

Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…

This quantitative based applied research study examined data collected fromstudents who have withdrawnfromor completed aneducator preparation program (EPP) ina small rural public community college in WestVirginia. This study compared studentretention rates with Frontier andRemote (FAR) designation by home zip code. These data informedthe research…

With technological advances, distance education has been frequently discussed in recent years. The learning environments used in this course usually generates a great deal of data because of the large number of students and the various tasks involving their interaction. In order to facilitate the analysis of the data, the authors researched to…

Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environment by exploring and utilizing educational data using machine learning and data mining techniques.…

Situated in the northwestern corner of Ohio, Bowling Green State University (BGSU) is reengaging adult students with "some college, but no degree" (SCND), promoting equitable attainment, and improving students' workforce outcomes. BGSU is a residential four-year university with a vibrant campus culture, NCAA Athletics, and over 200…

A significant amount of research has gone into predicting student performance and many studies have been conducted to predict why students drop out. A variety of data including digital footprints, socio-economic data, financial data, and psychological aspects have been used to predict student performance at the test, course, or program level.…

This study presents a systematic review of the literature on the predicting student retention in higher education through machine learning algorithms based on measures such as dropout risk, attrition risk, and completion risk. A systematic review methodology was employed comprised of review protocol, requirements for study selection, and analysis…

This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…

In the world of technology, tools and gadgets, a huge amount of data is produced every second in applications ranging from medical science, education, business, agriculture, economics, retail and telecom. Higher education institutes play an important role in the overall development of any nation. For the successful operation of these institutions,…

The measurement of student performance during their progress through university study provides academic leadership with critical information on each student's likelihood of success. Academics have traditionally used their interactions with individual students through class activities and interim assessments to identify those "at risk" of…

Nowadays, the virtual learning environment has become an ideal tool for professional self-development and bringing courses for various learner audiences across the world. There is currently an increasing interest in researching the topic of learner dropout and low completion in distance learning, with one of the main concerns being elevated rates…

This paper analyses how three European countries produce and use data within a specific educational policy field, that of school leaving and graduation. It compares how stakeholders in England, Finland and the Netherlands know what happens to the leavers from schools and universities. Through gathering evidence about the methodological…