This systematic literature review investigates the fairness of machine learning algorithms in educational settings, focusing on recent studies and their proposed solutions to address biases. Applications analyzed include student dropout prediction, performance prediction, forum post classification, and recommender systems. We identify common…

Each year, when GCSE and A level results are published, a common talking point in media coverage is how results of male and female students differ. This reflects a popular fascination with such differences, but there is also a deeper, longstanding research interest in sex differences in education, not just in England, but around the world.…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…

Early alert systems (EAS) are an important technological tool to help manage and improve student retention. Data spanning 16,091 students over 156 weeks was collected from a regionally based university in Australia to explore various microeconometric approaches that establish links between EAS and student retention outcomes. Controlling for…

Higher education institutes are increasingly turning their attention to web-based learning management systems. The purpose of this study is to investigate whether data collected from LMS can be used to predict student performance in classrooms that use LMS to supplement face-to-face teaching. Data was collected from eight courses spread across two…

As the demand for lifelong learning increases, many working adults have turned to online graduate education in order to update their skillsets and pursue advanced credentials. Simultaneously, the volume of data available to educators and scholars interested in online learning continues to rise. This study seeks to extend learning analytics…

Recognizing that children's learning outcomes generally remain low, in its recent 2017--2021 Education and Skills Sector Plan (ESSP) the Government of Zambia prioritized improving learning outcomes through strategies that addressed gaps in education system quality, access, equity and efficiency. What resources and contextual factors are associated…

The aim of this study is to identify online learning behavior that is excessively intense as reflected in a student's overly frequent interaction with the instructor through various communication channels. Then, this study aims to use learning analytics methodologies to discover whether a student with the identified behavior also displays the same…

"Advances in Accounting Education" is a refereed, academic research publication whose purpose is to help meet the needs of faculty members and administrators who are interested in ways to improve teaching, learning and curriculum development in the accounting area at the college and university level. We publish thoughtful, well-developed…