Many educational institutions are using predictive models to leverage actionable insights using student data and drive student success. A common task has been predicting students at risk of dropping out for the necessary interventions to be made. However, issues of discrimination by these predictive models based on protected attributes of students…

Predicting and improving the academic achievement of university students is a multifactorial problem. Considering the low success rates and high dropout rates, particularly in open education programs characterized by mass enrollment, academic success is an important research area with its causes and consequences. This study aimed to solve a…

In recent years, initiatives and the resulting application of precision education have been applied with increasing frequency in Taiwan; the accompanying discourse has focused on identifying potential applications for artificial intelligence and how to use learning analytics to improve teaching quality and learning outcomes. This study used the…

This cluster-randomised study investigated the effects of a Norwegian early warning system, the IKO model. IKO is a Norwegian acronym for identification, assessment, and follow-up, and the model aims to improve schools' abilities to identify and support students who are at risk of dropping out during the school year. The study involved 7677…

"Education is the key to success," one of the most heard motivational statements by all of us. People engage in education at different phases of our lives in various forms. Among them, university education plays a vital role in our academic and professional lives. During university education many undergraduates will face several…

Quality early childhood education and care has been the focus of interest of researchers for over half a century. Approaches to the quality monitoring and quality assurance of early childhood education and care, as well as its conceptualisation and operationalisation, have changed and developed over the decades in line with contemporary…

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 article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…

School dropout is a structural problem which permanently penalizes students and society in areas such as low qualification jobs, higher poverty levels and lower life expectancy, lower pensions, and higher economic burden for governments. Given these high consequences and the surge of the problem due to COVID-19 pandemic, in this paper we propose a…

Purpose: This study aims to investigate the feasibility of developing general predictive models for using the learning management system (LMS) data to predict student performances in various courses. The authors focused on examining three practical but important questions: are there a common set of student activity variables that predict student…

This paper examines ideas about mental health, wellbeing and school education to illustrate important issues in the relationship between mental health and education. The COVID crisis has amplified the pre-existing mental health problems of children and young people in England and recognition of the opportunities in schools to address these. The…

Over the last decade, there has been great research interest in the application of artificial intelligence (AI) in various fields, such as medicine, finance, and law. Recently, there has been a research focus on the application of AI in education, where it has great potential. Therefore, a systematic review of the literature on AI in education is…

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…

Tackling early leaving from education and training (ELET) is one of the headline targets for education policy in the European Union. Although ELET rates have been decreasing in most member states, male, socially disadvantaged and immigrant students remain overrepresented in ELET figures. Moreover, students in vocational tracks and students who…

Developing a sufficient level of writing proficiency takes time. It is also a complex skill difficult to measure. The history of writing assessments reveals changing views of construct validity, reliability and interpretation of results. This study used a binary logistic regression model with seven years of grades 3 to 12 annual direct writing…