Background: Randomized controlled trials (RCTs) give unbiased estimates of average effects. However, positive effects for the majority of students may mask harmful effects for smaller subgroups, and RCTs often have too small a sample to estimate these subgroup effects. In many RCTs, covariate and outcome data are drawn from a larger database. For…

Accelerating advancements in learning analytics and artificial intelligence (AI) offers unprecedented opportunities for improving educational experiences. Without including students' perspectives, however, there is a potential for these advancements to inadvertently marginalize or harm the very individuals these technologies aim to support. This…

This work focuses on simulation, design, development, and evaluation of a visual Learning Analytics (LA) tool -- Real-time Educational AI-powered Classroom Tool (REACT) -- to support educators' data-driven decision-making. The educational institutions face one of the biggest challenges, such as predicting student performance, detecting undesirable…

Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…

This study investigates current approaches to learning analytics (LA) dashboarding while highlighting challenges faced by education providers in their operationalization. We analyze recent dashboards for their ability to provide actionable insights which promote informed responses by learners in making adjustments to their learning habits. Our…

Educational analytics tend toward aggregation, asking what a "normative" learner does. In "The Left Hand of Data," educational researchers Matthew Berland and Antero Garcia start from a different assumption--that outliers are, and must be treated as, valued individuals. Berland and Garcia argue that the aim of analytics should…

The main goal of learning analytics and early detection systems is to extract knowledge from student data to understand students' trends of activities towards success and risk and design intervention methods to improve learning performance and experience. However, many factors contribute to the challenge of designing and building effective…

Artificial intelligence and data analysis (AIDA) are increasingly entering the field of education. Within this context, the subfield of learning analytics (LA) has, since its inception, had a strong emphasis upon ethics, with numerous checklists and frameworks proposed to ensure that student privacy is respected and potential harms avoided. Here,…

Recent negotiations of 'data' in schools place focus on student assessment and NAPLAN. However, with the rise in artificial intelligence (AI) underpinning educational technology, there is a need to shift focus towards the value of teachers' digital data. By doing so, the broader debate surrounding the implications of these technologies and rights…

In celebrating the 20th anniversary of the "International Journal of Educational Technology in Higher Education (IJETHE)," previously known as the "Revista de Universidad y Sociedad del Conocimiento (RUSC)," it is timely to reflect upon the shape and depth of educational technology research as it has appeared within the…

Using data to understand learning and improve education has great promise. However, the promise will not be achieved simply by AI and Machine Learning researchers developing innovative models that more accurately predict labeled data. As AI advances, modeling techniques and the models they produce are getting increasingly complex, often involving…