Like learning analytics, physics education research is a relatively young field that draws on perspectives from multiple disciplines. Network analysis has an even more heterodox perspective, with roots in mathematics, sociology, and, more recently, computer science and physics. This paper reviews how network analysis has been used in physics…

Monitoring students' academic progress is vital for ensuring timely completion of their studies and supporting at-risk students. Educational Data Mining (EDM) utilizes machine learning and feature selection to gain insights into student performance. However, many feature selection algorithms lack performance forecasting systems, limiting their…

The General Data Protection Regulation (GDPR) in the European Union contains directions on how user data may be collected, stored, and when it must be deleted. As similar legislation is developed around the globe, there is the potential for repercussions across multiple fields of research, including educational data mining (EDM). Over the past two…

Personalized education--the systematic adaptation of instruction to individual learners--has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when…

This commentary discusses how research approaches from Cognitive Network Science can be of relevance to research in the field of Learning Analytics, with a focus on modelling the knowledge representations of learners and students as a network of interrelated concepts. After providing a brief overview of research in Cognitive Network Science, I…

Recently, discovering learner behaviour has taken more attention in the field of e-learning. It aims to gain useful insights into the learning process of students despite the absence of direct interaction with teachers. In fact, the only available source of information in such environments is the log file that represents all possible interactions…

Lecture Capture (LC) material is accepted to be an available and accessible resource for students in universities across the world. This exploratory study investigates the "when viewing" LC material engagement of accounting undergraduate students. Three categories of engagement are defined, Near-Event-Viewing (NEV), Get-Round-to-Viewing…

Which learning analytics (LA) approach might be the best choice for your teaching and learning context? Learning analytics as a field of research and application seeks to collect, analyze, report, and interpret educational data with the goal of improving teaching and learning. But hasty adoption of learning analytics tools and methods that are…

The interactive learning is a continuous process, which is full of a large number of learning interaction activities. The data generated between learners and learning interaction activities can reflect the online learning behaviors. Through the correlation analysis among learning interaction activities, this paper discusses the potential…

Past research has yielded ample knowledge regarding the design of analytics-based tools for teachers and has found beneficial effects of several tools on teaching and learning. Yet there is relatively little knowledge regarding the design of tools that support teachers when a class of students uses AI-based tutoring software for self-paced…

Ethical issues are structurally present in the design and choice of data; the interaction between problem, model, and intervention; and the scientism that supports data analytics' claims to authority. In this chapter, I argue against three social assumptions behind common implementations of learning analytics: data realism, technological…

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…

Effective learning outcome modeling is crucial to the success of learning evaluation in education. In the digital age, the movement towards online learning and computerized assessments has resulted in an explosion of structured and unstructured educational data (e.g., learners' problem-solving process data), which offers new opportunities for…

Amidst ongoing technological and social change, this article explores the implications for critical education that result from a data-driven model of digital governance. The article argues that traditional notions of critique which rely upon the deconstruction and analysis of texts are increasingly redundant in the age of datafication, where the…

Although an increasing number of ethical data science and AI courses is available, with many focusing specifically on technology and computer ethics, pedagogical approaches employed in these courses rely exclusively on texts rather than on algorithmic development or data analysis. In this paper we recount a recent experience in developing and…