Learning analytics (LA) involves the measurement, collection, analysis, and reporting of data about learners and their contexts, aiming to understand and optimize both the learning process and the environments in which it occurs. Among many themes that the LA community considers, natural language processing (NLP) algorithms have been widely…

Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…

Digital footprints (DF) offer relevant information about educational activities and processes related to strategies of academic assessment, identification of skills and psychological traits of students, and permanence and dropout trends, etc. This study analyzes scientific evidence on the use of DF in education, and shows the results of a…

LearnSphere is a web-based data infrastructure designed to transform scientific discovery and innovation in education. It supports learning researchers in addressing a broad range of issues including cognitive, social, and motivational factors in learning, educational content analysis, and educational technology innovation. LearnSphere integrates…

Generative Artificial Intelligence (GenAI) is transforming education, with assessment design emerging as a crucial area of innovation, particularly in computer science (CS) education. Effective assessment is critical for evaluating student competencies and guiding learning processes, yet traditional practices face significant challenges in CS…

Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…

Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…

Digital data are transforming higher education (HE) to be more student-focused and metrics-centred. In the UK, capturing detailed data about students has become a government priority, with an emphasis on using student data to measure, compare and assess university performance. The purpose of this paper is to examine the governmental and commercial…