As the field evolved, more sophisticated methods for statistical modelling of network dynamics and formation were used to further examine the nature of social mechanisms that drive the formation of social networks among students and the factors that influence the formation of student social networks across various formal and informal learning settings.

In short, learning analytics increases the quality and quantity of feedback loops in the education system for teachers, learners and administrators.

The growth of online and distance education further contributed to the development of learning analytics

Learning analytics draws on theories and methods from machine learning and data science, education, cognitive psychology, statistics, computer science, neuroscience, and social and learning sciences to name but a few

learning analytics can assist in providing personalised and timely assessment and feedback at scale to large-sized classes.

learning analytics as the “measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs”

This article provides an overview of this journey, critically reflecting on the existing research, providing insights into the recent advances, and discussing the future of the field, positioning learning analytics within the broader agenda of systems thinking as means of advancing its institutional adoption.

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