Learner Engagement Analytics provides institutions with meaningful insights to support learners in achieving their academic goals while concurrently serving as a self-reflection tool for educators to inform their pedagogy and classroom practice.
Data analytics has become prevalent in various industries as it involves extracting and interpreting significant insights to improve decision-making efficacy. In recent times, the field of education research has also adopted this approach, particularly in higher education, which has led to the emergence of Learner Engagement Analytics (LEA). This has largely been driven by technological disruptions such as the adoption of online learning. Moreover, there is a significant emphasis on the role of higher education institutions in creating a conducive learning environment that empowers learners to achieve their academic potential.
LEA combines a range of data sources about student learning and engagement, which is captured from (but not limited to) learning management systems (e.g., Moodle, Blackboard), library and student attendance systems. This data is then analysed to gain insights into the learning experience of the learners and improve student retention rates by recognising learners who disengage in the early stages of their programme.
From an educator's perspective, the insights can inform their pedagogic approach, which can have a positive impact on the course/curriculum design and classroom practice.
Dr Usman Naeem is a Queen Mary Academy Fellow, where he is providing academic leadership to Queen Mary’s use of Learner Engagement Analytics (LEA), with specific responsibility for developing a strategy for and driving forward the uptake and enhancement of LEA.