In light of increasing concerns about surveillance, higher education institutions (HEIs) cannot afford a simple paternalistic approach to student data. Very few HEIs have regulatory frameworks in place and/or share information with students regarding the scope of data that may be collected, analyzed, used, and shared. It is clear from literature…

This paper details the anticipated impact of synthetic "big" data on learning analytics (LA) infrastructures, with a particular focus on data governance, the acceleration of service development, and the benchmarking of predictive models. By reviewing two cases, one at the sector-wide level (the Jisc learning analytics architecture) and…

This commentary reflects on the contributions to learning analytics and theory by a paper that describes how multiple theoretical frameworks were woven together to inform the creation of a new, automated discourse analysis tool. The commentary highlights the contributions of the original paper, provides some alternative approaches, and touches on…

Designing, validating, and deploying learning analytics tools for instructors or students is a challenge that requires techniques and methods from different disciplines, such as software engineering, human-computer interaction, computer graphics, educational design, and psychology. Whilst each has established its own design methodologies, we now…

This paper identifies some of the main challenges of data governance modelling in the context of learning analytics for higher education institutions, and discusses the critical factors for designing data governance models for learning analytics. It identifies three fundamental common challenges that cut across any learning analytics data…

Academic analytics and learning analytics have been increasingly adopted by academic institutions of higher learning for improving student performance and retention. While several studies have reported the implementation details and the successes of specific analytics initiatives, relatively fewer studies exist in literature that describe the…

With the continued adoption of learning analytics in higher education institutions, vast volumes of data are generated and "big data" related issues, including privacy, emerge. Privacy is an ill-defined concept and subject to various interpretations and perspectives, including those of philosophers, lawyers, and information systems…

The Open Academic Analytics Initiative (OAAI) is a collaborative, multi-year grant program aimed at researching issues related to the scaling up of learning analytics technologies and solutions across all of higher education. The paper describes the goals and objectives of the OAAI, depicts the process and challenges of collecting, organizing and…

A core goal for most learning analytic projects is to move from small-scale research towards broader institutional implementation, but this introduces a new set of challenges because institutions are stable systems, resistant to change. To avoid failure and maximize success, implementation of learning analytics at scale requires explicit and…

The disconnect between data collection and analysis across academic and administrative units within institutions of higher education makes it challenging to incorporate diverse data into curricular design. Understanding the factors related to student retention and success is unlikely to occur by focusing on only one unit at a time. By promoting…