A Comparison of Learning Analytics Frameworks: a Systematic Review

Abstract

While learning analytics frameworks precede the official launch of learning analytics in 2011, there has been a proliferation of learning analytics frameworks since. This systematic review of learning analytics frameworks between 2011 and 2021 in three databases resulted in an initial corpus of 268 articles and conference proceeding papers based on the occurrence of “learning analytics” and “framework” in titles, keywords and abstracts. The final corpus of 46 frameworks were analysed using a coding scheme derived from purposefully selected learning analytics frameworks. The results found that learning analytics frameworks share a number of elements and characteristics such as source, development and application focus, a form of representation, data sources and types, focus and context. Less than half of the frameworks consider student data privacy and ethics. Finally, while design and process elements of these frameworks may be transferable and scalable to other contexts, users in different contexts will be best-placed to determine their transferability/scalability.