Using big data analytics to support online learning and teaching in higher education

Big Data is a concept that emgerged with the rapid growth of web-base technologies and computer and mobile devices. It indicates large and aggregated data sets that can be captured and stored (Manyika et al., 2011). Big Data analytics uses new technologies and skills to analyse the flow of information, and thereby, reveals hidden threads, trends and patterns in the data (Matteson, 2013). While Big Data analytics is having a wide impact on public health and businesses’ commercialisation and marketing, its application remains limited in higher education. Learning management systems used at universities can be a source of Big Data, as they often feature a wide array of materials which can be made publicly available. In this project, emerging Big Data analytic techniques and skills are adopted to analyse archived data from the web-based learning system, MyLO, used at the University of Tasmania. Data were collected, including online discussions and news items proposed by lecturers, to examine correlations between lecturers’ pedagogical approaches and student learning outcomes and engagement. The finding will be relevant to other universities who wish to use Big Data analytics to support online learning and teaching.