Dreaming of Electric Sheep

CSU’s Vision for Analytics- Driven Adaptive Learning and Teaching


  • Simon Welsh
  • Philip Uys




Learning Analytics, Adaptive Learning;, Inductive, Deductive, Analytics Strategy, Organisational Design, Student Success, Personalised Learning, Online Learning


Current institutional approaches to Learning Analytics which focus on student risk and engagement are problematic in terms of their ability to support improved student learning and success outside of retention. Charles Sturt University’s (CSU’s) deductive work on defining its institutional model of Learning Analytics has led it to reconfigure its Learning Analytics activities into an Adaptive Learning and Teaching program. Adaptive Learning and Teaching is defined as any educational approach that utilises feedback or analytics on student learning to adapt content, teaching, systems and/or design to enhance learning effectiveness. A key feature of the CSU vision is to focus analytic processes on students’ representations of knowledge and integrate with the student “digital footprint” to provide real-time adaptation of online learning experiences and personalise online learning. Concurrently, CSU’s Adaptive Learning and Teaching Services team is working to build capability in using Learning Analytics to inform adaptation in learning and teaching practices.