Learning Analytics refers to the collection and analysis of student and teacher data for the purposes of improving learning and teaching.
It's about capturing, analysing and representing a variety of data to support students, teachers and institutions in adapting their practice/behaviours in order to be more effective. Learning Analytics is often associated with analysing student interactions with online learning systems, like CSU's Interact2.
Learn more about Learning Analytics at CSU.
Learn more about applying Learning Analytics in learning and teaching.
Learn more about Learning Analytics generally.
CSU's Learning Analytics activities are governed by our Code of Practice.
The Code of Practice is ourFramework for lawful and ethical practice in Learning Analytics. It establishes rules and limitations on the use of Learning Analytics by CSU.
The Code of Practice is supported by two important documents:
The Learning Analytics Code of Practice also operates in conjunction with the CSU Privacy Management Plan.
Learn more about making an inquiry or complaint under the Learning Analytics Code of Practice.
CSU seeks to foster multi-disciplinary research in Learning Analytics. We believe there are substantial opportunities for research and innovation in bringing together educationalists and learning scientists, computer scientists (especially those working in the areas of machine learning and AI), data scientists, psychologists and others.
Interested researchers should connect with our Learning Analytics Research Network.
If you would like to discuss Learning Analytics @ CSU further, please contact:
Dr Cassandra Colvin
Int Ph: 19848
Director, Learning Technologies:
Associate Professor Philip Uys
Int Ph: 57501