learning analytics

Algorithms are increasingly being used to make decisions that have a lasting impact on our current and future lives. There is a growing public awareness that algorithms, especially those used in forms of artificial intelligence, need to be understood as raising issues of fairness. But while everyone may have a vernacular understanding of what is fair or unfair, when algorithms are used numerous trade-offs are involved.

In the CiteLearn project, funded by Wikicred, we are developing a tool to support people in learning a key skill of verifiability, to support the writing and flow of credible information.

Our cutting-edge research in education leads the way in productive and ethical use of data and technology in classrooms. Drawing from the fields of learning analytics, educational data mining, and artificial intelligence in education, the core focus of the research strand is in the integration and implementation of technology to improve teaching and learning practices.

This question is central to work being undertaken by colleagues at UTS and internationally. Evidence and data are increasingly emphasised in educational contexts, with the spread of What Works centres such as the Educational Endowment Foundation (UK), Evidence for Learning (Australia), the What Works Clearinghouse (USA), international (PISA), national (SATS, NAPLAN, etc.

Data big and small have come to education, from creating online platforms to increasing standardised assessments. shutterstock Simon Knight, University of Technology Sydney and Simon Buckingham Shum, University of Technology Sydney