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New CIC publication explores the intersection between big data and education

Using causal models to bridge the divide between big data and educational theory

By Kirsty Kitto, Ben Hicks and Simon Buckingham Shum. 

Available via the British Journal of Educational Technology (https://bera-journals.onlinelibrary.wiley.com/doi/10.1111/bjet.13321)

Published: 2023

Photo by Claudio Schwarz on Unsplash

The following abstract is extracted from the publication.

With the proliferation of data in educational settings it is becoming even more important to ensure analytical results are grounded in reality. Ideally we would like to embed our theoretical concepts from the learning sciences in our data products in order to facilitate trust and interpretability. But getting from a well described theory to a theory formal enough to be operationalised using methods from Artificial Intelligence and Learning Analytics can be challenging. A new paper, Using causal models to bridge the divide between big data and educational theory, from CIC, outlines how causal models may help bridge this gap between our scientific knowledge and the applications of big data. The paper also introduces the causal modelling apparatus and explores how it may offer new insights to the field of Learning Analytics.

You can find out more about this publication by emailing the Connected Intelligence Centre (cic@uts.edu.au).

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