What if student attrition was treated like an illness? An epidemiological model for learning analytics
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Learning analytics is a technology on the rise in higher education. Adapted from business analytics, this approach is being used to track and predict student engagement and success in higher education. There is evidence to suggest that learning analytics can be successfully used to predict students at risk of failing or withdrawing and allow for the provision of just in time intervention. Despite this, the output of universities is not like that of other commercial ventures and business models for understanding consumer behaviour, for instance, are not equipped for accurate prediction of learning outcomes. The model presented in this poster is an attempt to create a predictive framework for =learning health' from a multifaceted, epidemiological perspective. The model serves as a framework for understanding early student success at the micro and macro levels and provides a foundation for evidence-based use of learning analytics within a higher education perspective.
ASCILITE 2011: Changing Demands, Changing Directions
Copyright 2011 ASCILITE. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
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