Peter Goodyear

In 2010 Professor Goodyear became the first Australian Laureate Fellow in the area of learning technology and the learning sciences. His $3 million Laureate research program focuses on the analysis of effective learning networks – including networks of people who are sharing experiences in the management of their own health conditions.

Professor Goodyear is a learning scientist whose research investigates how people come to understand complex phenomena and how they learn to make significant changes in their lives and in their environment. He also carries out research on the ways in which digital technologies can be designed to support complex learning and collaborative work.

Of particular interest to Professor Goodyear is how people learn to combine different areas of specialist knowledge and different ways of knowing. This is directly relevant to understanding how professionals from different disciplines collaborate to solve complex problems, how trainee professionals learn to combine theory and practice, and how professionals and their clients achieve shared understanding.

In Australian Research Council-funded work with his colleague in the Faculty of Education and Social Work, Dr Lina Markauskaite, he has shown how the application of theoretical knowledge in practice-based learning (e.g. internships, practical experiences) can be modelled as the activation and reintegration of specific sets of mental resources and the blending of conceptual frames. This explains why some forms of knowledge integration-combining ideas from different sources - are easier than others.

With Dr Rob Ellis, Professor Michael Prosser and others, Professor Goodyear has been mapping the various ways in which users of digital technology think about its application for learning purposes. Contrary to current beliefs about the tech-savvy 'net generation', this research shows that many young people have not mastered effective ways of using the Internet for learning purposes.

This research ties in with the work of the centre by helping us to understand and improve processes of inter-disciplinary research collaboration, inter-professional education and knowledge translation. It also helps with the design of effective learning networks – crucial to the Centre's ability to interact with end-users and beneficiaries of its research.