Systems of learning across levels: from neural to social structures


January 13, 2014


Room CPD-3.28, Centennial Campus, The University of Hong Kong

Professor Liaquat Hossain, The University of Hong Kong

This keynote is part of Winter Institute 2014.


Network effects on individuals’ ability to learn better have been documented in studies based on communication, social psychology and mathematical sociology. Studies have shown that the locus of innovation is found in networks of learning, rather than in individuals, as it maintains appropriate access to knowledge and resources that are otherwise unavailable. A constructivist view of learning posits that learners learn and generate knowledge through interaction with others. Learners work together as peers, using their combined knowledge to find a solution to the problem. The communication that results from this combined effort provides learners with the opportunity to examine and refine their understanding in a continuous process. Aligning with the social network perspective of observing both individual and group outcomes, learning as a consequence of a network structure will be explored in different contexts to  reveal systems of learning across levels: from neural to social structures.

About the Speaker

Liaquat Hossain recently joined the Faculty of Education of HKU as a Professor in Information Management. From 2000 to 2013, he served as Director, Deputy Head, Sub and Associate Dean for Faculty of Engineering and IT at the University of Sydney. He has secured AU$10M in competitive research funding from 2014 EU FP 7, 2014 NHMRC-National Medical and Health Research Council Australia, 2011-2013 ARC Discovery, 2009-2013 CRC-Commonwealth Research Centre, and 2001-2004 ARDA Advanced Research Development Agency in the US. He has published over 160 peer reviewed research articles, of which 65 are papers in international peer reviewed journals, 82 in peer reviewed international conferences, 11 peer reviewed book chapters and 2 books. His publications appeared in journals in disciplines ranging from information sciences, computational science, knowledge management, decision support, behavioral sciences, network science, applied mathematics, statistical mechanics, environmental science, engineering management, complexity, physics, medicine and public health.