Higher Education Research and Development Society of Australasia
John Biggs has made a distinguished contribution to teaching and learning, academic development and the higher education community in Australia and internationally. John was born in Hobart, Tasmania, where he studied and gained his first degree in the 1950s in psychology. John completed his doctoral studies at the University of London in the 1960s and held faculty positions in Australia, Canada, United Kingdom, and Hong Kong. His final institutional affiliation is Honorary Professor of Psychology at the University of Hong Kong. In 2017
John was invested as a Member of the Order of Australia (AM) in recognition of his “significant service to tertiary education, particularly in the fields of curriculum development and assessment”.
John’s earlier work was focused on the education of schoolteachers through his seminal work ‘The Process of Learning’ and subsequent editions, first written in the 1980s. A textbook authored by an Australian, for Australian teachers was deeply researched and accessibly written for student teachers and scholars of learning alike. John’s approach was unique at the time for it aimed to provide teachers with an understanding for making informed practical decisions, as distinct to elaborating psychological theories, which was typical for the Educational Psychological texts at the time. The ‘Process of Learning’ was deservedly the text of choice by the majority of Australian university teacher education programs for over a decade and helped shape our understanding of student learning and teachers’ practice and on which others have continued to build.
At this same time, John was developing the Student Approaches to Learning model and Questionnaire which continues to be widely used in schools and universities and has been validated in numerous confirmatory studies around the world in many different cultural settings. He personally extended this work in exploring the Chinese learner and contributed to deepening our knowledge of the ways in which Student Approaches to Learning was evident in Chinese and Confucius heritage countries. This is now taken for granted knowledge and underpins current texts and the work of other educational psychologists’ understanding student learning.
In the higher education arena, John’s conceptualisation and practical application of his outcomes approach to teaching coined as ‘constructive alignment’ has been equally significant. John again wrote a book to capture the theoretical and conceptual work, drawing on the empirical research that provided the basis of the model, weaving throughout the practical applications for university teachers. ‘Teaching for Quality Learning at University’ quickly became the textbook of choice for university teachers and professional development courses internationally. It is now in its fourth edition and is co-authored with Catherine Tang.
John’s contribution is more than as an author and of these highly influential conceptual models. He has worked in several countries demonstrating how these models can be applied by individuals and as a systemic, whole-of-institutions approach. There would not be a university curriculum design model that does not now specify ‘constructive alignment’. University executives and individual teachers alike use the term in what has become a shared understanding of its importance for structuring all aspects, from the formal curriculum, assessment, teaching and learning activities and learning environment in the service of the students’ learning experience.
These examples only touch on the influence John has had on higher education internationally and individuals he has mentored and generously supported. The HERDSA community and the higher education community more broadly has greatly benefited from his sustained intellectual and personal contribution as a researcher, author, teacher and colleague. HERDSA recognises and acknowledges John’s contribution to our knowledge and practice of teaching and for his challenge to us to always focus on students and their learning.