Human-Computer Interaction: Ergonomics and User Interfaces - Vol. 1

By Hans-Jörg Bullinger; Jürgen Ziegler | Go to book overview

Tasks and Situations: Considerations for
Models and Design Principles in Human
Computer Interaction

PeterJohnson
Department of Computer Science, Queen Mary & Westfield College
University of London, London E1 4NS
pete@dcs.qmw.ac.uk


1
Introduction

How do we design computer systems so that they are useful and efficient artefacts that improve the quality and productivity of our lives? What explanations can we offer as to why some systems achieve this and others fail? How can we predict a'priori which systems and system features are going to improve our lives and which ones will not? If we knew the answers to these questions then we would be in a better position to design and evaluate computer systems, and we would be developing an explanatory understanding of human computer interaction. I use the words explanatory understanding to differentiate such an account of human computer interaction from other, alternative, forms of account that seek purely to describe or to assess human computer interaction and interactive system designs, without giving any explanatory, causal account of how such interaction might have come about. In recent writings in human computer interaction and software engineering much attention has been given to ethnomethodological studies of human activity as either inputs to design or the analysis of peoples' use of design in the work place or elsewhere. I will argue that, while such accounts and approaches are useful, they are inadequate since they fail to provide any explanatory causal accounts as to how or why designs fail or succeed. Hence, they offer little in the way of guidance or principles for design. It is not the use of ethnomethodological approaches that I am dissatisfied with, far from it, I have long argued for the forms of observation, data collection and analysis that such approaches bring. It is the failure to recognise that a description is not an understanding and that causal explanations are needed to arrive at an understanding of what counts for good HCI. Further problems arise

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