©1990, 1995	Thesis overview	General contents
Chapter 7 overview	Chapter 8 section list	Chapter 9 overview

Chapter 8: Overall interpretation of results, conclusions and directions

This chapter summarises the main findings of the study, also explaining the nature of the results, along with ideas about the work needed to make the results more general. Suggestions on overcoming the great remaining obstacles to applying this methodology to real tasks are put forward. This application could be to interface redesign, systems design, and training; and for operator support, we introduce the Guardian Angel paradigm, as a vision of what could eventually follow on from this work. Lastly, the implications for further work are explored. These focus around the idea of a new approach to rule induction, using a human-like context structure, which could be based on the principle of minimising the cognitive requirements of executing a task.

Chapter overview and links to contents

8.1 Conclusions on human representations of complex systems
8.1.1 Collected salient important findings
8.1.2 Variation between individuals and situations
8.1.3 What is modelled?
8.1.4 Generalising the methodology
8.1.4.1 Removal of information hiding
8.1.4.2 Removal of restriction on interaction timing
8.1.4.3 Including analogue control inputs
8.1.4.4 Finding new representational primitives
8.1.5 Conjectures about contexts
8.1.5.1 The articulation of contexts
8.1.5.2 The development of contexts
8.1.5.3 Types of context

8.2 Further implications for systems design, decision aids, and training
8.2.1 Preconditions for applying the methodology
Applying to ship navigation
Applying to other complex tasks
Fast dynamic tasks
8.2.2 Interface redesign
8.2.3 Safety
8.2.4 The Guardian Angel support paradigm
8.2.5 Training and assessment
8.2.6 Early design

8.3 Still further work
8.3.1 Recreating context structure without explicit data on
8.3.2 Further refinements of the context structure
8.3.2.1 Refining the quantities into qualitative ranges
8.3.2.2 Re-examination of actions
8.3.3 Directions for machine learning
8.3.4 Prospects for contributing to the study of human learning

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