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Cognitive task load analysis : Allocating tasks and designing support

Author: Neerincx, M.A.
Publisher: Erlbaum
Place: Mahwah
Institution: TNO Technische Menskunde
Source:Hollnagel, E., Handbook of cognitive task design, 283 - 305
Identifier: 12259
Article number: Chapter 13
Keywords: Informatics · Cognitive task analysis · Task allocation


We present a method for Cognitive Task Analysis that guides the early stages of software development, aiming at an optimal cognitive load for operators of process control systems. The method is based on a practical theory of cognitive task load and support. In addition to the classical measure percentage time occupied, this theory distinguishes two load factors that affect cognitive task performance and mental effort: the level of information processing and the number of task-set switches. Recent experiments provided empirical support for the theory, showing effects of each load factor on performance and mental effort. The model can be used to establish task (re-)allocations and to design cognitive support. This chapter provides an overview of the method’s foundation and two example applications. The first example is an analysis of the cognitive task load for a future naval ship control centre that identified overload risks for envisioned operator activities. Cognitive load was defined in terms of task demands in such a way that recommendations could be formulated for improving and refining the task allocation and user-interface support. The second example consists of the design and evaluation of a prototype user interface providing support functions for handling high-demand situations: an information handler, a rule provider, a diagnosis guide and a task scheduler. Corresponding to the theory, these functions prove to be effective, in particular when cognitive task load is high. The user interface is currently being implemented at a bridge of an icebreaker. The two examples comprise an integrated approach on task allocation enhancement and design of cognitive support. The theory and method are being further developed in an iterative cognitive engineering framework to refine the load and support model, improve the empirical foundation and extend the examples of good practices.