Elsevier

Acta Psychologica

Volume 71, Issues 1–3, August 1989, Pages 89-146
Acta Psychologica

An approach to training based upon principled task decomposition

https://doi.org/10.1016/0001-6918(89)90006-1Get rights and content

Abstract

The primary purposes of the present research are (1) to specify a principled basis for analyzing the skill and knowledge components of expert performance within a domain. (2) to develop an instructional strategy based upon this decomposition, and (3) to study the knowledge and skills resulting from such instruction. The domain of application, the Space Fortress game (Mané et al. 1984; Mané 1985), is a complex task which involves the concurrent and coordinate use of perceptual and motor skills, conceptual and strategic knowledge, in the service of multiple goals.

There are three primary aspects to our approach. The first is a decomposition of the task domain from the perspective of the inherent structure of the task, its human information processing demands, and the characteristics of expert performance. The decomposition identifies the top level goals of experts and the strategies, skills, and knowledge developed by them in pursuit of those goals. The second aspect of our approach is an analysis of hierarchical relations among the skills and knowledge components to be acquired. Hierarchical relations derive from conditional and functional relations among the components. This process attempts to determine a possible set of transformations that will turn novices into experts. As part of this process, skills may be identified that are not present in expert performance but which are necessary precursors to the acquisition of some skill or knowledge that is a component of expert performance. The third aspect of our approach is a construction of activities for training the individual components and their integration based upon a set of design principles, and an evaluation of the nature of the skills and knowledge acquired.

In contrast to the training strategies pursued by other investigators within the Learning Strategies project, our training activities are not necessarily set in the context of the Space Fortress game. This allowed us to constrain task performance in such a way as to necessitate the development of particular concepts needed for expert performance. In addition, our training strategy focused, more than any of the other training strategies, on the cognitive aspects of expertise in the game. In particular, we were concerned with facilitating the development of the conceptual knowledge that our analyses indicated is necessary for expert ship control. Our experimental results indicate the subjects exposed to our series of training tasks not only performed better than control subjects on the Space Fortress game but also performed better on other dynamic control tasks as well as on a paper and pencil physics test that measured their understanding of how accelerations affect the motion of objects.

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    This work has been supported by DARPA Contract No. MDA 903-84-K-0065 to the University of Illinois, Principal investigator, Emanuel Donchin. The research has benefited from the perspectives and innumerable contributions of Richard Pew.

    In addition, we gratefully acknowledge the work of Barbara Freeman, who contributed to all phases of the work, particularly to the design and programming of the training tasks. We also want to thank Jane Imai for her help in running subjects. This research would not have been possible without the assistance of members of the Cognitive Psychophysiology Laboratory, University of Illinois, particularly Emanuel Donchin, Amir Mané, Earle Heffley, Brian Foote, Mike Anderson, and Bill Sherman.

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