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The Role of a Mental Model in Learning to Operate a Device *
Author(s) -
Kieras David E.,
Bovair Susan
Publication year - 1984
Publication title -
cognitive science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
ISBN - 0-13-444910-X
DOI - 10.1207/s15516709cog0803_3
Subject(s) - computer science , inference , set (abstract data type) , recall , rote learning , simple (philosophy) , component (thermodynamics) , artificial intelligence , control (management) , learning curve , machine learning , human–computer interaction , cognitive psychology , psychology , teaching method , operating system , programming language , mathematics education , cooperative learning , philosophy , physics , epistemology , thermodynamics
This report presents three studies concerned with learning how to operate a simple control panel device, and how this learning is affected by understanding a device model that describes the internal mechanism of the device. The first experiment compared two groups, one of which learned a set of operating procedures for the device by rote, and the other learned the device model before receiving the identical procedure training. The model group learned the procedures faster, retained them more accurately, executed them faster, and simplified inefficient procedures far more often, than the rote group. The second study demonstrated that the model group is able to infer the procedures much more easily than the rote group, which would lead to more rapid learning and better recall performance. The third study showed that the important content of the device model was the specific configuration of components and controls, and not the motivational aspects, component descriptions, or general principles. This specific information is what is logically required to infer the procedures. Thus, the benefits of having a device model depend on whether it supports direct and simple inference of the exact steps required to operate the device.