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Journals ACM SIGCHI Bulletin Volume 23 Issue 1

KARMA is a quantitative model which can be used to predict a user's acquisition, retention, maintenance, and transfer of system knowledge. In KARMA, three stages over the course of an operator's model (see Schumacher & Czerwinski, in press) are characterized: pretheoretic - the understanding of system structure centers on the retrieval of superficially similar instances in memory; experiential - some understanding of causal system relationships emerges, as does some reliance upon structural system information. Also, abstraction begins to occur across different, but similar systems; and expert - at this stage, the user makes abstractions across various system representations stored in memory; full reliance upon structural system knowledge emerges. Currently, a programmed simulation is used to compare our theoretical predictions and assumptions with experimental data. The simulation is running in Scheme (a dialect of LISP).

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KARMA: knowledge acquisition, retention and maintenance analysis

Czerwinski, M.; Schumacher, R.; Duba, B.
ACM SIGCHI Bulletin , Volume 23 (1)
Association for Computing Machinery – Jan 1, 1991

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