This study applies Adaptive Character of Thought‐Rational (ACT‐R), a theory of cognitive skill acquisition, to identify two techniques theorized to provide learners with a simplified and situation‐responsive set of production rules to use in a problemsolving context. The two techniques are abstraction (an optimization technique that produces a generalized rule set) and goal structuring (another optimization technique that produces a differentiated rule set). Accordingly, abstraction and goal structuring explanations were provided to users through a knowledge‐based system (KBS). Due to cognitive effort constraints on procedural learning, a subset of volunteer participants was extracted for analysis based on an exhibition of attentive learning behavior. Results of the study found that while intermediary stages of development were not detectable, participants receiving goal‐structuring explanations exhibited better problem solving performance, and the joint presentation of abstraction explanations led to further problem solving improvements. Abstraction explanations did not lead to improved problem solving, however, when provided in absence of goal‐structuring explanations. These findings extend ACT‐R to a new venue, increase understanding of ACT‐R theory, and provide developers of KBS with more substantive knowledge on optimization of KBS explanation design when knowledge transfer to less expert users is an objective.
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Spring 2007
Research Article|
March 01 2007
The Effect of Alternative Procedural Explanation Types on Procedural Knowledge Acquisition during Knowledge‐Based Systems Use
Georgia Smedley;
Georgia Smedley
University of Missouri–Kansas City.
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Steve G. Sutton
Steve G. Sutton
University of Central Florida.
University of Melbourne.
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Online ISSN: 1558-7959
Print ISSN: 0888-7985
American Accounting Association
2007
Journal of Information Systems (2007) 21 (1): 27–51.
Citation
Georgia Smedley, Steve G. Sutton; The Effect of Alternative Procedural Explanation Types on Procedural Knowledge Acquisition during Knowledge‐Based Systems Use. Journal of Information Systems 1 March 2007; 21 (1): 27–51. https://doi.org/10.2308/jis.2007.21.1.27
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