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A Learning Curve Analysis of Expert System Use *
Author(s) -
Fedorowicz Jane,
Oz Effy,
Berger Paul D.
Publication year - 1992
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1992.tb00420.x
Subject(s) - computer science , expert system , learning curve , measure (data warehouse) , domain (mathematical analysis) , subject matter expert , machine learning , artificial intelligence , risk analysis (engineering) , human–computer interaction , knowledge management , data science , data mining , mathematics , medicine , mathematical analysis , operating system
In this article, we study how an expert system affects novice problem solving in a financial risk analysis domain. We demonstrate that novice performance is improved after exposure to an expert system. Further, we show that novice performance continues to improve when the system is withdrawn. By comparing learning curves for people with exposure to those without, we can assess how much the system has benefitted its users. We demonstrate a quantitative methodology to measure the increment of learning due to the use of an information technology. We also explore the issue of how expertise is transferred from the system to the user.