1999Journal of Technology in Human ServicesRequires access

Using Case-Based Reasoning to Develop Computerized Guidance for Effective Practice

Ray Carlson

Open publisher page 5 citations

Abstract

SUMMARY Research on expertise suggests that several years of extensive practice should lead to the development of good insights into effective practice. This paper describes this research and what it suggests about ways to capture and utilize such expertise in a computerized training simulator. Case-based reasoning is looked at as a way to interpret this research and its utilization. The paper also summarizes a project that is collecting such experience-based insights in the child welfare field. Particular attention is directed at ways to validate the experiential insights collected.

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What this paper is about

SUMMARY Research on expertise suggests that several years of extensive practice should lead to the development of good insights into effective practice. This paper describes this research and what it suggests about ways to capture and utilize such expertise in a computerized training simulator. Case-based reasoning is looked at as a way to interpret this research and its utilization. The paper also summarizes a project that is collecting such experience-based insights in the child welfare field. Particular attention is directed at ways to validate the experiential insights collected.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

SUMMARY Research on expertise suggests that several years of extensive practice should lead to the development of good insights into effective practice. This paper describes this research and what it suggests about ways to capture and utilize such expertise in a computerized training simulator. Case-based reasoning is looked at as a way to interpret this research and its utilization. The paper also summarizes a project that is collecting such experience-based insights in the child welfare field. Particular attention is directed at ways to validate the experiential insights collected.

Key concepts: Experiential learning, Computer science, Field (mathematics), Management science, Knowledge management, Data science, Engineering ethics, Psychology

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