Components of expertise
DIGITAL.CSIC (Spanish National Research Council (CSIC)), Vol. 11, Issue 2, pp. 30–49 (1990)
10.1609/aimag.v11i2.831
Abstract
This article discusses frameworks for studying expertise at the knowledge level and knowledge-use level. It reviews existing approaches such as inference structures, the distinction between deep and surface knowledge, problem-solving methods, and generic tasks. A new synthesis is put forward in the form of a componential framework that stresses modularity and an analysis of the pragmatic constraints on the task. The analysis of a rule from an existing expert system (the Dipmeter Advisor) is used to illustrate the framework.
Topics
Field: Computer Science · Subfield: Artificial Intelligence
Keywords
Modularity (biology),Inference,Computer science,Task (project management),Knowledge base,Expert system,Artificial intelligence,Inference engine,Software engineering,Data science
UN Sustainable Development Goals
- Quality Education (0.43)
All Available Versions
- PDF Landing page — DIGITAL.CSIC (Spanish National Research Council (CSIC)) submittedVersion other-oa
- Landing page — VUBIR (Vrije Universiteit Brussel) submittedVersion
- Landing page — AI Magazine
Citations by Year
| 2023 | 2021 | 2020 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 |
|---|---|---|---|---|---|---|---|---|
| 1 | 3 | 3 | 1 | 3 | 1 | 3 | 6 | 4 |
- Information theory in ecology 1958 · 2126
- Mesopelagic fish biomass and trophic efficiency of the open ocean 2014 · 1813
- Guidance on Monitoring of Marine Litter in European Seas 2013 · 549
- Components of expertise 1990 · 476
- Alien flora of Europe: Species diversity, temporal trends, geographical patterns and research needs 2008 · 394
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