<rdf:RDF xmlns:community="http://www.bibsonomy.org/ontologies/2008/05/community#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:admin="http://webns.net/mvcb/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:cc="http://web.resource.org/cc/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:swrc="http://swrc.ontoware.org/ontology#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xml:base="http://www.bibsonomy.org/bibtex/23e0fc7b962143a2b724bf7243fc4050a/neilernst"><owl:Ontology rdf:about=""><rdfs:comment>BibSonomy publications for /bibtex/23e0fc7b962143a2b724bf7243fc4050a/neilernst</rdfs:comment><owl:imports rdf:resource="http://swrc.ontoware.org/ontology/portal"/></owl:Ontology><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/23e0fc7b962143a2b724bf7243fc4050a/neilernst"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/23e0fc7b962143a2b724bf7243fc4050a/neilernst"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://www.cs.toronto.edu/~nernst/papers/Rasmussen_-_SRK.pdf"/><swrc:date>Wed Jan 24 01:42:59 CET 2007</swrc:date><swrc:edition>SMC-13</swrc:edition><swrc:journal>IEEE Transactions on Systems, Man and Cybernetics</swrc:journal><swrc:number>3</swrc:number><swrc:pages>257--266</swrc:pages><swrc:title>Skills, rules, and knowledge: signals, signs, and symbols, and other distinctions in human performance models</swrc:title><swrc:volume>13</swrc:volume><swrc:year>1983</swrc:year><swrc:keywords>framework cognition </swrc:keywords><swrc:abstract>The introduction of information
technology based on digital computers for the
design of man-machine interface systems has led to
a requirement for consistent models of human
performance in routine task environments and
during unfamiliar task conditions. A discussion is
presented of the requirement for different types of
models for representing performance at the skill-,
rule-, and knowledge-based levels, together with a
review of the different ways in which information is
perceived at these different levels in terms of
signals signs, and symbols. Particular attention is
paid to the different possible ways of representing
system properties which underlie knowledge-based
performance and which can b characterized at
several levels of abstraction—from the
representation of physical form, through functional
representation, to representation in terms of
intention or purpose. Furthermore, the role of
qualitative and quantitative models in the design
and evaluation of interface systems is mentioned,
and the need to consider such distinctions carefully
is discussed</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="0" swrc:key="priority"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="121510" swrc:key="citeulike-article-id"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Jens Rasmussen"/></rdf:_1></rdf:Seq></swrc:author></rdf:Description></rdf:RDF>
