Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
1992-5-21
pubmed:abstractText
The evaluation of tutorial strategies, interface designs, and courseware content is an area of active research in the medical education community. Many of the evaluation techniques that have been developed (e.g., program instrumentation), commonly produce data that are difficult to decipher or to interpret effectively. We have explored the use of decision tables to automatically simplify and categorize data for the composition of user models--descriptions of student's learning styles and preferences. An approach to user modeling that is based on decision tables has numerous advantages compared with traditional manual techniques or methods that rely on rule-based expert systems or neural networks. Decision tables provide a mechanism whereby overwhelming quantities of data can be condensed into an easily interpreted and manipulated form. Compared with conventional rule-based expert systems, decision tables are more amenable to modification. Unlike classification systems based on neural networks, the entries in decision tables are readily available for inspection and manipulation. Decision tables, descriptions of observations of behavior, also provide automatic checks for ambiguity in the tracking data.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0195-4210
pubmed:author
pubmed:issnType
Print
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
681-5
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
1991
pubmed:articleTitle
Composing user models through logic analysis.
pubmed:affiliation
Harvard Medical School, Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't