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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/14503
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| Title: | IMPOSING STRUCTURE ON LINEAR PROGRAMMING PROBLEMS: AN EMPIRICAL ANALYSIS
OF EXPERT AND NOVICE MODELS |
| Authors: | Orlikowski, Wanda
Dhar, Vasant |
| Issue Date: | Jul-1986 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | IS-86-059 |
| Abstract: | Research on expert-novice differences falls into two complementary
classes. The first assumes that novice skills are a subset of those of
the expert, represented by the same vocabulary of concepts. The second
approach emphasizes novices' misconceptions and the different meanings
they tend to attribute to concepts. Our evidence, based on observations
of problem solving behavior of experts and novices in the area of
mathematical programming, reveals both type of differences: while
novices are to some extent underdeveloped experts, they also attribute
different meanings to concepts. The research suggests that experts'
concepts can be characterized as being more differentiated than those of
novices, where the differentiation enables experts to categorize problem
descriptions accurately into standard archetypes and facilitates
attribution of correct meanings to problem features. Our results are
based on twenty-five protocols obtained from experts and novices
attempting to structure problem descriptions into mathematical
programming models. We have developed a model of knowledge in the LP
domain that accommodates a continuum of expertise ranging from that of
the expert who has a highly specialized vocabulary of LP concepts to
that of a novice whose vocabulary might be limited to high school
algebra. We discuss the normative implications of this model for
pedagogical strategies employed by instructors, textbooks and
intelligent tutoring systems. |
| URI: | http://hdl.handle.net/2451/14503 |
| Appears in Collections: | IOMS: Information Systems Working Papers
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