THOMPSON@UMASS-CS.CSNET (02/03/86)
From: THOMPSON%umass-cs.csnet@CSNET-RELAY.ARPA I am looking for information about the knowledge structure differences of people who have different levels of expertise in a subject. For example, what is the difference in the knowledge structure of an "apprentice", a "journeyman",or a "master". I will be happy to collect these references and repost them. Please send them directly to me (via csnet). Roger Thompson Thompson@UMASS
bulko@SALLY.UTEXAS.EDU (Bill Bulko) (02/11/86)
From: bulko@SALLY.UTEXAS.EDU (Bill Bulko)
My attempted mail reply to thompson@umass-cs.csnet failed, so I'm
posting this instead. The request was for pointers to articles dealing
with how varying levels of expertise could be represented. My research
is related to problem solving in physics, and so I have read several papers
dealing with the way people learn how to solve problems in technical fields.
Below is an excerpt from my proposal containing the related (annotated)
references; I hope that they prove helpful.
Bhaskar, R., and H. A. Simon, "Problem Solving in Semantically Rich
Domains: An Example from Engineering Thermodynamics." Cognitive Science,
Vol. 1, No. 2, April 1977.
This is a study of the processes used by people to solve problems in
semantically rich domains, and how these processes compare with those in
general problem-solving domains. The authors choose the field of
thermodynamics, and use a protocol-encoding program called SAPA, which they
theorize corresponds to their subject's problem-solving behavior.
Chi, M. T. H., P. Feltovich, and R. Glaser, "Categorization and
Representation of Physics Problems by Experts and Novices." Cognitive
Science, Vol. 5, No. 2, April-June 1981.
The authors compare the ways experts and novices categorize physics problems
and form physical models of the problems based on the categories created.
Studies are presented which investigate the implications of the differences
found for problem solving in general.
Larkin, J., J. McDermott, D. Simon, and H. A. Simon, "Models of Competence in
Solving Physics Problems." Cognitive Science, Vol. 4, No. 4, October-
December 1980.
This article discusses how a person's experience and expertise in solving
physics problems determine the process by which he solves them. The authors
describe a set of two computer programs which they claim are accurate models
of "expert" and "novice" problem-solving protocols.
Larkin, J., and H. A. Simon, "Learning Through Growth of Skill in
Mental Modeling." Proceedings of the Third Annual Conference of
the Cognitive Science Society, p. 106.
The authors study how people develop the ability to take physical situations
and re-represent them in terms of scientific entities. They present a program
called ABLE, which models the performance of human experts and novices as they
solve physics problems, from this learning point of view.
Luger, G., "Mathematical Model Building in the Solution of Mechanics
Problems: Human Protocols and the MECHO Trace." Cognitive Science,
Vol. 5, No. 1, January-March 1981.
Luger describes an automatic problem solver, MECHO, and describes how it
can be used for model building and manipulation in solving problems in
physics. He compares traces of MECHO with the problem-solving protocols of
several human subjects, and hypothesizes that these traces are similar to the
model-building techniques that people in general use.
Hope these help,
Bill
"In the knowledge lies the power." -- Edward A. Feigenbaum
"Knowledge is good." -- Emil Faber
Bill Bulko Department of Computer Sciences
The University of Texas {ihnp4,harvard,gatech,ctvax,seismo}!sally!bulkomark@MIMSY.UMD.EDU (Mark Weiser) (02/14/86)
From: Mark Weiser <mark@mimsy.umd.edu> In article <8602111536.AA15674@sally.UTEXAS.EDU> sally!bulko (Bill Bulko) writes: > Chi, M. T. H., P. Feltovich, and R. Glaser, "Categorization and > Representation of Physics Problems by Experts and Novices." Cognitive > Science, Vol. 5, No. 2, April-June 1981. > The authors compare the ways experts and novices categorize physics problems > and form physical models of the problems based on the categories created. > Studies are presented which investigate the implications of the differences > found for problem solving in general. A related paper is : Mark Weiser and Joan Shertz. "Programming problem representation in novice and expert programmers." International Journal of Man-Machine Studies. December 1983. pp. 391-398. This paper is an application of some of the Chi, Feltovich, and Glaser methodology to the problem space of programming, with generically similar results. Differences in detail include categories of problem-solving used and not used by experts (algorithms yes, data-structures no), and differences between expert programmers and expert former programmers now programming managers. -mark Spoken: Mark Weiser ARPA: mark@maryland Phone: +1-301-454-7817 CSNet: mark@umcp-cs UUCP: {seismo,allegra}!umcp-cs!mark USPS: Computer Science Dept., University of Maryland, College Park, MD 20742
pamp@BCSAIC.UUCP (02/17/86)
From: decwrl!pyramid!hplabs!tektronix!uw-beaver!ssc-vax!bcsaic!pamp@ucbvax.berkeley.edu In article <8602100723.AA28871@ucbvax.berkeley.edu> you write: >From: THOMPSON%umass-cs.csnet@CSNET-RELAY.ARPA > > > I am looking for information about the knowledge structure > differences of people who have different levels of expertise > in a subject. For example, what is the difference in the > knowledge structure of an "apprentice", a "journeyman",or a > "master". > > I will be happy to collect these references and repost them. > Please send them directly to me (via csnet). > > Roger Thompson > > Thompson@UMASS One that I can recommend right off hand is - Kolodner,Janet L.,1984,Towards an understanding of the role of experience in the evolution from novice to expert: in Developments in expert systems;M.J.Coombs,ed.; Academic Press,p.95-116. You might also look into Schank's work Schank,R.C.,1982, Dynamic Memory:A thoery of learning in people and computers; Cambridge University Press, Cambridge. P.M.Pincha-Wagener