Expert and Novice User Differences and Implications for Product Design and Useability

Abstract

This paper explores differences and similarities between novice and expert users of interactive artifacts. In order to achieve this, protocol analysis was used to identify users' cognitive categories, knowledge categories and knowledge representation. This research is based on the premises that knowledge — domain-specific knowledge in particular — plays a significant role in distinguishing a novice from an expert user, and the way in which they use technologically interactive devices. The differences between expert and novice users were compared and identified with associated knowledge and knowledge representation for each cognitive category. These constitute the features that differentiate them as they reflect the kind of processes, representations, strategies or knowledge organisation that may occur for each cognitive category during the interaction. The paper also addresses the transitional process through which a novice becomes an expert and concludes about this finding's implication to design.

Get full access to this article

View all access options for this article.

References

Alexander

P. A.

Judy

J. E.

(1988), The Interaction of Domainspecific Knowledge in Academic Performance, Review of Educational Research, Vol. 4, pp 375–404.

Anzai

(1991), Learning and Use of Representation for Physics Expertise, in Ericsson

K. A.

Smith

, (Eds.) Toward a General Theory of Expertise, Cambridge University Press, New York, pp 64–92.

Chi

M. T. H.

Glaser

Farr

, (Eds.), (1988), The Nature of Expertise, Lawrence Erlbaum Associates, Hillsdale, NJ.

Duff

S. C.

Barnard

P. J.

(1990), Influencing Behaviour Via Device Representation; Decreasing Performance by Increasing Instruction, in Diaper

(Ed), Human-Computer InteractionINTERACT '90, North-Holland, Amsterdam, pp 61–66.

Ericsson

K. A.

Simon

H. A.

(1993), Protocol Analysis Verbal Reports as Data, The MIT Press, Cambridge, Massachusetts, pp 61, 223.

Feltovich

P. J.

Ford

K. M.

Hoffman

R. R.

(Eds.), (1997) Expertise in Context, AAAI Press/MIT Press, Menlo Park, Cal/Cambridge, Mass.

Gero

S. J.

McNeill

(1997), An Approach to the Analysis of Design Protocol, Design Studies.

Gentner

Stevens

A. L.

(Eds.) (1983), Mental Models, Lawrence Erlbaum, Hillsdale NJ.

Kieras

D. E.

Poison

P. G.

(1985), An Approach to the Formal Analysis of User Complexity, Int. J. Man-Machine Studies, 22, pp 365–394.

10.

Koedinger

K. R.

Anderson

J. R.

(1990), Abstract Planning and Perceptual Chunks: Elements of Expertise in Geometry, Cognitive Science 14, pp 511–550.

11.

Kolonder

J. L.

(1983), Towards an Understanding of the Role of Expertise in the Evolution from Novice to Expert, Int. J. ManMachine Studies, 19, pp 497–518.

12.

Kolodner

J L

Simpson

R L

, (1986) Problem solving and dynamic memory in Experience memory and reasoning, Kolodner

J. L.

Riesbeck

C. K.

(Eds.), Lawrence Erlbaum, Hillside, NJ, pp 99–114.

13.

Lesgold

Glaser

Rubinson

Klopfer

Feltovich

Wang

(1988), Expertise in a Complex Skill Diagnosing X-Ray Pictures in Chi

M. T. H.

Glaser

Farr

M. J.

(Eds.), The Nature of Expertise, Lawrence Erlbaum, Hillsdale, NJ, pp 311–31.

14.

McNeill

(1996), Personal communication, Sydney University, Sydney.

15.

Nardi

, (Ed.) (1996), Studying Context: A Comparison of Activity Theory, Situated Action Models and Distributed Cognition, in Nardi

(Ed.), Context and Consciousness: Activity theory and Human - Computer Interaction, The MIT Press, Cambridge, Mass., pp.69–102.

16.

Payne

S. J.

(1991), A Descriptive Study of Mental Models, Behaviour and Information Technology, 10 (1), pp 3–21.

17.

Popovic

(1998) Novice and Expert Users Model, Ph.D. Thesis, University of Sydney.

18.

Popovic

Gero

(2000), Expert and Novice Differences Comparative Analysis of Protocol Data (in preparation).

19.

Reimann

Chi

M. T. H.

(1989), Human Expertise, in Gilhooly

K. J.

(Ed), Human and Machine Problem Solving, Plenum Press, New York and London, pp 161–199.