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Expertise consists of those characteristics, skills and knowledge of a person (that is, expert) or of a system, which distinguish experts from novices and less experienced people. In many domains there are objective measures of performance capable of distinguishing experts from novices:expert chess players will almost always win games against recreational chess players; expert medical specialists are more likely to diagnose a disease correctly and so on.

There are broadly two academic approaches to the understanding and study of expertise. The first understands expertise as an emergent property of communities of practice. In this view expertise is socially constructed; tools for thinking and scripts for action are jointly constructed within social groups enabling that group jointly to define and acquire expertise in some domain.

In the second view expertise is a characteristic of individuals and is a consequence of the human capacity for extensive adaptation to physical and social environments. Many accounts of the development of expertise emphasise that it comes about though long periods of deliberate practice. In many domains of expertise estimates of 10 years experience or 10,000 hours deliberate practice are common. Typically recent research on expertise emphasises the nurture side of the nature versus nurture argument.^[1]

A number of computational models have been developed in cognitive science to explain the development from novice to expert. In particular, Herbert Simon and Kevin Gilmartin proposed a model of learning in chess called MAPP (Memory-Aided Pattern Recognizer).^[2] Based on simulations, they estimated that about 50,000 chunks (units of memory) are necessary to become an expert, and hence the many years needed to reach this level. More recently, the CHREST model (Chunk Hierarchy and REtrieval STructures) has simulated in detail a number a phenomena in chess expertise (eye movements, performance in a variety of memory tasks, development from novice to expert) and in other domains.^{[3] [4]}

Work on expert systems typically works from the premise that expertise is based on acquired repertoires of rules and frameworks for decision making which can be elicited as the basis for computer supported judgement and decision-making. However, there is increasing evidence that expertise does not work in this fashion. Rather, experts recognise situations based on experience of many prior situations. They are in consequence able to make rapid decisions in complex and dynamic situtions relying on recognition-primed decision-making.

In a critique of the expert systems literature, Dreyfus and Dreyfus ^[5] suggest:

If one asks an expert for the rules he or she is using, one will, in effect, force the expert to regress to the level of a beginner and state the rules learned in school. Thus, instead of using rules he or she no longer remembers, as the knowledge engineers suppose, the expert is forced to remember rules he or she no longer uses. … No amount of rules and facts can capture the knowledge an expert has when he or she has stored experience of the actual outcomes of tens of thousands of situations.”

^[6]

An important feature of expert performance seems to be the way in which experts are able to rapidly retrieve complex configurations of information from long term memory. They recognise situations because they have meaning. It is perhaps this central concern with meaning and how it attaches to situations which provides an important link between the individual and social approaches to the development of expertise.

In line with the socially constructed view of expertise, expertise can also be understood a form of power; that is, experts have the ability to influence others as a result of their defined social status.

1. ^ Anders Ericsson, Charness, Feltovich and Hoffman, 2006
2. ^ Simon and Gilmartin, 1973
3. ^ Gobet and Simon (2000)
4. ^ Gobet, de Voogt, & Retschitzki (2004)
5. ^ Dreyfus and Dreyfus (2005)
6. ^ Dreyfus and Dreyfus, 2005: 788

References

• Dreyfus, H. and Dreyfus, S. (2005) Expertise in real world contexts, Organization Studies, 26(5), 779-792.
• Gobet, F., de Voogt, A. J., & Retschitzki, J. (2004). Moves in mind: The psychology of board games. Hove, UK: Psychology Press.
• Gobet, F., & Simon, H. A. (2000). Five seconds or sixty? Presentation time in expert memory. Cognitive Science, 24, 651-682.
• Anders Ericsson, Charness. Feltovich, and Hoffman(2006)The Cambridge Handbook of Expertise and Expert Performance Cambridge: Cambridge University Press.
• Simon, H. A., & Gilmartin, K. J. (1973). A simulation of memory for chess positions. Cognitive Psychology, 5, 29-46.

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Germain (2006) has developed a measure of perception of employee expertise called the Generalized Expertise Measure (GEM). She has also found that there is a behavioral dimension found in "experts", in addition to the dimensions suggested by Swanson and Holton (2001).

Here is Germain's Generalized Expertise Measure. This scale is copyrighted and must not be used without citing the author (Germain, 2006).

1. This person has knowledge that is specific to his or her field of work. 2. This person shows that they have the education necessary to be an expert in their field. 3. This person has knowledge about their field. 4. This person has the qualifications required to be an expert in their field. 5. This person has been trained in his or her area of expertise. 6. This person is ambitious about their work in the company. 7. This person can assess whether a work-related situation is important or not. 8. This person is capable of improving himself or herself. 9. This person is charismatic. 10. This person can deduce things from work-related situations easily. 11. This person is intuitive in their job. 12. This person is able to judge what things are important in their job. 13. This person has the drive to become what he or she is capable of becoming in their field. 14. This person is self-assured. 15. This person has self-confidence. 16. This person is an expert who is outgoing.

References:

Germain, M. L. (2006). Development and preliminary validation of a psychometric measure of expertise: The Generalized Expertise Measure (GEM). Unpublished Doctoral Dissertation. Barry University, Florida.

Swanson, R. A., & Holton III, E. F. (2001). Foundations of Human Resource Development. San Francisco: Berrett-Koehler Publishers, Inc.