Expert

For other uses, see Expert (disambiguation).

"Cognoscenti" redirects here. For the Marvel character, see Cognoscenti (comics).

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An expert ( Audio (US) (help·info), also called cognoscente^[1]) is someone widely recognized as a reliable source of technique or skill whose faculty for judging or deciding rightly, justly, or wisely is accorded authority and status by their peers or the public in a specific well-distinguished domain. An expert, more generally, is a person with extensive knowledge or ability based on research, experience, or occupation and in a particular area of study. Experts are called in for advice on their respective subject, but they do not always agree on the particulars of a field of study. An expert can be, by virtue of credential, training, education, profession, publication or experience, believed to have special knowledge of a subject beyond that of the average person, sufficient that others may officially (and legally) rely upon the individual's opinion. Historically, an expert was referred to as a sage (Sophos). The individual was usually a profound thinker distinguished for wisdom and sound judgment.

Experts have a prolonged or intense experience through practice and education in a particular field. In specific fields, the definition of expert is well established by consensus and therefore it is not necessary for an individual to have a professional or academic qualification for them to be accepted as an expert. In this respect, a shepherd with 50 years of experience tending flocks would be widely recognized as having complete expertise in the use and training of sheep dogs and the care of sheep. Another example from computer science is that an expert system may be taught by a human and thereafter considered an expert, often outperforming human beings at particular tasks. In law, an expert witness must be recognized by argument and authority.

Research in this area attempts to understand the relation between expert knowledge and exceptional performance in terms of cognitive structures and processes. The fundamental research endeavor is to describe what it is that experts know and how they use their knowledge to achieve performance that most people assume requires extreme or extraordinary ability. Studies have investigated the factors that enable experts to be fast and accurate.^[2]

Expertise

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; etc.

Academic views on expertise

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 emphasize that it comes about through long periods of deliberate practice. In many domains of expertise estimates of 10 years experience^[3] deliberate practice are common. Recent research on expertise emphasizes the nurture side of the nature versus nurture argument.^[3]

Some factors not fitting the nature-nurture dichotomy are biological but not genetic, such as starting age, handedness, and season of birth.^[4][5][6]

Historical views on expertise

In line with the socially constructed view of expertise, expertise can also be understood as a form of power; that is, experts have the ability to influence others as a result of their defined social status. By a similar token, a fear of experts can arise from fear of an intellectual elite's power. In earlier periods of history, simply being able to read made one part of an intellectual elite. The introduction of the printing press in Europe during the fifteenth century and the diffusion of printed matter contributed to higher literacy rates and wider access to the once-rarefied knowledge of academia. The subsequent spread of education and learning changed society, and initiated an era of widespread education whose elite would now instead be those who produced the written content itself for consumption, in education and all other spheres.

Plato's "Noble Lie", concerns expertise. Plato did not believe most people were clever enough to look after their own and society's best interest, so the few "clever" people of the world needed to lead the rest of the flock. Therefore, the idea was born that only the elite should know the truth in its complete form and the rulers, Plato said, must tell the people of the city "The Noble Lie" to keep them passive and content, without the risk of upheaval and unrest.

In contemporary society, doctors and scientists, for example, are considered to be experts in that they hold a body of dominant knowledge that is, on the whole, inaccessible to the layman (Fuller: 2005: 141). However, this inaccessibility and perhaps even mystery that surrounds expertise does not cause the layman to disregard the opinion of the experts on account of the unknown. Instead, the complete opposite occurs whereby members of the public believe in and highly value the opinion of medical professionals or of scientific discoveries (Fuller: 2005: 144), despite not understanding it.

Research related to expertise

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).^[7] 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 of phenomena in chess expertise (eye movements, performance in a variety of memory tasks, development from novice to expert) and in other domains.^[8][9]

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 recognize 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. Work on "Skilled Memory and Expertise" by Anders Ericsson and James J. Staszewski confronts the paradox of expertise and claims that people not only acquire content knowledge as they practice cognitive skills, they also develop mechanisms that enable them to use a large and familiar knowledge base efficiently.^[2]

Work on expert systems (computer software designed to provide an answer to a problem, or clarify uncertainties where normally one or more human experts would need to be consulted) typically is grounded on 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 judgment and decision-making. However, there is increasing evidence that expertise does not work in this fashion. Rather, experts recognize situations based on experience of many prior situations. They are in consequence able to make rapid decisions in complex and dynamic situations.

In a critique of the expert systems literature Dreyfus & Dreyfus (2005) 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 they no longer remember, as knowledge engineers suppose, the expert is forced to remember rules they no longer use. … 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.^[10]

Skilled Memory Theory

Skilled Memory and Expertise^[2]

The role of long term memory in the skilled memory effect was first articulated by Chase and Simon in their classic studies of chess expertise. They asserted that organized patterns of information stored in long term memory (chunks) mediated experts' rapid encoding and superior retention. Their study revealed that all subjects retrieved about the same number of chunks, but the size of the chunks varied with subjects' prior experience. Experts' chunks contained more individual pieces than those of novices. This research did not investigate how experts find, distinguish, and retrieve the "right" chunks from the vast number they hold without a lengthy search of long term memory.

Skilled memory enables experts to rapidly encode, store, and retrieve information within the domain of their expertise and thereby circumvent the capacity limitations that typically constrain novice performance. For example, it explains experts' ability to recall large amounts of material displayed for only brief study intervals, provided that the material comes from their domain of expertise. When unfamiliar material (not from their domain of expertise) is presented to experts, their recall is no better than that of novices.

The first principle of skilled memory, the meaningful encoding principle, states that experts exploit prior knowledge to durably encode information needed to perform a familiar task successfully. Experts form more elaborate and accessible memory representations than novices. The elaborate semantic memory network creates meaningful memory codes that create multiple potential cues and avenues for retrieval.

The second principle, the retrieval structure principle states that experts develop memory mechanisms called retrieval structures to facilitate the retrieval of information stored in long term memory. These mechanisms operate in a fashion consistent with the meaningful encoding principle to provide cues that can later be regenerated to retrieve the stored information efficiently without a lengthy search.

The third principle, the speed up principle states that long term memory encoding and retrieval operations speed up with practice, so that their speed and accuracy approach the speed and accuracy of short term memory storage and retrieval.

Examples of skilled memory research described within the Ericcson and Stasewski study include:

• a waiter who can accurately remember up to 20 complete dinner orders in an actual restaurant setting by using mnemonic strategy, patterns, and spatial relations (position of the person ordering). At the time of recall all items of a category (e.g., all salad dressings, then all meat temperatures, then all steak types, then all starch type) would be recalled in a clockwise fashion for all customers.
• a running enthusiast who grouped together short random sequences of digits and encoded the groups in terms of their meaning as running times, dates, and ages. He was thus able to recall over 84% of all digit groups presented in a session totaling 200-300 digits. His expertise was limited to digits; when a switch from digits to letters of the alphabet was made he exhibited no transfer—his memory span dropped back to about six consonants.
• math enthusiasts who can in less than 25 seconds mentally solve 2 x 5 digit multiplication problems (e.g., 23 x 48,856) that have been presented orally by the researcher.

Expertise in problem solving

Much of the research regarding expertise involves the studies of how experts and novices differ in solving problems (Chi, M. T. H., Glasser R., & Rees, E.,1982). Mathematics (Sweller, J., Mawer, R. F., & Ward, M. R., 1983) and physics (Chi, Feltovich, & Glaser, 1981) are common domains for these studies.

One of the most cited works in this area, Chi et al. (1981), examines how experts (PhD students in physics) and novices (undergraduate students that completed one semester of mechanics) categorize and represent physics problems. They found that novices sort problems into categories based upon surface features (e.g., keywords in the problem statement or visual configurations of the objects depicted). Experts, however, categorize problems based upon their deep structures (i.e., the main physics principle used to solve the problem).

Their findings also suggest that while the schemas of both novices and experts are activated by the same features of a problem statement, the experts’ schemas contain more procedural knowledge which aid in determining which principle to apply, and novices’ schemas contain mostly declarative knowledge which do not aid in determining methods for solution.

Germain's Expertise Scale

Germain's main points Relative to a specific field, an expert has: Specific education, training, and knowledge Required qualifications Ability to assess importance in work-related situations Capability to improve themselves Intuition Self-assurance and confidence in their knowledge

Marie-Line Germain (Germain, 2006) developed a psychometric measure of perception of employee expertise called the Generalized Expertise Measure (GEM). She defined a behavioral dimension in "experts", in addition to the dimensions suggested by Swanson and Holton (2001). Her 16-item scale contains objective expertise items and subjective expertise items. Objective items were named Evidence-Based items. Subjective items (the remaining 11 items from the measure below) were named Self-Enhancement items because of their behavioral component.

This person has knowledge specific to a field of work. This person shows they have the education necessary to be an expert in the field. This person has the qualifications required to be an expert in the field. This person has been trained in their area of expertise. This person is ambitious about their work in the company. This person can assess whether a work-related situation is important or not. This person is capable of improving themselves. This person is charismatic. This person can deduce things from work-related situations easily. This person is intuitive in the job. This person is able to judge what things are important in their job. This person has the drive to become what they are capable of becoming in their field. This person is self-assured. This person has self-confidence. This person is outgoing. (Condensed from Germain, 2006).

References related to Germain's Expertise Scale

• Germain, M. L. (2009). The impact of perceived administrators' expertise on subordinates' job satisfaction and turnover intention. Academy of Human Resource Development. Arlington, VA. February 18–22, 2009.
• 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.
• Germain, M. L. (2006). Perception of Instructors’ Expertise by College Students: An Exploratory Qualitative Research Study. American Educational Research Association annual conference, San Francisco, CA. April 7–11.
• Germain, M. L. (2006, February). What experts are not: Factors identified by managers as disqualifiers for selecting subordinates for expert team membership. Academy of Human Resource Development Conference. Columbus, OH. February 22–26.
• Germain, M. L. (2005). Apperception and self-identification of managerial and subordinate expertise. Academy of Human Resource Development. Estes Park, CO. February 24–27.
• Swanson, R. A., & Holton III, E. F. (2001). Foundations of Human Resource Development. San Francisco: Berrett-Koehler Publishers, Inc.

Contrasts and comparisons

Associated terms

An expert differs from the specialist in that a specialist has to be able to solve a problem and an expert has to know its solution. The opposite of an expert is generally known as a layperson, while someone who occupies a middle grade of understanding is generally known as a technician and often employed to assist experts. A person may well be an expert in one field and a layperson in many other fields. The concepts of experts and expertise are debated within the field of epistemology under the general heading of expert knowledge. In contrast, the opposite of a specialist would be a generalist, somebody with expertise in many fields.

The term is widely used informally, with people being described as 'experts' in order to bolster the relative value of their opinion, when no objective criteria for their expertise is available. The term crank is likewise used to disparage opinions. Academic elitism arises when experts become convinced that only their opinion is useful, sometimes on matters beyond their personal expertise.

In contrast to an expert, a novice (known colloquially as a newbie or 'greenhorn') is any person that is new to any science or field of study or activity or social cause and who is undergoing training in order to meet normal requirements of being regarded a mature and equal participant.

"Expert" is also being mistakenly interchanged with the term "authority in new media. An expert can be an authority if through relationships to people and technology, that expert is allowed to control access to his expertise. However, a person who merely wields authority is not by right an expert. In new media, users are being misled by the term "authority. Many sites and search engines such as Google and Technorati use the term "authority" to denote the link value and traffic to a particular topic. However, this "authority only measures populist information. It in no way assures that the author of that site or blog is an expert.

See also the "expertise" section below.

Developmental characteristics

Some characteristics of the development of an expert have been found to include

• A characterization of this practice as "deliberate practice", which forces the practitioner to come up with new ways to encourage and enable themselves to reach new levels of performance^{[citation needed]}
• An early phase of learning which is characterized by enjoyment, excitement, and participation without outcome-related goals^[11]
• The ability to rearrange or construct a higher dimension of creativity. Due to such familiarity or advanced knowledge experts can develop more abstract perspectives of their concepts and/or performances.^{[citation needed]}

Use in literature

Mark Twain defined an expert as "an ordinary fellow from another town".^[12] Jesus is even quoted as saying "A prophet is not without honor, except in his hometown." Mark 6:4. Will Rogers described an expert as "A man fifty miles from home with a briefcase." Danish scientist and Nobel laureate Niels Bohr defined an expert as "A person that has made every possible mistake within his or her field."

See also

• Consultant
• Polymath

General

Scholar, Know-how, Skill, Competence, Excellence, Technical government, Insider, Tutor expertise in adult education

Criticism

Anti-intellectualism, Denialism

Psychology

Dunning–Kruger effect, Pygmalion effect, Rational skepticism

Notes

1. ^ "Past master". Merriam-Webster. 2011. http://www.merriam-webster.com/dictionary/cognoscente. Retrieved 05-12-2011. 
2. ^ ^{a b c} (Ericsson & Stasewski 1989)
3. ^ ^{a b} (Ericsson et al. 2006)
4. ^ (Gobet 2008)
5. ^ (Gobet & Chassy 2008)
6. ^ (Gobet & Campitelli 2007)
7. ^ Simon and Gilmartin (1973)
8. ^ (Gobet & Simon 2000)
9. ^ (Gobet, de Voogt & Retschitzki 2004)
10. ^ (Dreyfus & Dreyfus 2005, p. 788)
11. ^ Janet L. Starkes, K Anders Ericsson (2003) Expert Performance in Sports Advances in Research on Sport Expertise. p. 91
12. ^ Funny, Witty and Inspirational Quotes and Sayings - Doc's Ever-Changing Home Pages Are Entertaining the World, One Person at a Time ©

References

• Chase, W.G.; Simon, Herbert A. (1973a). "The mind's eye in chess". In W.G. Chase. Visual information processing. New York: Academic Press. ISBN 0121701506. 
• Chase, W.G.; Simon, Herbert A. (1973b). "Perception in chess". Cognitive Psychology 4: 55–81. doi:10.1016/0010-0285(73)90004-2. 
• Chi, M. T.; Feltovich, P. J.; Glaser, R. (1981). "Categorization and representation of physics problems by experts and novices". Cognitive Science 5 (2): 121–152. doi:10.1207/s15516709cog0502_2. 
• Chi, M. T. H., Glasser R., & Rees, E. (1982). Expertise in problem solving. In R. J. Sternberg (Ed.), Advances in the psychology of human intelligence. (Vol. 1, pp. 7–75). Hillsdale, NJ: Erlbaum.
• Dreyfus, H.; Dreyfus, S. (2005). "Expertise in real world contexts". Organization Studies 26 (5): 779–792. doi:10.1177/0170840605053102. 
• Ericsson, K. A. (2000). Expert Performance and Deliberate Practice
• Ericsson, Anders K.; Charness, Neil; Feltovich, Paul; Hoffman, Robert R. (2006). Cambridge handbook on expertise and expert performance. Cambridge, UK: Cambridge University Press. ISBN 0521600812. http://www.cambridge.org/us/catalogue/catalogue.asp?isbn=052184097X. 
• Ericsson, Anders K.; Prietula, Michael J.; Cokely, Edward T. (2007). "The Making of an Expert". Harvard Business Review (July–August 2007). http://www.coachingmanagement.nl/The%20Making%20of%20an%20Expert.pdf. 
• Ericsson, Anders K.; Stasewski, James J. (1989). "Chapter 9: Skilled Memory and Expertise: Mechanisms of Exceptional Performance". In David Klahr and Kenneth Kotovsky. Complex Information Processing: The Impact of Herbert A. Simon. Hillesdale N.J.: Lawrence Erlbaum Associates. 
• Gibbons, M.. (1994). Visual information processing. London: SAGE Publications. ISBN 9780803977945. http://books.google.com/books?id=7_L4C-vmdOkC. 
• Gobet, Fernand (2008). "The role of deliberate practice in expertise: Necessary but not sufficient". bura.brunel.ac.uk. http://bura.brunel.ac.uk/handle/2438/2120. Retrieved June 16, 2010. 
• Gobet, F.; Campitelli, G. (2007). "The role of domain-specific practice, handedness and starting age in chess". Developmental Psychology 43 (1): 159–172. doi:10.1037/0012-1649.43.1.159. PMID 17201516. http://bura.brunel.ac.uk/bitstream/2438/611/1/Gobet_DevPsyc_Final.pdf. 
• Gobet, F.; Chassy, P. (2008). "Season of birth and chess expertise". Journal of Biosocial Science 40 (2): 313–316. doi:10.1017/S0021932007002222. PMID 18335581. http://bura.brunel.ac.uk/bitstream/2438/736/1/Seasonality%20and%20chess.pdf. 
• Gobet, F.; de Voogt, A. J.; Retschitzki, J. (2004). Moves in mind: The psychology of board games. Hove, UK: Psychology Press. ISBN 1841693367. 
• Gobet, F.; Simon, Herbert A. (2000). "Five seconds or sixty? Presentation time in expert memory". Cognitive Science 24 (4): 651–682. doi:10.1207/s15516709cog2404_4. 
• Goldman, A. I. (1999). Knowledge in a Social World. Oxford: Oxford University Press.
• Mieg, Harald A. (2001). The social psychology of expertise. Mahwah, NJ: Lawrence Erlbaum Associates.
• Shanteau, J.; Weiss, D.J.; Thomas, R.P.; Pounds, J.C. (2002). "Performance-based assessment of expertise: How to decide if someone is an expert or not". European Journal of Operational Research 136 (2): 253–263. doi:10.1016/S0377-2217(01)00113-8. 
• Simon, H. A.; Chase, W.G. (1973). "Skill in chess". American Scientist 61: 394–403. 
• Simon, H. A.; Gilmartin, K. J. (1973). "A simulation of memory for chess positions". Cognitive Psychology 5: 29–46. doi:10.1016/0010-0285(73)90024-8. 
• Sowell, T. (1980). Knowledge and decisions. New York: Basic Books, Inc.
• Swanson, R. A., & Holton III, E. F. (2001). Foundations of Human Resource Development. San Francisco: Berrett-Koehler Publishers, Inc.
• Sweller, J.; Mawer, R. F.; Ward, M. R. (1983). "Development of expertise in mathematical problem solving". Journal of Experimental Psychology 112 (4): 639–661. doi:10.1037/0096-3445.112.4.639. 
• Tynjala, P (1999). "Towards expert knowledge? A comparison between a constructivist and a traditional learning environment in the university". International Journal of Educational Research 31 (5): 357. doi:10.1016/S0883-0355(99)00012-9. 
• Fuller, S. (2005). The Intellectual. Icon Books
• Collins, R. (1979). The Credential Society
• Dewey, J. (1927). The Public and its Problems
• Nettleton, S.; Burrows, R.; O'Malley, L. (2005). "The mundane realities of the everyday use of the internet for health, and their consequences for media convergence". Sociology of Health and Illness 27 (7): 972–992. doi:10.1111/j.1467-9566.2005.00466.x. PMID 16313525. 

Further reading

Books and publications

• Ikujiro Nonaka, Georg von Krogh, and Sven Voelpel, Organizational Knowledge Creation Theory: Evolutionary Paths and Future Advances. Organization Studies, Vol. 27, No. 8, 1179-1208 (2006). SAGE Publications, 2006. DOI 10.1177/0170840606066312
• Sjöberg, Lennart (2001). "Limits of Knowledge and the Limited Importance of Trust". Risk Analysis 21 (1): 189–198. doi:10.1111/0272-4332.211101. PMID 11332547. 
• Hofer, Barbara K.; Pintrich, Paul R. (1997). "The Development of Epistemological Theories: Beliefs about Knowledge and Knowing and Their Relation to Learning". Review of Educational Research 67 (1): 88–140. doi:10.2307/1170620. JSTOR 1170620. 
• B Wynne, May the sheep safely graze? A reflexive view of the expert-lay knowledge divide. Risk, Environment and Modernity: Towards a New Ecology, 1996.
• Thomas H. Davenport, et al., Working knowledge . 1998, knowledge.hut.fi.
• Mats Alvesson, Knowledge work: Ambiguity, image and identity. Human Relations, Vol. 54, No. 7, 863-886 (2001). The Tavistock Institute, 2001.
• Peter J. Laugharne, Parliament and Specialist Advice, Manutius Press, 1994.
• Jay Liebowitz, Knowledge Management Handbook. CRC Press, 1999. 328 pages. ISBN 0849302382
• C. Nadine Wathen and Jacquelyn Burkell, Believe it or not: Factors influencing credibility on the Web. Journal of the American Society for Information Science and Technology, VL. 53, NO. 2. PG 134-144. John Wiley & Sons, Inc., 2002. DOI 10.1002/asi.10016
• Nico Stehr, Knowledge Societies. Sage Publications, 1994. 304 pages. ISBN 0803978928

Patents

• U.S. Patent 4,803,641, Basic expert system tool, Steven Hardy et al., Filed November 25, 1987, Issued February 7, 1989.
• Effectuation: Decision heuristics of expert entrepreneurs