What Is an Expert?
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Currently the most prevalent is that an expert is a person who has some skill or knowledge in some domain that is matched by only a few other people. These people are thus extraordinary in some way. Anders Ericsson, probably the best known of the researchers on expertise defines expertise as Relatively stable outstanding performance.Experts are often labeled as such. People called exceptional, superior, gifted, talented, specialist, expert, etc. tend to belong to the set of experts.
There is no doubt that there are large differences in the quality of performance of different people on different tasks or in different domains. We can think of this difference as a scale of expertise. Novices are those who do not perform very well, and we can move through different levels of expertise until we find some individuals that we might say are skilled or knowledgeable beyond that of almost everyone else in the world, or world class. What is the nature of this dimension? What are the categories within which this level of expertise motif applies?
Becoming an expert in any domain requires experience and effort. Don Norman introduced the notion that an someone requires 10,000 hours of experience and practice for reasonably complex domains to have the possibility of being an expert. Most people seem to agree with that assessment. In order for someone to become an expert in physics, music, chess, psychology, mathematics, baseball, etc. takes many hours, even years, of hard work and practice.
***Keith Ericsson in viewing the development of expertise argued that the most important factor, perhaps even necessary and sufficient for developing expertise is deliberative practice. Deliberative practice has four properties: (1) it is at an appropriate level of difficulty, (2) the participant receives informative feedback, (3) the participant has many opportunities for repetition, and (4) the participant has th opportunity to correct for errors (from Ericsson (1996; found in Sternberg & Ben-Zeev (2001).
If we focus on the process of becoming an expert rather than the claim that only a few become expert, we may come to a position I first heard from Micki Chi. Children are universal novices. They have not developed very many of the component skills needed for any domain. Decalage is the order of the day; many of the skills needed are relatively domain specific. The topics in the topics of cognitive development are a selection of the topics that could be studied under the rubric of expertise. Following Vygotsky, people learn to perceive and think in the domains that they come into direct interaction with. Some skills are fairly general in that they underlie many other skills. Those are the ones that children tend to learn first.
Domains that show movement from novice to expert include: Walking, talking, reading English text, writing, riding a bicycle, driving a car, getting around campus, talking to friends, studying particular courses, taking notes, seeing mathematical relationships, understanding formal arguments, taking multiple choice tests, taking essay tests. As we develop skills in these areas the structure of our performance changes.
Hypothesis: The development of expertise parallels the development of cognition in children.
As people develop expertise their skills and performance becomes structurally different than it was prior to that development. The performance of experts is qualitatively different from those of novices. When one learns a new task she is automatically at an early stage of development. How early depends to a great extent on how many of the component skills have already been developed.
Some examples–(What is a domain?) playing chess, looking at blood slides, listening to music, looking at an x-ray, looking at 3-D pictures, riding a bicycle, skiing. dancing, gymnastics, solving physics problems, walking, reading, riding a bicycle, driving a car, dancing, typing, computer programming, cab driving, radiology, medical diagnosis, playing a piano, violin, basketball, baseball, football, gymnastics, golf, writing papers, taking tests.
Propositional knowledge–Philosophically–knowing what. When novices learn in a new domain, the information tends to be represented as independent single propositions, with the development of expertise the separate pieces become integrated into larger units.
Mayers categories of propositional knowledge and comments
Kinds of propositional knowledge–(a) factual e.g. equations, (b) syntactic–recognize appropriate forms, (c) semantic e.g. physical world, (d) schematic e.g. structural relations among parts and types, (e) strategic e.g. approach to solving problems
I am not real happy about the five categories of knowledge that Mayer uses. Its not a bad first step, but I have some problems with it. More now that I am more of an expert than when I first encountered it. Particularly, I have trouble understanding Mayers difference between Factual and Semantic knowledge. Both of these refer to having some knowledge of the Domain under study.
The richness of understanding grows with the gaining of expertise. The schemata that one uses to account for the empirical observations get larger and more interconnected.
Syntactic knowledge could be the learning of equations, vocabulary, abbreviations, symbols, particular forms of acceptable sentences, etc.
Semantic knowledge in the linguistic sense is knowing how to map the words, sentences, and equations onto the domain. This is not easy. After identifying the basic laws of motion Newton spent years trying to apply them to different domains and other physicists continued that process for two hundred more years.
Schematic knowledge looks at the domain and identifies similarities and differences among parts. What is deemed similar often changes as one gains expertise. As stated in the text, novices are much more likely to be captivated by surface similarities and experts abstract or implicit ones.
Strategic knowledge is more similar to procedural knowledge–knowing how. How one is likely to attempt to solve a problem is likely to vary as a function of the experience one has with the domain. As one becomes more familiar she is much more likely for obvious problems solve them by forward chaining or working forward. However, the data for real problems, i.e.,