Adaptive expertise

Adaptive expertise is a broad construct that encompasses a range cognitive, motivational, and personality-related components, as well as habits of mind and dispositions. Its empirical validity has been examined in a number of training and learning contexts. The term was first coined by Giyoo Hatano and Kayoko Inagaki¹, to tease out the variability within groups of experts. To illustrate, imagine two sushi chefs: one who makes every piece perfectly but routinely makes the same few types over and over, and one produces new menus frequently. To some, this is an unfair comparison, as it is the person plus the situation/environment that allow us to see behavior. For the former sushi chef, the routine construction may be imposed, and the chef may be able to break out of the routines easily given a different situation. Learning Scientists are interested in the construct, in part because they would like to understand different learning trajectories may or may not provoke the ability to break out of routines when called upon to do so.

Expertise can be thought of as a continuum of adaptive ability making the distinction between those characterised as ‘merely skilled versus ‘highly competent’; as ‘artisans’ versus ‘virtuosos’ ⁵; or as those approaching a problem in a routine versus more flexible way ². The notion of adaptive expertise highlights that a new problem can be viewed as a point of departure for exploration ⁵ and not just an opportunity to do a task more efficiently ⁶. Adaptability enabled the Apollo 13 crew to successfully build an air filter from ill-fitting parts whilst in space, while the TV chef, Jamie Oliver, is able to flamboyantly and creatively produce good food using only simple ingredients.

A distinguishing feature of adaptive expertise is the ability to apply knowledge effectively to novel problems or atypical cases in a domain without glossing over distinctive factors. Holyoak⁷ characterised adaptive experts as being capable of drawing on their knowledge to invent new procedures for solving unique or fresh problems, rather than simply applying already mastered procedures. Adaptability allows experts to recognize when rules and principles that generally govern their performance do not apply to certain problems or situations ⁸. Moreover, studies have shown that this flexibility can result in better performance than that of experts who do not display cognitive flexibility, resulting in, amongst other things, better technical trouble shooting ⁸; workplace error avoidance; and more accurate medical diagnosis ¹⁰. John D. Bransford considers this flexible, innovative application of knowledge, in large part, underlies adaptive experts’ greater tendency to enrich and refine their understanding on the basis of continuing experience to learn from problem-solving episodes ⁶.

A Model of Adaptive Expertise

One model of adaptive expertise ² looks at two dimensions along which a learner may develop: efficiency and innovation. All experts are efficient when solving problems that are routine. When presented with a problem that is not routine, or when transferring into a different situation, the expert may innovate.

Schwartz, Bransford and Sears ² have graphically illustrated how developing adaptive expertise emerges through what they refer to as an “Optimal Adaptability Corridor” (OAC). While expertise involves fluency with routines, which they label ‘Routine Expert’, it becomes increasingly important in dynamic and variable situations that more than routine solutions are required. When innovative thinking is part of a problem solution, this leads to becoming an ‘Adaptive Expert’². Routine expertise can be envisioned as efficiency gained through routine practice and is, almost by definition, domain specific. Adaptive expertise takes this kind of efficiency along with flexibility and innovation to address real-time problems. Having this capacity provides the context and focus for the learning environment and affords opportunities to move an individual’s development along that corridor towards realising their optimal adaptability. The work carried out by Schwartz and his colleagues relates to the theory of Transfer of Learning

Calculating Adaptive Expertise

Adaptive expertise is tied to the ability to transfer, that is, to apply knowledge to solving problems in a new context by recognizing the underlying similar concepts or principles that govern the given situation. A problem may be composed of factual knowledge, conceptual knowledge, and require transfer. One group^3,4 of researchers looking specifically at the development of adaptive expertise in bioengineering operationalize adaptive expertise as the following: $AE=0.14F\; -\; 0.36C\; +\; 1.27T$, based on experimental results, but they do not yet know if these weights are generalizable.

ee also

* Expertise
* Expert systems
* Skilled worker
* Transfer of Learning

References

1. Hatano, G. and K. Inagaki (1986). "Two courses of expertise." Child development and education in Japan: 262–272.

2. Schwartz, D. L., Bransford, J. D. & Sears, D. (2005). Efficiency and innovation in transfer. Transfer of Learning from a modern multidisciplinary perspective. J. Mestre. Greenwich, CT, Information Age Publishing: 1-51. 3. Pandy, M. G., A. J. Petrosino, et al. (2004). "Assessing Adaptive Expertise in Undergraduate Biomechanics." Journal of Engineering Education 93(3): 211-222. 4. [http://fie.engrng.pitt.edu/icee2006/]

5. Miller, R.B. (1978) ‘The Information System Designer’ In Singleton, W.T. (Ed.) The Analysis of Practical Skills. Baltimore, MD: University Park Press.

6. Bransford, J. D., Brown, A. L. & Cocking R. R. (2000) . Washington: National Academy Press

7. Holyoak, K. J. (1991) Symbolic Connectionism: Toward third-generation theories of expertise In K. A. Ericsson & J. Smith (Eds.) Toward a General Theory of Expertise: Prospects and Limits 301-335. Cambridge, UK: Cambridge University Press.

8, Gott, S., Hall, P., Pokorny, A., Dibble, E., & Glaser, R. (1992) A naturalistic study of transfer: Adaptive expertise in technical domains In D. Detterman & R. Sternberg (Eds.) Transfer on Trial: Intelligence, Cognition, and Instruction 258–288. Norwood, NJ: Ablex.

9. Woods, D.D., Johannesen, L., Cook, R.I., and Sarter, N.B. (1994) Behind Human Error: Cognitive Systems, Computers, and Hindsight. Dayton, OH: Crew Systems Ergonomic Information and Analysis Center

10. Feltovich, P. J., Spiro, R. J., & Coulson, R.L. (1997) Issues of expert flexibility in contexts characterized by complexity and change In P. J. Feltovich, K. M. Ford, & R. R. Hoffman, (Eds.) Expertise In Context 126–146. Menlo Park, California: AAAI Press/MIT Press.