Theories for the Development of Expertise

The Nature or Nurture of Expertise

Historically, expertise has been strongly correlated with inherent ability. Experts were thought to be “born” and required training only to reach their highest level of performance. This was based on ideas by Galton (1869 as cited by Macnamara et al (2014)), a geneticist, who noted that excellence in the arts and sciences tended to run within families. However, this theory alone is in contrary to what is observed in surgical training, where despite initially showing poor aptitude for practical skill, most novices will progress and become expert surgeons. Therefore, whilst innate ability is undoubtedly an important factor when carrying out a task, is it really necessary for the development of expertise?

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The current view, first suggested by behavioural psychologist Watson (1930), completely moves away from the need for innate ability, and suggests that experts are “made” through practice, determination and hard-work (as cited by Macnamara et al (2014)). This theory is supplemented by Ericsson et al (1993), who state that while amount of practice and experience play an important role in the development of expertise, quantity alone is insufficient, but rather quality in the form of sustained deliberate practice is more important in the development of expertise. Ericsson et al (1993) defined this as practising individual skills with the specific aim of improvement, and famously quoted that 10000 hours of deliberate practice (DP) was required to attain expertise, which they based on the estimated cumulative quantity that the best musicians engaged in over their careers.

DP hence involves practising the skill at progressively more challenging levels, with feedback and reflection, in an attempt to master it. I am able to relate to this as a musician myself; I was taught never to practise by playing the same piece of music over and over again. Rather I practise my fingering with the specific intention of becoming a better pianist by challenging myself with progressively faster and more technically challenging pieces of music. Thus, whilst frequent repetition may maintain my skill level, DP is crucial for advancement. Similarly, Rees-Lee and Kneebone (2015) describe the process of DP in tailors whereby the initially learn to practice on cloth and then progress to trousers and jackets. While this sequential training is similar to surgery in that the trainee starts with suturing and then progress to operations, the benefit of a graded training program in surgery over the apprenticeship in tailoring is that of a curricula whereby increasing levels of difficulty are specifically introduced at regular intervals over the course of the training program, thus facilitating DP and development of expertise.

On the contrary, Ericsson et al and the theory of DP has been criticised for placing no weight on innate talent. DP alone does not explain why only certain people are able to successfully take up playing a musical instrument. Macnamara et al (2014) argue that the majority of people will stop doing what they are not good at, and thus talent must precede DP. Grantcharov and Reznick (2009) were critical of the 10000 hours within the surgical domain, as it is based on the assumption that surgical trainees learn at the same rate, which is not the case. Recently, Hambrick et al (2014) and a subsequent meta-analysis by Macnamara et al (2014) have shown that within the domains of music, chess, education, sport and professions there is a large variance that cannot be explained by DP. Whilst the effect of DP was strong on music, chess and sport, it was extremely weak on education and professions. This may be because DP isn’t as defined in the latter activities, or alternatively performance in these activities is much less predictable (for example handling emergencies in surgery, or teaching students of varying knowledge levels). Subsequently, they concluded that while DP is a very important predictor of individual differences in performance, it isn’t as significant as Ericsson et al have stated.

Overall, it seems evident that in both surgical and non-medical professions, the purpose of the selection process is to pick those candidates that demonstrate the innate abilities required to be a member of their community of practice. It is however sustained DP that will allow the individual to become an expert. Sadideen et al (2013) further suggests that innate ability will both speed up the rate at which this expertise is achieved, but will also be the limiting factor to how far one can progress.

Efficiency versus Innovation

As discussed in the previous section, sustained deliberate practice (DP) plays a critical role in the development of expertise. Through progressive challenges, the purpose of DP is to move the expert away from automation. Thus, the term “expert” can be split into two types; the routine expert and the adaptive expert (Alderson, 2010).

The routine expert is one that has developed high levels of proficiency in a task by sheer volume of repetitive experience, which has subsequently lead to automation of the task. With a limitation to the cognitive process during automation, routine experts will try to adapt a problem to their existing solution, and as such Mylopoulos and Regehr (2007c) use the term “experienced non-expert” to describe these individuals. This is supported by Gawande (2002 as cited by Alderson, 2010) who argues that anyone can therefore become a routine “expert” within a narrow range if the environment of the task remains stable. The craft of glass blowing is an example of routine expertise. Here the blower has physical mastery of the materials and tools required to successfully blow glass, and as such it has become an automated process. Atkinson (2013) describes that within glass blowing there is little or no room for alternate approaches or novelty. Tried and tested methods are the shared culture of the craft and within this community of practice, the same technique and materials are used worldwide. Pedagogy in glass blowing is not learner-centred, but revolves around the technique, tools and materials, and whilst there is the stability within the craft, there is also a limited routine range. In contrast, expertise in the surgical field requires a greater flexibility due to the highly individualised characteristics of each patient, and greater innovation is required to deal with the regular challenges (Atkinson, 2013). Thus the surgeon must develop adaptive expertise to broaden their knowledgebase rather than just applying it.

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Adaptive experts seek and utilise new problems and challenges to encourage DP so as to extend their knowledge and boost performance (Alderson, 2010). They treat learning as a continuous ongoing process, developing flexible and creative methods of solving problems, rather than speed and automaticity. In essence, adaptive experts don’t try to do tasks more efficiently, they try to do it better (Mylopoulos and Regehr, 2007c). Subsequently, the adaptive expert continually seeks to move centripetally within the model of legitimate peripheral participation; they are not happy in the periphery unlike their routine expert counterparts (Mylopoulos et al, 2009). Through their flexibility and understanding of their accumulated knowledge, adaptive experts are better able to apply their past knowledge to deal with new problems (Mylopoulos and Regehr, 2007b). Kneebone and Woods (2014) demonstrate this by simulating an operation using a retired surgical team. Here it is evident that within the right simulated context of the operating theatre and the familiarity of the same team, the adaptive expertise of the surgeon can be utilised many years later to perform the surgery. It can be argued that other non-medical experts such as musicians are also able to do this if asked to play a piece of music many years later. From personal experience as a musician, I would counter-argue that in this situation routine expertise is used as they would just be repeating a piece of music from memory, whilst the surgeon would be utilising their knowledge and applying it to operate on a new case with all of its various anatomical and physiological permutations (adaptive expertise).

Wulf et al (2010) suggests that one should push away the automaticity and non-cognitive practice associated with the routine expert, and instead aim for adaptive expertise. Although Alderson (2010) supports this statement, he points out that in surgery the processes of adaptive expertise such as DP, seeking challenges and innovation need to be monitored to prevent harm to the patient that may arise from the overenthusiastic surgeon forever seeking new knowledge and thus persistently “at the bottom of the procedural learning curve”. On the contrary, Guest et al (2001) argues routine and adaptive expertise are not separate entities, but rather two ends of a continuous spectrum. They argue that while adaptive expertise should predominate in surgery, by automating basic technical skills, this will help to free-up time for the cognitive processes needed to deal with and learn from the more important and complex situation. The true expert has therefore developed resources and processes that allow effective and efficient solutions for the routine problems of practice (e.g. pattern recognition aided by illness scripts and encapsulated concepts), thus allowing a reinvestment of the cognitive area liberated through the automation process towards innovation and extending new knowledge (Mylopoulos and Regehr, 2007c).