Reflections on the Study of Expertise and Its Implications for Tomorrow’s World

In this chapter, we reflect on the themes that emerged throughout this Handbook. First, we review why expertise is not always revered and ask whether this relates to the way expertise has been defined and measured. We then re-examine definitions of expertise presented throughout the Handbook as well as the idea that expertise is, in part, about increasing one’s cognitive ability to adapt to complexity. Next, we take a look at where we have been, as a community of communities of expertise researchers, and whether we are heading in good directions, placing an especial focus on how expertise is and should be measured. In the penultimate section, we present some ideas about future areas of research recommended by chapter authors. Finally, we present a potential way forward for researchers to continue to move the field of expertise studies in a positive direction and, ultimately, to better prepare individuals to operate effectively in tomorrow’s workplace.

Incident-Based Methods for Studying Expertise

Incident-based interview methods are powerful tools for studying expertise in context. They provide insight into expert cognition that cannot be obtained with other methods. They complement performance measures that show what an expert can do, by providing insight into what is going on in the interviewee’s head. These methods facilitate description of expertise in the context of work and aid in developing testable hypotheses. They can be used to uncover cognitive requirements to support acquisition of skill via decision support design and training. Findings can also be used to inform the design of tools to support expertise and descriptive models to inform basic research. This chapter discusses four types of incident-based interview methods, examines analysis strategies, and provides examples of products resulting from this type of research and their influence on applications. Practical issues associated with the use of incident-based interview methods are considered, and future directions are discussed.

Cognitive Flexibility Theory and the Accelerated Development of Adaptive Readiness and Adaptive Response to Novelty

This chapter examines expertise in complex and ill-structured domains from the perspective of cognitive flexibility theory (CFT). The emphasis is on adaptation under conditions of “ordinary novelty.” An approach to situational novelty via meta-features of an adaptive mindset that generalizes across cases in ways that content does not, and that fosters the skill of novel rearrangement of previously encountered case features in ways that are adaptive to new situations, is presented. The chapter describes CFT’s theoretical and empirical approach to combating rigidity and oversimplification, and to accelerating expertise in assembling “schemas of the moment” with learning based on the principled development and application of computer-supported case-based environments. Receiving special emphasis are many new modes of deliberate practice of adaptive flexibility. The chapter concludes with societal implications for today’s rapidly changing and increasingly complex world.

Expertise in Law Enforcement

The aim of this chapter is to provide an overview of expertise research in law enforcement and guidance for those planning on conducting research themselves. The chapter begins by describing conceptualizations of expertise in law enforcement, and offers a working definition. The chapter then identifies challenges facing researchers interested in conducting expertise research in law enforcement, and advises how to overcome those challenges. Next, concrete examples are provided of how research in this domain has been conducted. In doing so, the chapter covers a broad range of methods and highlights the subtleties that researchers new to the domain should consider when designing and conducting expertise research. Following that, key insights from the literature are described, covering the spectrum of expertise in law enforcement. Finally, directions for future research are suggested.

Stress, Skilled Performance, and Expertise

Experts must often execute cognitive and motor skills in demanding, potentially stressful environments. Broadly, stress impairs attention and working memory, increasing vulnerability to cognitive overload. Theories of attentional resources and cognitive skill acquisition suggest a Standard Capacity Model (SCM) of expertise and stress vulnerability. However, the SCM has several deficiencies including neglect of contextual factors and the complexities of stress. Theoretical challenges are compounded by methodological issues including the choice of stress measure, and individual differences in response. The interplay between stress and expertise is explored across four domains: test anxiety, sports performance, surgery, and vehicle driving. In each domain, stress is sometimes associated with overload, consistent with the SCM, such that expertise buffers stressor impacts. However, expert performance is also subject to domain-specific influences beyond cognitive capacity, including strategies for emotional regulation, choking under pressure, and aggressive behaviors. Thus, relationships between stress and expertise must be understood contextually.

Framing and Translating Expertise for Government

Expertise is of great value within and for government, which seeks to influence complex situations through the use of complex policy interventions. The framing of expertise in government, however, is not immune to popular narratives that we are all experts now and that all perspectives on an issue are of equal value, irrespective of who proposes them. This chapter describes the nature of government work and its challenges; the overlap between expertise, evidence, and values; how expertise has been considered over time in government, and the difficulty in identifying who the expert is. We then reconsider whether expertise is under threat, and identify research gaps that if addressed would support the further professionalization of the policy function in government.

Expertise in Weather Forecasting

Weather forecasting is a highly technical domain, relying on many kinds of technologies and many kinds of data. This chapter summarizes four research programs ranging from organizational to individual analyses to provide unique, complementary insights about expertise. Forecaster learning was highly dependent on the forecasters’ context, and whether they gained expertise depended on having a strong personal identity as a forecaster. How forecasters coped with risk and uncertainty suggests expertise is not just a deeper causative understanding, but an ability to provide an accurate forecast that serves users well. Novice forecasters employ rule-based knowledge, while experts employ a fluid and flexible application of knowledge. Expert forecasters have extensive, complex knowledge about each type of weather process they forecast, a knowledge that may be lost if not captured and passed on to the next generation. This empirical work on professional activity in context has the potential to invigorate studies of expertise.

Modeling Experts with Fast-and-Frugal Heuristics

According to the program reviewed in this chapter, people—including experts—use fast-and-frugal heuristics. These heuristics are models of bounded rationality that function well under limited knowledge, memory, and computational capacities. These heuristics are ecologically rational: they are fitted to the structure of information in the environment. While studying experts in the context of this program amounts to modeling them with fast-and-frugal heuristics, studying the acquisition of expertise focuses on how laypeople learn such heuristics. Experts can be viewed as intuitive statisticians. They have larger samples than novices and they are—through experience, education, and feedback—able to construct both accurate models of their environment and smart heuristics. Because fast-and-frugal heuristics do not require complex calculation and are typically easy to set up, this program offers a straightforward way to aid experts: After the heuristics’ performance has been determined under various environmental conditions, experts can be educated about these results.

Uncovering Expertise for Safe and Efficient Performance in Railroad Operations

This chapter provides an overview of the literature on expertise in railroad operations and how it contributes to overall safety and productivity. The chapter is informed by research conducted across multiple continents, including Australia, Europe, and the United States. While the primary focus is on locomotive engineers, expertise in other railroad positions (e.g., conductors, dispatchers) is also covered. The chapter begins with an overview of railroad operations and how expertise fits into the railroad enterprise. Methods used to uncover expertise in railroad research are summarized, followed by a review of the types of strategies that railroad workers exhibit. This includes cognitive as well as teamwork strategies that contribute to overall system safety and resilience. This is followed by a discussion of the impact of ongoing technological changes on the requirements for expertise, and the chapter ends with speculation on longer term changes in railroad technologies and the nature of expertise.

Reflections on the Professional Practice of Knowledge Capture

The practice of capturing cognitive performance and expertise has grown into a profession over the past several decades. This chapter offers reflections from a professional knowledge capturer. The chapter describes the scope of, uses for, and origins of knowledge capture. It then moves to a description of the praxis of knowledge capture, including a discussion of protocols and methods for knowledge elicitation, focusing on the components common to all capture methods—structure and probing questions. The issues of cognitive burden sharing across the capturer and holder, how purpose guides execution, and how constraints can shape practical developments in approaches to knowledge capture are also discussed. Throughout, the chapter offers illustrative stories of knowledge capture from the field. The chapter concludes by looking at future directions for the profession.