Knowledge Domains and Domain Learning

Maggioni, Liliana; Alexander, Patrick

doi:10.1016/b978-0-08-044894-7.00483-8

Cited by 3 publications

(2 citation statements)

References 30 publications

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“…Overall, structured and ill-structured domains are different regarding several factors (see Table 1). Table 1 is roughly similar to Shanteau (1992, p. 259) and was influenced by the sources in this chapter, especially Alexander (1992aAlexander ( , 1992b, Maggioni and Alexander (2011), Ericsson (2018a), Ackerman (2011), andvan de Wiel et al (2004).…”

Section: Characteristics Of Commercial Domainssupporting

confidence: 54%

“…According to Alexander (1992aAlexander ( , 1992b and Maggioni and Alexander (2011), domains are defined by the body of knowledge that refers to a particular part of the world, a studied area, or a discipline. This knowledge is learned in formal contexts (e.g., school) or informally during practice in the domain (Alexander, 1992a).…”

Section: Characteristics Of Commercial Domainsmentioning

confidence: 99%

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Expertise Development in the Workplace Through Deliberate Practice and Progressive Problem Solving: Insights from Business-to-Business Sales Departments

Köhler

Rausch²

2022

Vocations and Learning

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Expertise is featured by continued high performance in a particular domain. Expertise research has primarily focused on absolute expertise in structured domains such as chess and emphasized the significance of deliberate practice for expertise development. We investigated the development of relative expertise in commercial domains as part of ill-structured domains. Due to the ill-structuredness and acknowledging the use of the term expert in organizational practice, we developed a taxonomy to distinguish between four types of experts in the broader sense (relative expert, managerial relative expert, evolved specialist, and native specialist). Eighteen peer-nominated individuals from business-to-business sales departments from four German organizations participated in our interview study. A content analysis was applied using both deductive and inductive categorizations. The interview data clearly corresponds to the concept of progressive problem solving rather than to the concept of deliberate practice. Almost all our respondents referred to either “being thrown in at the deep end” by others (assigned complex tasks) or “jumping in at the deep end” of one’s own accord (self- selected complex tasks). However, the interview partners described features of deliberate practice for novices. In this very early stage of expertise development, more experienced colleagues structure parts of the ill-structured domain and enable deliberate practice while for advanced beginners and later stages expert development rather resembles progressive problem solving. Our results provide implications on how to foster expertise development in ill-structured domains. Possible limitations arise from the small sample, the peer-nomination process, and the retrospective nature of interview data.

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