Expert Knowledge Measure
An Expert Knowledge Measure is knowledge measure of level of specialized knowledge held by an individual or entity in a specific domain.
- Context:
- It can (typically) be applied to Experts.
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- Context:
- It can be applied to expert entities like individuals, teams, or organizations to gauge their level of specialized knowledge.
- It can (often) be utilized in both academic and industry settings to understand and quantify the depth of someone's expertise in a designated field.
- It can be used to evaluate and compare the performance of various experts within the same domain.
- It can inform recruitment practices, promotions, and resource allocation by distinguishing between varying levels of expertise.
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- Example(s):
- An Expert Medical Knowledge, can identifies the level of medical acumen held by a medical professional.
- An Expert Legal Knowledge, can assess and rank the specialized legal knowledge of a legal professional.
- An Expert IT Knowledge, can gauge the level of expertise of an IT professionals in various facets of information technology..
- An Expert Automotive Knowledge, can be used to evaluate the knowledge level of an automotive professional.
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- Counter-Example(s):
- See: Expert, Knowledge, Expert System, Domain Specific Knowledge Base, Expert Legal Knowledge, Lay Knowledge, Subject Matter Expertise.
References
2023
- Web-search summary
- Expert knowledge refers to the extensive understanding and mastery an individual possesses in a specific field or profession as a result of in-depth study, experience, or training. This term implies a level of proficiency that often combines both knowledge and technical skill, but the demonstration of this expertise is critical in fostering respect and trust, especially in a workplace environment. Expert knowledge finds applications in various sectors, such as facility management, interlibrary loan duties, automatic text summarization, and studies around traffic-related air pollution. In these contexts, expert knowledge can shape decision-making, problem-solving, and the formulation of vital strategies or systems. Furthermore, expert knowledge can be seen as a key component in the development of working computer programs or prototypes. However, acquiring and utilizing such knowledge comes with challenges, such as societal politics, potential loss of personal judgment, and maintaining the quality of information.
In addition, expert knowledge plays a crucial role in public engagement with science and in distinguishing genuine expertise from non-expertise. The processes and landscapes of knowledge creation involve various types of knowledge, including professional, experiential, institutional, and social knowledge.
The concept of expert knowledge also delves into the realm of perceptual expertise, arguing that expert knowledge can be enriched and expanded through learning, which in turn influences their beliefs. This perspective counters the notion of cognitive permeation where cognition influences perceptual learning and subsequent beliefs.
In conclusion, expert knowledge is a dynamic and versatile concept encompassing a variety of disciplines and is steeped in both theoretical educational practices and practical applications. It is shaped by perception, learning, and the environment in which it applied.
- Expert knowledge refers to the extensive understanding and mastery an individual possesses in a specific field or profession as a result of in-depth study, experience, or training. This term implies a level of proficiency that often combines both knowledge and technical skill, but the demonstration of this expertise is critical in fostering respect and trust, especially in a workplace environment. Expert knowledge finds applications in various sectors, such as facility management, interlibrary loan duties, automatic text summarization, and studies around traffic-related air pollution. In these contexts, expert knowledge can shape decision-making, problem-solving, and the formulation of vital strategies or systems. Furthermore, expert knowledge can be seen as a key component in the development of working computer programs or prototypes. However, acquiring and utilizing such knowledge comes with challenges, such as societal politics, potential loss of personal judgment, and maintaining the quality of information.