Expertise Development for Next-Generation Digital Learners

Expertise Development for Next-Generation Digital Learners

Eulho Jung (Boise State University, USA), Doo Hun Lim (University of Oklahoma, USA) and Soo Jeoung Han (Boise State University, USA)
DOI: 10.4018/978-1-5225-3873-8.ch003
OnDemand PDF Download:
$30.00
List Price: $37.50

Abstract

As the nature of work has become much more complex and sociotechnical, the needs for developing expertise are high. Research on expertise development are diverse (Bjork, 1994; Einstein & McDaniel, 2005; Schneider et al., 2002), but empirical studies intended to bridge expertise development and instructional design theories are relatively scarce (Ertmer et al., 2008; Fadde, 2009). This chapter addresses why and how scholars and practitioners should foster expertise development skills for Next-Generation digital learners.
Chapter Preview
Top

Expertise Studies Overview

Developing expertise takes a substantial amount of time. Ericsson (2009) stated it could take up to 10 years of experience and deliberate practice to declare having expertise. However, schools as well as non-profit and for-profit organizations have always been interested in advancing training methods that help learners/trainers learn faster and more efficiently. To this end, researchers and practitioners have begun developing methods to help non-experts perform like experts by developing theories and models to identify what to teach. Some of the tools and methods that are widely recognized in the field include Macrocognition (Patterson & Miller, 2012; Schraagen et al., 2000), Human-Centered Computing (Hoffman & Militello, 2012), Naturalistic Decision Making (Zsambok & Klein, 2014), Cognitive Systems Engineering (Hollnagel & Woods, 2005), Cognitive Task Analysis (Clark & Estes, 1996; Crandall, Klein, & Hoffman, 2006; Feltovich et al., 1997; Hollnagel, 2003; Jenkins, 2009; Lukas & Albert, 1993), and the field of Expertise Studies in general (Ericsson, 2009; Ericsson et al., 2006; Hoffman, 2007). In order to synthesis these efforts, Hoffman et al. (2013) proposed a concept called Accelerated Expertise, that suggested ways by which to accelerate the learning process to make a non-expert appear to be an expert.

Key Terms in this Chapter

Deliberate Practice: Deliberate practice is a highly structured activity engaged in with the specific goal of improving performance.

Pattern Recognition: Pattern recognition is the process of classifying input data into objects or classes based on key features.

Cognitive Task Analysis: Cognitive task analysis (CTA) is a type of Task analysis aimed at understanding tasks that require a lot of cognitive activity from the user, such as decision-making, problem-solving, memory, attention and judgement.

Metacognition: Metacognition is thinking about one's thinking.

Situational Awareness: Situational Awareness is the ability to identify, process, and comprehend the critical elements of information about what is happening to the team with regards to the mission.

Expertise: Basis of credibility of a person who is perceived to be knowledgeable in an area or topic due to his or her study, training, or experience in the subject matter.

Novice: Literally, someone who is new—a probationary member who has had some (“minimal”) exposure to the domain.

Shared Leadership: Shared leadership is a leadership style that broadly distributes leadership responsibility, such that people within a team and organization lead each other.

Model Domain Learning (MDL): The Model of Domain Learning (MDL) is an alternative perspective on expertise that arose from studies of student learning in academic domains, such as reading, history, physics, and biology.

Complete Chapter List

Search this Book:
Reset