Advancing the practice of cognitive task analysis: a call for taxonomic research

Abstract

Cognitive task analysis (CTA) captures unobservable cognitive processes, decisions and judgments of expert performance. Over 100 different CTA methods are identified in prior literature. However, existing classifications typically sort techniques by process rather than outcome, application or causal mechanism. Therefore, techniques can be misapplied and comparative analysis of methods made difficult. Based on the frequency distribution of CTA methods in 1065 studies, a subsample representing 60% of the most frequently published methods was coded based on elicitation and analysis techniques. Consistency of resulting applications was assessed. Inconsistent matching of CTA methods and subsequent applications indicate CTA is currently more craft than technology. Therefore, there is no robust basis for selecting one method over another for research or practice. Specific challenges include comparing the reliability and validity of individual methods and optimising selection of techniques for intended applications. Developing a causal taxonomy may facilitate such advancements.

Designing simulator-based training: An approach integrating cognitive task analysis and four-component instructional design

“…Both mental actions and movements related to complex surgical tasks should be carefully identified before implementing in training programmes (Kneebone 2003). Development of simulator-based training should preferably start with a structured analysis of the complex procedure to be simulated using 'cognitive task analysis' (CTA), a generic term referring to a variety of interview and observation methods aimed at unravelling experts' performance of complex tasks in order to capture the knowledge, thought processes and goal structures experts rely on during task performance (Clark et al 2008;Yates & Feldon 2010). Before this information can be used in developing simulator-based training, it needs to be translated into instructional design focusing primarily on the identification, ordering and presentation of information about a skill in a blueprint for training that can help learners acquire skills in a coordinated and integrated manner (Clark et al 2008).…”

Evaluation of the Educational Value of a Virtual Reality TURP Simulator According to a Curriculum-based Approach

“…Therefore, in the future, we recommend to use a more structured method for the TNA, integrating psychomotor and cognitive skills, for example, cognitive task analysis (CTA). 36,37 Cognitive task analysis refers to a variety of interview and observation methods aimed at unraveling experts' performance of complex tasks to capture the knowledge, decision-making processes, and goal structures the experts rely on during task performances. 36,37 In CTA, it is important to identify which part of a task can be classified as ''automatic,'' where experts perform tasks without conscious awareness, and which parts as ''nonautomatic,'' requiring conscious attentions, also for experts.…”

A multi-disciplinary review of knowledge acquisition methods: From human to autonomous eliciting agents

“…To date, the literature focused more on the internal mechanism of the KA methods, and less on establishing an accurate description of the KA process, or a relation between the process and the purpose of the exercise [49,207,51,210,211]. Thus, the choice on how to conduct a KA exercise is strongly dependant on the purpose of the exercise.…”

“…In Cooke's study, the formalisation stage is explicitly associated with the formulation of a computational model, while Crandall and colleagues state that representation means "displaying data, presenting findings, and communicating meaning" that is, communicating the output of the analysis step. In a different approach to the ones described above, Yates and colleagues [210,211] acknowledge the three stages in the KA process; however, they note that the last two, analysis and representation, are usually treated together, being inseparable in the context of modelling the knowledge acquired through elicitation. Researchers in Knowledge Discovery also acknowledge the three stages model, with the three stages named: data preprocessing, data mining, and knowledge interpretation and evaluation [29,152,148,147].…”