Deriving and analyzing performance strategy in a two-dimensional drawing task

Abstract This research determined the performance strategy of six expert users on an engineering drawing task. Six experts were required to complete one engineering drawing task during which the whole drawing process was video-recorded. By reviewing the videotape together with the keystroke data, the drawing process of each subject was repeated by the experimenters to analyze mental pauses and operation sequence in terms of execution steps (functional units) separated by large mental pauses. These execution steps were grouped into 13 unit tasks to classify a subject's performance strategy into two major types. Different unit tasks and performance strategies were compared by several performance measures: physical time, small mental time, large mental time, and error time. These performance time measures were well predicted by a U-shaped model using the unit task (sequence) number as the predictor. This could have been caused by the proposing of a feasible solution at the initial stage, and the increase in working memory load caused by the gradual increase in graphic components and constraints between components toward the end of the drawing process. Finally, a flowchart formulated with the unit tasks was utilized to summarize the strategy of each individual subject. A flowchart constructed using this approach can be regarded as a conceptual model in future training of novice users when learning a new computer language or software. Relevance to industry This research determined the performance strategy of six expert users on an engineering drawing task. It demonstrated that flowcharts derived from the analysis of unit tasks can be utilized to describe the strategy of each individual subject. The same analytical approach can be adapted to build similar models for other software packages and application domains.