Determining the impact of task complexity on decision-making and retention in virtual industrial training

Abstract

This study examines the effect of task complexity and experience level on decision-making performance and retention after virtual industrial training. A virtual industrial training system (VITS) is introduced to investigate the relationship between retention, retention interval, risk perception, task complexity, experience level and the presence of a simulated accident. A similar model is developed for mental workload. Training conditions are varied so that the contribution of visual cues, auditory cues and written instructions can be tested. The cues in the virtual training system correspond to real conditions, and are included to provide some warnings that allow decision-making with lower risk and improved performance, even as task complexity increases. Decisions in different machining conditions in the virtual training system cause different machining outcomes such as simulated tool breakage, poor surface finish or good surface finish. This study considers subjects' decisions during a comparable real industrial task as well. Preliminary results regarding the relationships between learning, retention, and task complexity in the virtual and real conditions will be discussed. A discussion of the influence of hazards in the simulation environment on hazard perception and performance in the real task will also be discussed.