ABSTRACT
Operation of heavy construction equipment is a cognitively demanding task, and training of operators is risky and costly. Advances in computer-based virtual training systems have emerged as a solution to limitations associated with use of actual equipment, effectively reducing risk and on-machine training time, and allowing flexibility in learning environments. We report an experiment that compared two training methods for the initial phase of learning to operate a simulated hydraulic excavator: (a) audiovisual instructions for teaching operation of controls, and (b) hands-on operation of the excavator. After receiving one or the other of these training methods, participants performed a Controls Familiarization test that requires execution of appropriate joystick control actions in response to verbal stimuli presented visually that correspond to the desired action (e.g., “Activate the bucket close function”). For both groups, the actions were executed faster and with fewer errors as they practiced the Controls Familiarization task. Participants taught with the instructional method performed better than those who learned control operation through hands-on exploring, with this benefit apparent mainly for the two more difficult control functions—moving the stick in or out, and opening or closing the bucket. Increasing the allotted time for hands-on learning from 1 to 5 min did not seem to increase the amount of learning that took place. Instructions convey control–machine relations that are difficult to learn just through “free play” operation of a simulated machine.
Funding
This research was made possible by support from the National Science Foundation (NSF) under Grant No. CMMI-0700492. Opinions, findings, conclusions, or recommendations are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Additional information
Notes on contributors
Bhushan N. Bhalerao
Bhushan N. Bhalerao received his Master’s degree in Civil Engineering from Purdue University in 2009. He is currently Director at MEP System Solutions Pvt. Ltd in Pune, Maharashtra, India, where he specializes in Plumbing Engineering and Fire Suppression Systems Design Consultancy.
Phillip S. Dunston
Phillip S. Dunston received his PhD from North Carolina State University in 1995. He is currently a professor of civil engineering at Purdue University, where he specializes in advanced technology applications for construction equipment and visualization.
Robert W. Proctor
Robert W. Proctor received his PhD from the University of Texas at Arlington in 1975. He is currently a distinguished professor of psychological sciences at Purdue University, with courtesy appointment in the School of Industrial Engineering, where he specializes in basic and applied human performance.