Peter A. Hancock, D.Sc., Ph.D. is Provost Distinguished Research Professor in the Department of Psychology and the Institute for Simulation and Training, as well as at the Department of Civil and Environmental Engineering and the Department of Industrial Engineering and Management Systems at the University of Central Florida (UCF). At UCF in 2009 he was created the 16th ever University Pegasus Professor and in 2012 was named 6th ever University Trustee Chair. He directs the MIT2 Research Laboratories and is the Associate Director of the Center for Applied Human Factors in Aviation (CAHFA). Prior to his current position he founded and was the Director of the Human Factors Research Laboratory (HFRL) at the University of Minnesota where he held appointments as Professor in the Departments of Computer Science and Electrical Engineering, Mechanical Engineering, Psychology, and Kinesiology, as well as being a member of the Cognitive Science Center and the Center on Aging Research. He continues to hold an appointment as a Clinical Adjunct Professor in the Department of Psychology at Minnesota. He is also an affiliated Scientist of the Humans and Automation Laboratory at Duke University, a Research Associate of the University of Michigan Transport Research Institute, and a Senior Research Associate at the Institute for Human and Machine Cognition in Pensacola, Florida. He is also a member of the Scientific Advisory Broad of the Hawaii Academy.
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Assessment and Utility of human Mental Workload: Past Successes and future challenges
When humans engage in the act of cognition there is an associated emergent affect which has been used to characterize reflections of both the idiographic and nomothetic degree of that challenge. Such mental workload assessment has proved to be a critical tool in the practical evaluation of human work, especially when that work primarily involves interactions with advanced technological systems. However, the history of mental workload assessment has not been without dispute. Some approaches have principally featured the distillation and effects of the objective task to be performed; a nomothetic and task-load dominant perspective whose methods include approaches such as cognitive task analysis among a number of others. Alternative investigations have emphasized the way in which the individual reacts to resolve the externally imposed demand and such adaptive reactions are often couched in the terms of experimental and cognitive psychological research. For yet another constituency, the central concern is the efficiency of the on-going performance; often taken as indicative of current and perhaps also prospective capacity. I shall argue that each have, in their own way, contributed to the success of mental workload as both a construct and a practical tool. Yet, inter-mixing and interpolating these differing perspectives has led to definitional and utilitarian disputes. I shall illustrate the problems of some resultant apparent impasses through discussion of the association-insensitivity-dissociation matrix which arises when different reflections of mental workload either agree (associate), disagree (dissociate), or are indifferent (insensitive), one to another. Resolution of such methodological concerns leads us toward a series of questions about the nature of the workload signal. While momentary workload level has been a well explored metric, many other temporal and functional characteristics (e.g., the effects of prospective load, the influence of previous load level, etc.) have not yet been sufficiently explored. I shall layout a brief road map for such exploration. Finally, I shall argue that not all workload is equal. Classic workload assessment provides little differentiation between those tasks that are involving and engaging versus those that are rote and repetitive, even when their absolute workload scores are objectively equal. I shall argue that our community now needs to explore and exploit these important affective dimensions, especially in light of the growth in interaction with ever more automated and ever more autonomous systems. Avenues toward such hybrid model developed are adumbrated.
Chris Wickens currently a visiting professor of psychology at Colorado State University. He is also currently a senior scientist at AlionScience Corp. in Boulder Colorado. He received his BA in physical sciences from Harvard University (1967), his PhD in Experimental Psychology from the University of Michigan in 1974, and served in the US Navy for 3 years. He joined the faculty of psychology at University of Illinois in 1974, and in 1984 he became Head of the Aviation Human Factors Division, and in 1994 the Associate Director of the University of Illinois Institute of Aviation. He has also served three years as a visiting Professor in the Department of Behavioral Science at the US Air Force Academy.
He has written two textbooks on Engineering Psychology, and on Human Factors, now in their 4th and 2nd editions respectively, and also co-authored two books on Air Traffic Control human factors. He has received the Airbus Award from the Flight Safety Foundation, the FAA’s Excellence in Research award, and the Arnold Small Award from the Human Factors & Ergonomics Society. His current research interests are in the applications of attention theory to display design, real world multi-tasking, mental workload prediction & assessment and human-automation interaction. Since joining AlionSciences in 2005 he has developed computational models of these processes with special application to aerospace systems. He has been an avid mountain climber.
Mental Workload: assessment, prediction and consequences
Mental workload (MWL) can be examined from three perspectives: assessment, prediction and consequences. In spite of the fact that research on the topic of MWL has grown exponentially since the 1970s, and continues to grow, the vast majority of published work has been on mental workload assessment, to the point of diminishing returns. Considerably less has been done on predictive models, where workload may be defined by such measurable task characteristics as cognitive complexity and working memory load. Finally, it appears that there is least research on the consequences of high MWL or effort to task performance and, in particular, task decision strategies. Hence I will talk only briefly about assessment, more on prediction, and still more on how predicted workload can influence decision task strategies and how this linkage can be modeled. Thus the talk will focus on how predicted MWL or mental effort can influence the decision of:
- What information to seek
- Which tasks to choose in a task switching setting
- How much effort to invest in a learning situation
- Whether and when to use automation
- Whether to behave in a risky fashion
The role of computational models of effort in these choices will be discussed.
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Karel completed his study in Psychology at the University of Groningen, major in experimental psychology and psychophysiology, by the end of 1979. Then as a PhD student at the Institute for Experimental Psychology wrote a thesis titled “Event Related Potentials and Information Processing”. From 1983 on he was senior researcher at the Traffic Research Centre of the University of Groningen. In 1986 he became head of the department of “Task Performance and Cognition”. Since 1994 he was additionally appointed Research Manager of the Institute, responsible for the Centre’s research planning en quality control. After the Centre was closed at 1 January 2000, he became (part-time) associate professor at the department of Experimental and Work Psychology of the University of Groningen and (part-time) full professor at the department of Transport Policy and Logistics at Delft University of Technology. Presently he is full professor at both Universities. Acquisition of grants and subsidies has been an integral part of his job since 1986, from National and International Authorities (NWO, Ministries and European Commission) as well as various companies in the pharmaceutical and automotive industry. During his scientific career he (co-)authored over 400 publications. He also organised and (co-) edited an International Handbook, and a large number of conference proceedings. Research interests are human factors in occupational settings, particularly traffic and transport. Research topics include effects of psycho-active substances and fatigue on driving behaviour, measurement methods, psycho-physiological aspects of task performance, work load in traffic, specifically under and with ICT applications. He participated, and still does, in large European projects focusing on design and evaluation of new telematics applications (ADAS) in traffic.
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The assessment of mental workload, combining objective and subjective measures
Many accidents in industry, in the workplace, and certainly in traffic are mainly caused by, or at least related to, inadequate mental workload, whether either too low (vigilance) or too high (stress), not optimal. The second half of the 20th century faced us with increasing traffic density and complexity, in the air and on the ground, leading to problems in the sense of human error, extreme effort, fatigue, stress, discomfort and what have you, urging the study into the development of measurement of mental workload. Similar needs were met in industry, together provoking a host of research with respect to objective measurements and subjective measurements of mental workload. Mental workload is related to the proportion of the capacity an operator is spending on task performance. The measurement of mental workload is the specification of that proportion. Task demands are managed by the operators, as far as needed thus leading to at least minimal output, i.e. a task performance avoiding accidents. In order to assess mental workload, the cost of the desired, target level of performance that should be achieved (or continued) is the topic of interest. These costs are referred to as mental effort which is comparable to what may be referred to as ‘trying hard enough’, struggling to stay on the safe side. Changes in effort will be visible in performance indices and in self-reports of the operators themselves, or alternatively, in changes in certain physiological measures. These days, the traffic environment and participation itself is gaining in complexity, notwithstanding all ICT devices that are well-intended designed to support the traffic participant by (aiming at) minimizing the complexity. However, the drawback is that ICT support itself generates information, in a variety of different forms but still or again burdening the operator, be it not always consciously. The new appeal to the traffic participant compels another view on the sources and consequences of mental workload in the modern operator environment. We will have to employ full sail for the pitfalls that we are facing now.