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A workload model and measures for computer performance evaluation

A generalized workload definition is presented which constructs measurable workloads of unit size from workload elements, called elementary processes. An elementary process makes almost exclusive use of one of the processors, CPU, I/O processor, etc., and is measured by the cost of its execution. Various kinds of user programs can be simulated by quantitative composition of elementary processes into a type. The character of the type is defined by the weights of its elementary processes and its structure by the amount and sequence of transitions between its elementary processes. A set of types is batched to a mix. Mixes of identical cost are considered as equivalent amounts of workload. These formalized descriptions of workloads allow investigators to compare the results of different studies quantitatively. Since workloads of different composition are assigned a unit of cost, these descriptions enable determination of cost effectiveness of different workloads on a machine. Subsequently performance parameters such as throughput rate, gain factor, internal and external delay factors are defined and used to demonstrate the effects of various workload attributes on the performance of a selected large scale computer system.

Kerner, H.↗

The effects of control order, feedback, practice, and input device on tracking performance and perceived workload

The present experiment examined the influence of several task-related factors on tracking performance and concomitant workload. The manipulated factors included tracking order, the presence or absence of knowledge of performance, and the control device. Summed root mean square error (rmse) and perceived workload were measured at the termination of each trial. Perceived workload was measured using the NASA Task Load Index (TLX) and the Subjective Workload Assessment Technique (SWAT). Results indicated a large and expected effect for track order on both performance and the perception of load. In general, trackball input was more accurate and judged for lower load than input using a mouse. The presence or absence of knowledge of performance had little effect on either performance or workload. There were a number of interactions between factors shown in performance that were mirrored by perceived workload scores. Results from each workload scale were equivalent in terms of sensitivity to task manipulations. The pattern of results affirm the utility of these workload measures in assessing the imposed load of multiple task-related variables.

Hancock, P. A.↗

Quantitative EEG patterns of differential in-flight workload

Four test pilots were instrumented for in-flight EEG recordings using a custom portable recording system. Each flew six, two minute tracking tasks in the Calspan NT-33 experimental trainer at Edwards AFB. With the canopy blacked out, pilots used a HUD display to chase a simulated aircraft through a random flight course. Three configurations of flight controls altered the flight characteristics to achieve low, moderate, and high workload, as determined by normative Cooper-Harper ratings. The test protocol was administered by a command pilot in the back seat. Corresponding EEG and tracking data were compared off-line. Tracking performance was measured as deviation from the target aircraft and combined with control difficulty to achieve an estimate of 'cognitive workload'. Trended patterns of parietal EEG activity at 8-12 Hz were sorted according to this classification. In all cases, high workload produced a significantly greater suppression of 8-12 Hz activity than low workload. Further, a clear differentiation of EEG trend patterns was obtained in 80 percent of the cases. High workload produced a sustained suppression of 8-12 Hz activity, while moderate workload resulted in an initial suppression followed by a gradual increment. Low workload was associated with a modulated pattern lacking any periods of marked or sustained suppression. These findings suggest that quantitative analysis of appropriate EEG measures may provide an objective and reliable in-flight index of cognitive effort that could facilitate workload assessment.

Sterman, M. B.↗

Workload: Measurement and Management

Poster: The workload research project has as its task to survey the available literature on: (1) workload measurement techniques; and (2) the effects of workload on operator performance. The first set of findings provides practitioners with a collection of simple-to-use workload measurement techniques along with characterizations of the kinds of tasks each technique has been shown reliably address. This allows design practitioners to select and use the most appropriate techniques for the task(s) at hand. The second set of findings provides practitioners with the guidance they need to design for appropriate kinds and amounts of workload across all tasks for which the operator is responsible. This guidance helps practitioners design systems and procedures that ensure appropriate levels of engagement across all tasks, and avoid designs and procedures that result in operator boredom, complacency, loss of awareness, undue levels of stress, or skill atrophy that can result from workload that distracts operators from the tasks they perform and monitor, workload levels that are too low, too high, or too consistent or predictable. Only those articles that were peer reviewed, long standing and generally accepted in the field, and applicable to a relevant range of conditions in a select domain of interest, in analogous "extreme" environments to those in space were included. In addition, all articles were reviewed and evaluated on uni-dimensional and multi-dimensional considerations. Casner & Gore also examined the notion of thresholds and the conditions that may benefit mostly from the various methodological approaches. Other considerations included whether the tools would be suitable for guiding a requirement-related and design-related question. An initial review of over 225 articles was conducted and entered into an EndNote database. The reference list included a range of conditions in the domain of interest (subjective/objective measures), the seminal works in workload, as well as summary works

Gore, Brian Francis↗

An Approach to Quantify Workload in a System of Agents

The role of humans in aviation and other domains continues to shift from manual control to automation monitoring. Studies have found that humans are often poorly suited for monitoring roles, and workload can easily spike in off-nominal situations. Current workload measurement tools, like NASA TLX, use human operators to assess their own workload after using a prototype system. Such measures are used late in the design process and can result in ex- pensive alterations when problems are discovered. Our goal in this work is to provide a quantitative workload measure for use early in the design process. We leverage research in human cognition to de ne metrics that can measure workload on belief-desire-intentions based multi-agent systems. These measures can alert designers to potential workload issues early in design. We demonstrate the utility of our approach by characterizing quantitative differences in the workload for a single pilot operations model compared to a traditional two pilot model.

Single Pilot Operations↗

Model-based estimation and prediction of task-imposed mental workload

Mental workload has been an area of intensive research for better than a decade. One specific area of interest in aircrew related workload research is concerned with the development of quantitative indices of workload in aircraft piloting tasks. This paper presents a model-based approach for quantifying mental workload in operational terms. The suggested modeling framework is based on an interpreted Petri net characterization of a task in which 'places' are equated to specific task-related activities and 'transitions' are viewed as internal or external forcing events. It is shown that within this framework quantitative assessments can be made of both cumulative and instantaneous workload associated with the performance of a task and its individual component subtasks. It is suggested that insights gained from analyzing task-specific workload within this modeling paradigm can suggest plausible explanations for reconciling discrepancies between subjectively elicited workload estimates and behavioral/performance measures.

Madni, A. M.↗

The dissociation of subjective measures of mental workload and performance

Dissociation between performance and subjective workload measures was investigated in the theoretical framework of the multiple resources model. Subjective measures do not preserve the vector characteristics in the multidimensional space described by the model. A theory of dissociation was proposed to locate the sources that may produce dissociation between the two workload measures. According to the theory, performance is affected by every aspect of processing whereas subjective workload is sensitive to the amount of aggregate resource investment and is dominated by the demands on the perceptual/central resources. The proposed theory was tested in three experiments. Results showed that performance improved but subjective workload was elevated with an increasing amount of resource investment. Furthermore, subjective workload was not as sensitive as was performance to differences in the amount of resource competition between two tasks. The demand on perceptual/central resources was found to be the most salient component of subjective workload. Dissociation occurred when the demand on this component was increased by the number of concurrent tasks or by the number of display elements. However, demands on response resources were weighted in subjective introspection as much as demands on perceptual/central resources. The implications of these results for workload practitioners are described.

Yeh, Y. H.↗

Modified Petri net model sensitivity to workload manipulations

Modified Petri Nets (MPNs) are investigated as a workload modeling tool. The results of an exploratory study of the sensitivity of MPNs to work load manipulations in a dual task are described. Petri nets have been used to represent systems with asynchronous, concurrent and parallel activities (Peterson, 1981). These characteristics led some researchers to suggest the use of Petri nets in workload modeling where concurrent and parallel activities are common. Petri nets are represented by places and transitions. In the workload application, places represent operator activities and transitions represent events. MPNs have been used to formally represent task events and activities of a human operator in a man-machine system. Some descriptive applications demonstrate the usefulness of MPNs in the formal representation of systems. It is the general hypothesis herein that in addition to descriptive applications, MPNs may be useful for workload estimation and prediction. The results are reported of the first of a series of experiments designed to develop and test a MPN system of workload estimation and prediction. This first experiment is a screening test of MPN model general sensitivity to changes in workload. Positive results from this experiment will justify the more complicated analyses and techniques necessary for developing a workload prediction system.

White, S. A.↗

Memory and subjective workload assessment

Recent research suggested subjective introspection of workload is not based upon specific retrieval of information from long term memory, and only reflects the average workload that is imposed upon the human operator by a particular task. These findings are based upon global ratings of workload for the overall task, suggesting that subjective ratings are limited in ability to retrieve specific details of a task from long term memory. To clarify the limits memory imposes on subjective workload assessment, the difficulty of task segments was varied and the workload of specified segments was retrospectively rated. The ratings were retrospectively collected on the manipulations of three levels of segment difficulty. Subjects were assigned to one of two memory groups. In the Before group, subjects knew before performing a block of trials which segment to rate. In the After group, subjects did not know which segment to rate until after performing the block of trials. The subjective ratings, RTs (reaction times) and MTs (movement times) were compared within group, and between group differences. Performance measures and subjective evaluations of workload reflected the experimental manipulations. Subjects were sensitive to different difficulty levels, and recalled the average workload of task components. Cueing did not appear to help recall, and memory group differences possibly reflected variations in the groups of subjects, or an additional memory task.

Staveland, L.↗

Inflight evaluation of four measures of pilot workload

Four measures of pilot workload were tested in the NASA C-141 Kuiper Airborne Observatory. The measured included a communications analysis, subjective ratings of workload, subjective ratings of additional factors related to workload, and heart rate. Data were collected for 11 flights, each of which lasted approximately seven hours. Heart rate was found to be significantly higher for the pilot who was flying than for the pilot who was not flying and it varied significantly across flight segments, peaking during landing and take off, particularly for the pilot in the left seat who was resonsible for aircraft control. For both left and right seats, the subjective assessment of stress rather than the subjective assessment of workload was significantly correlated with variation in heart rate. Frequencies of different types of communications varied significantly across segments of flight, however, they were not correlated with subjective ratings of workload. There was a significant difference between the left and right seats in the types of activities that contributed to their workload, however, workload was considered to be equivalent for the two.

Hart, S. G.↗

Predicting operator workload during system design

A workload prediction methodology was developed in response to the need to measure workloads associated with operation of advanced aircraft. The application of the methodology will involve: (1) conducting mission/task analyses of critical mission segments and assigning estimates of workload for the sensory, cognitive, and psychomotor workload components of each task identified; (2) developing computer-based workload prediction models using the task analysis data; and (3) exercising the computer models to produce predictions of crew workload under varying automation and/or crew configurations. Critical issues include reliability and validity of workload predictors and selection of appropriate criterion measures.

Aldrich, Theodore B.↗

Human workload in aviation

The application of human-factors analysis techniques to the evaluation of aircraft-crew workloads is discussed in an introductory overview. Consideration is given to the importance of workload for safety, crew size, automation, and certification; the definition and measurement of workload, physical vs mental workloads, subjective ratings, secondary tasks, biocybernetic measures, and attention and workload. Recent studies of pilot and ATC workloads are reviewed, and typical data are presented in graphs. Future trends are discussed, and it is predicted that increased cockpit automation will eventually require new methods to maintain operator attention rather than reduce workload.

Kantowitz, Barry H.↗

Voice measures of workload in the advanced flight deck: Additional studies

These studies investigated acoustical analysis of the voice as a measure of workload in individual operators. In the first study, voice samples were recorded from a single operator during high, medium, and low workload conditions. Mean amplitude, frequency, syllable duration, and emphasis all tended to increase as workload increased. In the second study, NASA test pilots performed a laboratory task, and used a flight simulator under differing work conditions. For two of the pilots, high workload in the simulator brought about greater amplitude, peak duration, and stress. In both the laboratory and simulator tasks, high workload tended to be associated with more statistically significant drop-offs in the acoustical measures than were lower workload levels. There was a great deal of intra-subject variability in the acoustical measures. The results suggested that in individual operators, increased workload might be revealed by high initial amplitude and frequency, followed by rapid drop-offs over time.

Schneider, Sid J.↗

Prediction of Traffic Complexity and Controller Workload in Mixed Equipage NextGen Environments

Controller workload is a key factor in limiting en route air traffic capacity. Past efforts to quantify and predict workload have resulted in identifying objective metrics that correlate well with subjective workload ratings during current air traffic control operations. Although these metrics provide a reasonable statistical fit to existing data, they do not provide a good mechanism for estimating controller workload for future air traffic concepts and environments that make different assumptions about automation, enabling technologies, and controller tasks. One such future environment is characterized by en route airspace with a mixture of aircraft equipped with and without Data Communications (Data Comm). In this environment, aircraft with Data Comm will impact controller workload less than aircraft requiring voice communication, altering the close correlation between aircraft count and controller workload that exists in current air traffic operations. This paper outlines a new trajectory-based complexity (TBX) calculation that was presented to controllers during a human-in-the-loop simulation. The results showed that TBX accurately estimated the workload in a mixed Data Comm equipage environment and the resulting complexity values were understood and readily interpreted by the controllers. The complexity was represented as a "modified aircraft account" that weighted different complexity factors and summed them in such a way that the controllers could effectively treat them as aircraft count. The factors were also relatively easy to tune without an extensive data set. The results showed that the TBX approach is well suited for presenting traffic complexity in future air traffic environments.

Lee, Paul U.↗

Pilot Workload and Speech Analysis: A Preliminary Investigation

Prior research has questioned the effectiveness of speech analysis to measure the stress, workload, truthfulness, or emotional state of a talker. The question remains regarding the utility of speech analysis for restricted vocabularies such as those used in aviation communications. A part-task experiment was conducted in which participants performed Air Traffic Control read-backs in different workload environments. Participant's subjective workload and the speech qualities of fundamental frequency (F0) and articulation rate were evaluated. A significant increase in subjective workload rating was found for high workload segments. F0 was found to be significantly higher during high workload while articulation rates were found to be significantly slower. No correlation was found to exist between subjective workload and F0 or articulation rate.

Bittner, Rachel M.↗

Comparison of Physical Workload Across Eva-Simulation Analog Environments: Hybrid Space Suit Simulator and Pressurized Suit Testing

NASA conducts research, testing, and training across a variety of analog environments to support characterization of human performance during Extravehicular Activities (EVAs). Time utilizing pressurized suits in an offloaded environment is both limited and expensive, making it challenging to carry out extensive research with these suits. The Human Physiology, Performance, Protection, and Operations (H-3PO) Laboratory at NASA Johnson Space Center designed a Hybrid Space Suit Simulator (HS3) as a low-cost, workload approximator and easy access research tool to provide relevant physical and cognitive workloads during simulated EVAs. A pilot study was conducted in a 1g analog environment where six healthy subjects (3 male, 3 female) underwent simulated 5-hour EVAs in the HS3. This study used a COSMED K5 portable metabolic analyzer and a Polar H10 heart rate monitor to evaluate physical workload during the EVAs. For direct comparison, EVA tasks and timelines were modeled after a similar study conducted in pressurized suits (Mark-III spacesuit, n=3 male; small xPGS spacesuit, n=3 female) at NASA’s Active Response Gravity Offload System (ARGOS) offloaded to Lunar gravity (1/6 g). The 1g HS3 data demonstrated increased metabolic rate when compared to pressurized, Lunar-offloaded suited simulated EVAs for certain tasks including the kneeling scoop (HS3: 1194±199 BTU/hr, ARGOS: 860±170 BTU/hr, p < 0.05) and 20 lb object relocation (HS3: 1651±136 BTU/hr, ARGOS: 1048±252.8 BTU/hr, p < 0.05), but it did not demonstrate any significant differences in heart rate (p > 0.05). Other simulated EVA tasks, such as a 500 m traverse (HS3: 1431±177 BTU/hr, ARGOS: 1212±294 BTU/hr, p > 0.05), showed similar workload profiles with no significant workload differences between HS3 and ARGOS. The HS3 is a useful research tool for increasing workloads in EVA research without pressurized suits, though it may overestimate workload during certain EVA tasks when used in 1g environments.

Zachary Wusk↗

Why You Might Feel Drained at the End of the Day: Workload and the Anesthesiologist

Anesthesiology is a medical specialty with one of the highest workloads and stress levels compared to all others. It is critical that anesthesiologists understand and develop effective strategies for managing their workload to avoid professional burnout. In this presentation, I will first provide an overview and definition of concepts related to workload, including task load, multitasking, concurrent task management, and interleaving tasks, and will discuss common assumptions (that are typically incorrect) relative to workload and task management. I will review common ways that anesthesiologists might unwittingly "sabotage" their attempts to manage their workload and will briefly discuss workload management techniques and strategies that they can implement to more effectively manage their tasks.

anesthesiology↗

Pilot Workload is Associated with Long Duty Days and Multiple Flight Legs

Pilot workload is a real concern throughout aviation, especially in short-haul operations due to short flights and multiple flight legs. Our goal was to examine the workload experienced by pilots during normal operations in a short-haul airline. Thirty pilots flew a roster consisting of a cycle of five days of mid-day start time duty hours with many flight legs (baseline block) followed by four days off, five early start time duty hours followed by three days off, five mid-day time starts with many legs followed by three days off and then five early start time followed by one day off. The pilots provided evaluations of workload by scoring the six subscales of NASA-TLX (i.e., Mental Demand, Performance, Physical Demand, Effort, Temporal Demand, and Frustration) on their duty days during each flight and once during rest days. The analyses included the raw TLX scores for each demand, the mean raw TLX, and the overall weighted TLX mean for duty days and rest days. We found that mental demand was significantly lower for each duty schedule and rest relative to baseline (early start 1st block p = 0.016, late duty p = 0.017, early start 2nd block p < 0.001, rest p < 0.001). Temporal demand was significantly lower than baseline on early duty 1st block (p = 0.02), early start 2nd block (p < 0.001), and rest (p < 0.001). Effort was significantly lower than baseline only during early start 1st block (p = 0.014) and early start 2nd block (p < 0.001). Frustration was significantly lower during early start 2nd block relative to baseline (p = 0. 039). Physical demand and performance were higher relative to baseline during rest days (p < 0.001). Mean raw TLX showed significantly lower workload for early start 1st block (p = 0.011) and early start 2nd block (p < 0.001). The overall weighted TLX showed significantly lower workload for early start 1st block (p = 0.004), early start 2nd block (p < 0.001) and rest (p < 0.001). We found that pilots experienced higher workload on longer duty days with multiple flight legs. Pilots experienced lower mental demand, temporal demand, and effort on short duty days even though when their duty started earlier in the day. During days off pilots experienced higher physical demand and higher performance.

short-haul↗