Investigating The Universality And Comprehensive Ability Of Measures To Assess The State Of Workload

Measures of workload have been developed on the basis of the various definitions, some are designed to capture the multi-dimensional aspects of a unitary resource pool (Kahneman, 1973) while others are developed on the basis of multiple resource theory (Wickens, 2002). Although many theory based workload measures exist, others have often been constructed to serve the purpose of specific experimental tasks. As a result, it is likely that not every workload measure is reliable and valid for all tasks, much less each domain. To date, no single measure, systematically tested across experimental tasks, domains, and other measures is considered a universal measure of workload. Most researchers would argue that multiple measures from various categories should be applied to a given task to comprehensively assess workload. The goal for Study 1 to establish task load manipulations for two theoretically different tasks that induce distinct levels of workload assessed by both subjective and performance measures was successful. The results of the subjective responses support standardization and validation of the tasks and demands of that task for investigating workload. After investigating the use of subjective and objective measures of workload to identify a universal and comprehensive measure or set of measures, based on Study 2, it can only be concluded that not one or a set of measures exists. Arguably, it is not to say that one will never be conceived and developed, but at this time, one does not reside in the psychometric catalog. Instead, it appears that a more suitable approach is to customize a set of workload measures based on the task. The novel approach of assessing the sensitivity and comprehensive ability of conjointly utilizing subjective, performance, and physiological workload measures for theoretically different tasks within the same domain contributes to the theory by laying the foundation for improving methodology for researching workload. The applicable contribution of this project is a stepping-stone towards developing complex profiles of workload for use in closed-loop systems, such as human-robot team iv interaction. Identifying the best combination of workload measures enables human factors practitioners, trainers, and task designers to improve methodology and evaluation of system designs, training requirements, and personnel selectio

Assessing the use of Photorealistic and Computer Simulated Landscapes to Understand the Cumulative Landscape and Visual Impacts of Onshore Wind Turbines

There has been considerable research into issues around the social acceptance and visual impact of wind farms. However, relatively little is known about the factors that contribute to the cumulative landscape and visual impacts (CLVI) of wind turbines. With the continued growth of onshore wind power in the UK, understanding the CLVI of wind power developments is increasingly important. The majority of research which has studied the landscape and visual impact of wind turbines has used static photomontages. Some researchers have suggested that computer simulations should be used for research, as well as interactive design and planning. However, little if any research has been done which objectively assesses the validity of using these simulations. This thesis set out to address these methodological and theoretical gaps in the literature. Chapters 3 and 4 present two studies that were carried out to assess physiological responses to videos of wind turbines in a real-world and computer-simulated landscape (created using Sketchup and Google Earth). The findings showed that participants’ visual patterns were similar for the photorealistic and computer-simulated landscape, however the skin conductance response (SCR) data showed that affective responses were quite different. Given the different in affective response, these studies called into question the validity of using computer simulations to represent wind turbines in the landscape. Chapter 5 presents a study which attempted to examine whether the differences found in studies 1 and 2 were of any practical significance. As such, it sought to examine if there were any differences in preferences based on whether people were present with a photomontage or a computer simulation. The study also sought to better understand the factors that contribute to the CLVI of wind farm extensions. Results suggest that people’s preferences are not affected by whether they are presented with photomontages or computer simulations. The results also suggest that size, number, visual match, and turbine distribution are important factors in contributing to the visual impact of wind farm extensions. Collectively, the three studies illustrate novel methods for research into the CLVI of wind turbines. The studies also provide support for the use of computer simulations in research and interactive design and planning, as well as giving some insights into the factors that affect the CLVI of wind farm extensions

Verbal lie-detection using the reality monitoring approach: an analysis of its effectiveness and moderating factors

A large body of research findings suggests that verbal cues to deception can boost deception-detection accuracy rates to levels significantly above chance. This thesis examines the effectiveness of, and influences on, one of the most popular and widely used verbal lie-detection approaches, Reality Monitoring (RM). The RM approach has advantages not only in terms of its underpinnings in memory research and theory, but also its ease with regard to practical application. The RM approach assumes that deceptive verbal accounts, because they are artificial and not based directly on actual experience, differ from truthful accounts according to a variety of criteria (truthful accounts contain more vivid, spatial, temporal and affective information, etc.). However, so far, as in many other areas of lie-detection research, research in the area of RM has lacked methodological standardisation; consequently, we know little of the potential effects of contextual and other moderating variables on RM measures. In view of this, the primary aims of the present thesis were a) to assess whether, if conveyed in a standard format, the RM approach has any value overall in distinguishing between truthful and deceptive accounts, and b) if it does, to investigate the circumstances under which it might give optimal results; i.e. to assess some of the main factors which may moderate its efficacy in this respect. To these ends, six experimental studies were conducted which looked at truthful and deceptive accounts (generated by participants in the laboratory using video and autobiographical sources) and considered the effects of a number of different moderators; these included, first and second-language effects, modality (i.e. written vs. spoken discourse), absence/presence of others, demand characteristics effects, scoring systems (rating scales vs. raw frequencies) and standardisation for account length. Overall, results indicated that in most studies there was evidence that total RM scores, as determined by the procedures applied here, successfully discriminated between truthful and deceptive accounts. However, results varied when RM criteria were considered individually, and when the influence of various moderators was assessed. For example, frequency measures of spatial and temporal information were found to be two of the most consistently effective diagnostic RM criteria. However, overall, RM was a more effective diagnostic tool before accounts were standardised for length; indeed, total RM scores failed to distinguish between truthful and deceptive accounts after accounts had been standardised for length. Also, the presence of others and modality (written or spoken) were two key moderator variables whose impact on total RM scores varied depending on whether or not the accounts were standardised for length. A number of other related variables were also considered; for example, truthful accounts were longer than deceptive accounts in both duration and length and the number of words produced per second was significantly greater for truthful accounts. Implications for research and practise are discussed; though perhaps most important in this respect was the finding that, despite the overall success of RM in discriminating truthful from deceptive accounts, RM criteria were not generally discriminating after standardisation for word-count or length. Moreover, a number of the moderators affected RM scores regardless of whether they were derived from truthful or deceptive accounts. This suggests that we may still be a long way from developing a method (such as the use of normative criteria) that could be used in the field to classify individual cases. Nevertheless, in the meantime, at the very least, the present results suggest that when judging the veracity of accounts using RM criteria, the scoring and other moderating variables identified in this thesis should be investigated systematically, and measured and applied consistently, if researchers wish to compare and replicate findings within and across studies

Analysis Of Multiple Physiological Sensor Data

Physiological measures offer many benefits to psychological research including objective, non-intrusive assessment of affective and cognitive states. However, this utility is limited by analysis techniques available for testing data recorded by multiple physiological sensors. The present paper presents one set of data that was attained from a repeated measures design with a nominal independent variable for analysis. Specifically, the International Affective Picture System (IAPS; Lang, Bradley, & Cuthbert, 2008), a series of images known to convey seven different emotions, was presented to participants while measures of their neurological activity (Electroencephalogram; EEG), heart rate (Electrocardiogram; ECG), skin conductance (Galvanic Skin Respond; GSR), and pupillary response were taken. Subsequently, a discussion of statistics available for analyzing responses attained from the various sensors is presented. Such statistics include correlation, ANOVA, MANOVA, regression, and discriminant function analysis. The details on design limitations are addressed and recommendations are given for employing each statistical option. © 2011 Springer-Verlag