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The exact properties of the interaction between emotional drives and other psychological phenomena is still a vastly unexplored field. The purpose of this paper will be to examine further the effects of one of these emotional drives, that of fear, on task performance, and to explore some of the theoretical conceptualizations already put forth regarding this interaction.

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Stroke rehabilitation is to train the motor function of a patients limb. In this process, functional assessment is of importance, and it is primarily based on a patients task performance. The context of the rehabilitation discussed in this thesis is such that functional assessment is conducted through a computer system and the Internet. In particular, a patient performs the task at home in a haptic virtual environment, and the task performance is transmitted to the therapist over the Internet. One problem with this approach to functional assessment is that a patients mind state is little known to the therapist. This immediately leads to one question, that is, whether an elevated mind state will have some significant effect on the patients task performance? If so, this approach can result in a considerable error. The overall objective of this thesis study was to generate an answer to the aforementioned question. The study focused on a patients elevated fatigue state. The specific objectives of the study include: (i) developing a haptic virtual environment prototype system for functional assessment, (ii) developing a physiological-based inference system for fatigue state, and (iii) performing an experiment to generate knowledge regarding the fatigue effect on task performance. With a limited resource in recruiting patients in the experiment, the study conducted few experiments on patients but mostly on healthy subjects. The study has concluded: (1) the proposed haptic virtual environment system is effective for the wrist coordination task and is likely promising to other tasks, (2) the accuracy of proposed fatigue inference system achieves 89.54%, for two levels of fatigue state, which is promising, (3) the elevated fatigue state significantly affects task performance in the context of wrist coordination task, and (4) the accuracy of the individual-based inference approach is significantly higher than that of the group-based inference approach. The main contributions of the thesis are (1) generation of the new knowledge regarding the fatigue effect on task performance in the context of home-based rehabilitation, (2) provision of the new fatigue inference system with the highest accuracy in comparison with the existing approaches in literature, and (3) generation of the new knowledge regarding the difference between the individual-based inference and group-based inference approaches.

Stroke rehabilitation is to train the motor function of a patients limb. In this process, functional assessment is of importance, and it is primarily based on a patients task performance. The context of the rehabilitation discussed in this thesis is such that functional assessment is conducted through a computer system and the Internet. In particular, a patient performs the task at home in a haptic virtual environment, and the task performance is transmitted to the therapist over the Internet. One problem with this approach to functional assessment is that a patients mind state is little known to the therapist. This immediately leads to one question, that is, whether an elevated mind state will have some significant effect on the patients task performance? If so, this approach can result in a considerable error. The overall objective of this thesis study was to generate an answer to the aforementioned question. The study focused on a patients elevated fatigue state. The specific objectives of the study include: (i) developing a haptic virtual environment prototype system for functional assessment, (ii) developing a physiological-based inference system for fatigue state, and (iii) performing an experiment to generate knowledge regarding the fatigue effect on task performance. With a limited resource in recruiting patients in the experiment, the study conducted few experiments on patients but mostly on healthy subjects. The study has concluded: (1) the proposed haptic virtual environment system is effective for the wrist coordination task and is likely promising to other tasks, (2) the accuracy of proposed fatigue inference system achieves 89.54%, for two levels of fatigue state, which is promising, (3) the elevated fatigue state significantly affects task performance in the context of wrist coordination task, and (4) the accuracy of the individual-based inference approach is significantly higher than that of the group-based inference approach. The main contributions of the thesis are (1) generation of the new knowledge regarding the fatigue effect on task performance in the context of home-based rehabilitation, (2) provision of the new fatigue inference system with the highest accuracy in comparison with the existing approaches in literature, and (3) generation of the new knowledge regarding the difference between the individual-based inference and group-based inference approaches.

Auditors face strong incentives to execute tasks efficiently and meet deadlines; these conditions are both conducive to – and rewarding of – implemental mindsets. However, an implemental mindset may deprioritize careful analysis and thoughtful decision-making, leading to suboptimal performance and audit quality. Conversely, deliberative mindsets promote critical thinking and open-mindedness – and research suggests auditors in a deliberative mindset perform complex tasks more effectively than auditors in an implemental mindset. Additionally, auditors encounter frequent reminders about the consequences of audit failures. This study examines how these factors (i.e., mindsets and consequence reminders) jointly influence auditors' performance on complex tasks. I predict that consequence reminders will be helpful to auditors in an implemental mindset but counter-productive to auditors in a deliberative mindset. Consistent with theory, results from a 2x2 experiment reveal that undergraduate student participants in a deliberative mindset outperform those in an implemental mindset in an error identification task. However, I find no evidence that a consequence reminder influences performance or moderates the effect of mindsets in this task. My results contribute to the emerging literature on the benefits of deliberative mindsets and can help guide future research in this area.

The research objectives were (1) to perform a detailed review of the literature on speech recognition technology and the attentional demands of driving; (2) to develop decision tools that assist designers of in-vehicle systems; (3) to experimentally examine automatic speech recognition (ASR) design parameters, input modalities, and driver ages; and (4) to provide human factors recommendations for the use of speech recognition technology in automotive applications. Two experiments were conducted to determine the effects of ASR design parameters, input modality, and age on driving performance, system usability, and driver preference/acceptance. Eye movement behavior, steering input behavior, speed maintenance behavior, reaction time to forward scene event, task completion time, and task completion errors when driving and performing in-vehicle tasks were measured. Driver preference/acceptance subjective data were also recorded. The results showed that ASR design parameters significantly affected measures of driving performance, system usability, and driver preference/acceptance. However, from a practical viewpoint, ASR design parameters had a nominal effect on driving performance. Differences measured in driving performance brought on by changes in ASR system design parameters were small enough that alternative ASR system designs could be considered without impacting driving performance. No benefits could be claimed for ASR systems improving driving safety/performance compared to current manual-control systems. Speech recognition system design demonstrated a moderate influence on the usability of in-vehicle tasks. Criteria such as task completion times and task completion errors were shown to be different between speech-input and manual-input control methods, and under different ASR design configurations. Therefore, trade-offs between ASR system designs, and between speech-input and manual-input systems, could be evaluated in terms of usability. Finally, ASR system design had a nominal effect on driver preference/acceptance. Further research is warranted to determine if long-term use of ASR systems with less than optimal design parameters would result in significantly lower values for driver preference/acceptance compared to data collected in this research effort. Human factors recommendations for the use of ASR technology in automotive applications are included. The recommendations are based on the empirical research and the literature review on speech recognition technology and the attentional demands of driving. / Ph. D.

The perception of self-efficacy is a central cognitive construct in explaining motivation. Assigned goals are established in the literature as affecting self-efficacy, but only a few researchers investigated their effects in complex tasks. One stream of research revealed the positive effects of easy goals on performance in a complex task without regard to self-efficacy perceptions. In the present study, the focus was on the effects of assigned, easy goals on self-efficacy and personal goals in complex task performance. It was expected that easy goals would be superior to moderate or impossible goals because the complexity and uncertainty of the task distorts subjects' perceptions of goal difficulty.