Browsing by Subject "Task analysis"

Now showing 1 - 7 of 7
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    Assembly line balancing utilizing fatigue constraints and task grouping
    (Texas Tech University, 1988-05) Rentschler, David
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    Assembly line balancing utilizing fatigue constraints and task grouping
    (Texas Tech University, 1988-05) Rentschler, David
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    Diversity, conflict, and systems leadership in project groups: a longitudinal study
    (Texas Tech University, 2002-12) Agar, Feride Pinar
    The changing demography of the workforce has made group composition the most actively researched determinant of group effectiveness. The present study examined the effects of a major aspect of group composition, group diversity, on intragroup conflict and group performance. The majority of research on group diversity has considered diversity to be stable and objective. This study proposed a model of diversity that emphasized its perceptual and transient nature. It was postulated that different types of diversity would be salient at different times in a group's life and that these different types of diversity would trigger different group processes. Further, the model proposed in this study incorporated systems leadership, which enabled diverse groups to avoid the unfavorable effects of diversity while reaping its benefits. Seventy-six student project teams in the capstone Strategic Management class offered in the college of business administration of a large southwestern state university participated in a longitudinal survey study to test specific hypotheses derived from the proposed model. The results indicated that diversity had a transient nature and that the salience of different forms of diversity changed throughout groups' development. Also, it was found that different forms of diversity led to different types of conflict, which in turn influenced group performance. Finally, it was found that systems leadership moderated between diversity and conflict.
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    Effects of task content, task type, and leader gender on perceptions of gender differences in leadership effectiveness
    (Texas Tech University, 1998-05) Sutton, Janet L.
    In this experiment, leaders of intellective tasks were required to bring the group to a decision as to which of three alternatives was the correct alternative. Leaders of judgmental tasks were required to bring the group to a consensus as to which was the best alternative. The paradigm allowed leaders to clearly exhibit differential behaviors depending on task type. This experiment focused on the effects of congruency between task content and leader gender on perceptions of gender differences in leadership effectiveness. Based on past research on the interaction of leader gender with task content, it was hypothesized that leaders should receive higher leadership effectiveness ratings when there was congruency between task content and leader gender. Furthermore, because judgmental tasks require consideration of opinions and values of group members (i.e., a stereotypically feminine characteristic), it was hypothesized that female leaders should be perceived as more effective when task type was judgmental than when task type was intellective. Building on Hypotheses 1 and 2, Hypothesis 3 predicted that when task type was judgmental, congruency between task content and leader gender should result in higher effectiveness evaluations for female leaders than male leaders. Hypothesis 3 also predicted that incongruency between task content and leader gender should result in equal evaluations to that of male leaders. As Figure 1 shows, the interaction of task content, task type, and leader gender was predicted to affect perceptions of gender differences in leadership effectiveness.
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    Inference of task execution times using linear regression techniques
    (Texas Tech University, 2002-12) Muniyappa, Vinay
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    Quantifying Experience and Task Performance in 3D Serious Games
    (2019-05) Desai, Kevin Parag
    Mixed reality systems allow the development of different 3D immersive games, by immersing a live captured 3D model of a person in a virtual environment and enabling interactions and collaborations among geographically distributed people. Serious gaming is one application domain for a mixed reality system in which games are developed for primary purpose of education or training rather than just entertainment. Different aspects of a serious game such as visual, interaction, immersion, etc. influence the user’s perceived experience. Task performance in a serious game reflects how efficiently and accurately users carry out the assigned tasks. For instance, in a serious game for a virtual STEM (Science, Technology, Engineering and Mathematics) experiment, the user’s task performance can be characterized by how accurately the user follows the given procedure and how efficiently the goals are accomplished. User’s task performance in such serious games is typically influenced by his/her experience of the provided virtual environment for carrying out the assigned task. In this dissertation, we focus on the problem of quantifying experience and task performance in 3D serious games by addressing the following questions - (i) Can we, and if so how do we, quantify the user’s experience and potentially improve it in different serious games? (ii) Can we, and if so how do we, map the user’s task performance in a real world scenario to the corresponding virtual world serious game? Also, is there a correlation that exists between the user’s task performance and experience in serious games? Since serious games is a wide domain covering countless applications, it would be difficult if not impossible to generalize and answer the above questions for all of them. Hence, we focus on solving the research questions for 3 different domains of serious games developed using a mixed reality framework, namely Exergames, Multi-Modal Collaborative Virtual Laboratory (MMCVL) and Penalty training game. In order to quantify the visual experience, a learning-based objective measure is developed that emulates human perception of the 3D human open mesh quality. For a mixed reality application, a large amount of 3D data is generated and transmitted across the network, even for a single RGB-D Kinect camera. To reduce this data, based on the available bandwidth, a visual quality based vertex selection technique and a sweep-line based meshing technique is used. The user experience of a mixed reality game is improved, if accurate interactions are provided for a wide range of motion. Multiple cameras are needed to provide a complete representation of the person from all directions. A fast skeleton-based re-calibration method is developed that performs continuous and simultaneous extrinsic calibration of multiple Kinect cameras. Skeletal poses from multiple Kinect cameras are combined in order to generate a high quality combined 3D point cloud model. User studies are performed to evaluate the effect of 3 aspects - visual, interaction and immersion, on the overall quality of experience. For automatically assessing the task performance of a single user or a group of users in a 3D serious game, we formally express the assessment logic using an Augmented Hierarchical Task Network (A-HTN). Game authors are provided with an authoring script to help them incorporate the assessment logic in the game. Recording mechanism is used to store user’s task performance for assessment as well as for future reference. User studies are conducted on the 3 serious games domains and correlation analysis is performed to show that the user’s task performance improves if high quality of experience is provided in 3D serious games.
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    The multiple resource constrained scheduling problem
    (Texas Tech University, 1998-05) Montes, Elliot J.
    In this dissertation, algorithm methods that provide solutions to the Mutiple Resource Constrained Scheduling (MRCS) problem are presented. The MRCS problem can be considered an m machine, n job problem with batch setups subject to resource (worker) constraints with the objective of minimizing makespan, the maximum job completion time. Additionally, the machines are non-identical and parallel where job preemption is not allowed. The MRCS problem exists in systems where each job set requires processing by a specific machine and a crew of workers. Even though multiple machines exist in the system, not all machines can perform all jobs. Furthermore, before a worker(s) can be assigned to operate a machine for a particular job, the respective worker(s) must have been trained to perform that job. In addition, workers must be retrained before performing any new type of job. The goal is to schedule the jobs, workers, and machines such that the total makespan is minimized. This problem is unique because not only are workers and machines considered, but the workers have the additional job training requirements. The MRCS problem can be found in high health risk and environmental risk systems where continual operator training is mandatory before work can begin or continue. Such operations can be found in nuclear plant maintenance, defense industries, and other areas. The developed algorithm is evaluated via Monte Carlo sampling, existing decision rule comparison, and through human subjects testing.