Date of Degree
Dissertation - Open Access
Industrial and Systems Engineering
Doctor of Philosophy
James Worth Bagley College of Engineering
Department of Industrial and Systems Engineering
This research evaluated mental schema accuracy, user experience, and training methods of computer based tasks using educational software. Aims were to investigate the impact of mental schemas on individuals’ usability of technology and analyze the impact of training and user experience in terms of mental schemas and performance. Study one investigated schema accuracy as a predictor of perceived usability and mental workload; by analyzing the accuracy of users’ mental schema through task correctness. Task was found to be a significant predictor of the measures of usability, along with various demographic variables. When considering the effect of tasks, schema accuracy was a significant predictor of perceived usability and mental workload for task two (online quiz). Perceived usability showed lower values indicating higher perceptions of usability for task two and mental workload had lower values indicating reduced mental workload for task two. Significant, positive correlations were found between perceived usability and mental workload. Findings show schema accuracy as a preliminary measure of users’ subjective usability of non-problem solving tasks, based on the type of task tested and demographic data of students. Study two examined experience level (experienced and un-experienced) effects mental schema accuracy, robustness, completion time, and errors using three computer-based tasks. Experienced participants showed lower values for number of errors and robustness than un-experienced users. Significant, positive correlations were found between schema accuracy and completion time, and errors and completion time. The findings support the use of experience to analyze the impact of mental schemas and performance measures. Study three explored the change in training methods (no-training, paper, or video) on user changes in mental schema accuracy, robustness, completion times and errors. Training improved robustness, specifically paper-based training. Performance results showed that students who spent small periods of time using the software more times a week had made fewer errors and had more robust schemas. Demographic experience categories found that participants who spent more time using the software had fewer errors. Significant, positive correlations were found between schema accuracy and robustness. These results show that training improves mental schema robustness and reduces the number of errors while completing computer based tasks.
Nash, Kylie, "Mental Schema Accuracy: Investigating the Impact of Schemas on Human Performance and Technology Usability" (2012). Theses and Dissertations MSU. 3064.