Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnólogico de Cd. Juárez, Cd. Juárez 32500, Chih., Mexico.
Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnólogico de Cd. Cuauhtémoc, Cd. Cuauhtémoc 31500, Chih., Mexico.
Int J Environ Res Public Health. 2023 Jan 9;20(2):1184. doi: 10.3390/ijerph20021184.
In the manufacturing environments of today, human-machine systems are constituted with complex and advanced technology, which demands workers' considerable mental workload. This work aims to design and evaluate a Graphical User Interface developed to induce mental workload based on Dual N-Back tasks for further analysis of human performance. This study's contribution lies in developing proper cognitive analyses of the graphical user interface, identifying human error when the Dual N-Back tasks are presented in an interface, and seeking better user-system interaction. Hierarchical task analysis and the Task Analysis Method for Error Identification were used for the cognitive analysis. Ten subjects participated voluntarily in the study, answering the NASA-TLX questionnaire at the end of the task. The NASA-TLX results determined the subjective participants' mental workload proving that the subjects were induced to different levels of mental workload (Low, Medium, and High) based on the ANOVA statistical results using the mean scores obtained and cognitive analysis identified redesign opportunities for graphical user interface improvement.
在当今的制造环境中，人机系统由复杂先进的技术构成，这需要工人承担相当大的脑力工作负荷。本研究旨在设计和评估一个基于双 N 回任务的图形用户界面，以进一步分析人类绩效，从而诱导脑力工作负荷。这项研究的贡献在于对图形用户界面进行适当的认知分析，确定在界面上呈现双 N 回任务时出现的人为错误，并寻求更好的用户-系统交互。分层任务分析和错误识别任务分析方法用于认知分析。十名受试者自愿参加了这项研究，在任务结束后回答了 NASA-TLX 问卷。NASA-TLX 的结果确定了主观参与者的主观脑力工作负荷，证明根据使用获得的平均分数进行的 ANOVA 统计结果，受试者被诱导到不同水平的脑力工作负荷（低、中、高），并且认知分析确定了图形用户界面改进的重新设计机会。
