Cognitive Analyses for Interface Design Using Dual N-Back Tasks for Mental Workload (MWL) Evaluation

Nancy Ivette Arana- De las Casas (), Jorge De la Riva-Rodríguez, Aide Aracely Maldonado-Macías () and David Sáenz-Zamarrón
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Nancy Ivette Arana- De las Casas: Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnólogico de Cd. Juárez, Cd. Juárez 32500, Chih., Mexico
Jorge De la Riva-Rodríguez: Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnólogico de Cd. Juárez, Cd. Juárez 32500, Chih., Mexico
Aide Aracely Maldonado-Macías: Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnólogico de Cd. Juárez, Cd. Juárez 32500, Chih., Mexico
David Sáenz-Zamarrón: Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnólogico de Cd. Cuauhtémoc, Cd. Cuauhtémoc 31500, Chih., Mexico

IJERPH, 2023, vol. 20, issue 2, 1-20

Abstract: 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.

Keywords: mental workload (MWL); NASA-TLX; hierarchical task analysis (HTA); task analysis for error identification (TAFEI) (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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