Prediction of Human Performance Time to Find Objects on Multi-display Monitors using ACT-R Cognitive ArchitecturePrediction of Human Performance Time to Find Objects on Multi-display Monitors using ACT-R Cognitive Architecture
- Other Titles
- Prediction of Human Performance Time to Find Objects on Multi-display Monitors using ACT-R Cognitive Architecture
- Authors
- 오형석; 명노해; 김상협; 장은혜; 박병준
- Issue Date
- 2013
- Publisher
- 대한인간공학회
- Keywords
- ACT-R; Cognitive architecture; Model-based evaluation; Multi-display monitors
- Citation
- 대한인간공학회지, v.32, no.2, pp.159 - 165
- Indexed
- KCI
- Journal Title
- 대한인간공학회지
- Volume
- 32
- Number
- 2
- Start Page
- 159
- End Page
- 165
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/105021
- DOI
- 10.5143/JESK.2013.32.2.159
- ISSN
- 1229-1684
- Abstract
- Objective: The aim of this study was to predict human performance time in finding objects on multi-display monitors using ACT-R cognitive architecture. Background: Display monitors are one of the representative interfaces for interaction between people and the system. Nowadays, the use of multi-display monitors is increasing so that it is necessary to research about the interaction between users and the system on multi-display monitors. Method: A cognitive model using ACT-R cognitive architecture was developed for the model-based evaluation on multi-display monitors. To develop the cognitive model, first,an experiment was performed to extract the latency about the where system of ACT-R. Then, a menu selection experiment was performed to develop a human performance model to find objects on multi-display monitors. The validation of the cognitive model was also carried out between the developed ACT-R model and empirical data. Results: As a result, no significant difference on performance time was found between the model and empirical data. Conclusion: The ACT-R cognitive architecture could be extended to model human behavior in the search of objects on multi-display monitors..
Application: This model can help predicting performance time for the model-based usability evaluation in the area of multi-display work environments.
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