• IE interfaces
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• v.25 no.2
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• pp.187-195
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• 2012

The driver model based on the ACT-R cognitive architecture was developed in order to predict the performance and cognitive workload of a driver operating HVI devices. In the 10 HVI tasks, the predicted performance time and cognitive workload by the ACT-R driver model was well matched and highly correlated with the mean of performance times and subjective workload ratings from 15 participants, respectively. It is strongly proposed that the ACT-R driver model in this study can be applied to evaluate the usability of a new HVI design with less cost in the early stage of system development.

• Journal of the Ergonomics Society of Korea
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• v.32 no.2
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• pp.159-165
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• 2013

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.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.43-49
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• 2015

The aim of this study was to model unusual association with declarative knowledge by positive affect using ACT-R cognitive architecture. Existing research related with cognitive modeling tends to pay a lot of attention to strong and negative cognitive moderator. Mild positive affect, however, has far-reaching effects on problem solving and decision making. Typically, subjects with positive affect were more likely to respond to unusual associates in a word association task than subjects with neutral affect. In this study, a cognitive model using ACT-R cognitive architecture was developed to show the effect of positive affect on the cognitive organization related with memory. First, we organized the memory structure of stimulus word 'palm' based on published results in a word association task. Then, we decreased an ACT-R parameter that reflects the amount of weighting given to the dissimilarity between the stimulus word and the associate word to represent reorganized memory structure of the model by positive affect. As a result, no significant associate probability difference between model prediction and existing empirical data was found. The ACT-R cognitive architecture could be used to model the effect of positive affect on the unusual association by decreasing (manipulating) the weight of the dissimilarity. This study is useful in conducting model-based evaluation of the effects of positive affect in complex tasks involving memory, such as creative problem solving.

• Journal of the Ergonomics Society of Korea
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• v.29 no.6
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• pp.907-914
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• 2010

Cognitive model, that is cognitive architecture, is the model expressed with computer program to show the process how human solve a certain problem and it is continuously under investigation through various fields of study such as cognitive engineering, computer engineering, and cognitive psychology. In addition, the much extensive applicability of cognitive model usually helps it to be used for quantitative prediction of human Behavior or Natural programming of human performance in many HCI areas including User Interface Usability, artificial intelligence, natural programming language and also Robot engineering. Meanwhile, when a system designed, an usability test about conceptual design of interface is needed and in this case, analysis evaluation using cognitive model like GOMS or ACT-R is much more effective than empirical evaluation which naturally needs products and subjects. In particular, if we consider the recent trend of very short-end term between a previous technology development and the next new one, it would take time and much efforts to choose subjects and train them in order to conduct usability test which is repeatedly followed in the process of a system development and this finally would bring delays of development of a new system. In this study, we predicted quantitatively the human behavior processes which contains cognitive processes for menu selection in touch screen interface through ACT-R, one of the common method of usability test. Throughout the study, it was shown that the result using cognitive model was equal with the result using existing empirical evaluation. And it is expected that cognitive model has a possibility not only to be used as an effective methodology for evaluation of HCI products or system but also to contribute the activation of HCI cognitive modeling in Korea.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.291-298
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• 2012

Objective: The aim of this study is to predict Korean text entry on touchscreens using ACT-R cognitive architecture. Background: Touchscreen application in devices such as satellite navigation devices, PDAs, mobile phones, etc. has been increasing, and the market size is expanding. Accordingly, there is an increasing interest to develop and evaluate the interface to enhance the user experience and increase satisfaction in the touchscreen environment. Method: In this study, Korean text entry performance in the touchscreen environment was analyzed using ACT-R. The ACT-R model considering the characteristics of the Korean language which is composed of vowels and consonants was established. Further, this study analyzed if the prediction of Korean text entry is possible through the ACT-R cognitive model. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed model can predict the accurate physical movement time as well as cognitive processing time. Application: This study is useful in conducting model-based evaluation on the text entry interface of the touchscreen and enabled quantitative and effective evaluation on the diverse types of Korean text input interfaces through the cognitive models.

• Journal of the Ergonomics Society of Korea
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• v.35 no.4
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• pp.225-235
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• 2016

Objective: The aim of this study is to model all levels of situation awareness (SA), which would be able to predict situation awareness quantitatively. Background: When measuring situation awareness, directly measuring SA methods such as SAGAT and SART have been utilized. Several approaches (cognitive modeling approaches) were introduced to model SA but level 3 SA was not completed. For real-life situation, however, it is necessary to detect the problematic level of SA rather than overall SA. Therefore, we proposed a new model of all levels of SA in this study. Method: In order to model all levels of SA, this study chose factors in ACT-R architecture through literature review. ATC (Air Traffic Control)-related simulation task was video-taped to analyze human behaviors in order to model all levels of SA including level 3. Results: As a result, regression analyses show that cognitive activities (neural activations) represented for all levels of SA were highly correlated with SAGAT. Conclusion: In conclusion, neural activations in ACT-R could be proved to be effective to model all levels of SA. Application: Our SA model could be used to predict all levels of SA quantitatively without directly measuring the SA of operators.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.6
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• pp.377-385
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• 2016

The previous Adaptive Control of Thought-Rational (ACT-R) cognitive architecture model has a limitation in that it cannot accurately predict human visual search strategy, because time effect, one of important human cognitive features, is not considered. Thus, the present study proposes ACT-R cognitive modeling that contains the impact of time using a revised utility system in the ACT-R model. Then, the validation of the model is performed by comparing results of the model with eye-tracking experimental data and SEEV-T (SEEV-Time; SEEV model which considers time effect) model in "Where's Wally" game. The results demonstrate that the model data fit fairly well with the eye-tracking data ($R^2=0.91$) and SEEV-T model ($R^2=0.93$). Therefore, the modeling method which considers time effect using a revised utility system should be used in predicting the human visual search paradigm when the available time is limited.

• Journal of the Ergonomics Society of Korea
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• v.31 no.6
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• pp.705-713
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• 2012

Objective: The aim of this study is to predict human visual target search using ACT-R cognitive architecture in real scene images. Background: Human uses both the method of bottom-up and top-down process at the same time using characteristics of image itself and knowledge about images. Modeling of human visual search also needs to include both processes. Method: In this study, visual target object search performance in real scene images was analyzed comparing experimental data and result of ACT-R model. 10 students participated in this experiment and the model was simulated ten times. This experiment was conducted in two conditions, indoor images and outdoor images. The ACT-R model considering the first saccade region through calculating the saliency map and spatial layout was established. Proposed model in this study used the guide of visual search and adopted visual search strategies according to the guide. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed ACT-R model is able to predict the human visual search process in real scene images using salience map and spatial layout. Application: This study is useful in conducting model-based evaluation in visual search, particularly in real images. Also, this study is able to adopt in diverse image processing program such as helper of the visually impaired.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.158-167
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• 2018

The role of S/W in weapon systems has been developed with various functions and complex structures. As the weapon system S/W is directly related to quick and accurate decision making of users, more accurate evaluation is required during the training. However, situation awareness of weapon system S/W users has only been assessed qualitatively such as by simple test or qualitative judgement. Therefore, this study suggests the 'Cognition Ratio' concept which represents the quantitative of users by combining ACT-R cognitive architecture to SA (Situation Awareness) and Fitts' Law based on the theory of cognitive engineering. The cognition ratio is a ratio of cognition among the whole cognitive behavior process including perception and psychomotor. Moreover, this study provides a systematic assessment process of situation awareness that will be applicable to various weapon system S/W for effective assessment.