Browsing by Subject "Cognitive load"
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Item Open Access Analyzing occupants' control over lighting systems in office settings using immersive virtual environments(Elsevier BV, 2021-06) Mahmoudzadeh, Parisa; Afacan, Yasemin; Adi, Muhamad NadimResearch has identified occupant behavior as one of the key contributors to building energy performance gap. Thus, this study systematically analyzed the impact of having personal control over lighting system on occupants' lighting choices, lighting satisfaction, and task performance in a virtual office setting. For this purpose, 30 participants took part in a 3-phased experiment with immersive virtual environments (IVEs). Each phase of the experiment offered a different degree of control over the lighting. Personality traits were also studied in relation to lighting choices. Finally, a technology acceptance model (TAM) was employed to further investigate the participants’ attitude towards the virtual reality (VR) technology. The findings of this study showed that using an interactive lighting system, which was as satisfactory compared to a conventional lighting system, encouraged the participants to use more natural light. The interactive lighting system imposed the same amount of cognitive load on the participants for performing a reading task as a conventional lighting system, which was significantly lower than their cognitive load scores for performing the task with automated lighting system. Personality analyses demonstrated that the participants with a high score on openness had a wide range of lighting choices either with conventional or with interactive lighting. This study's results differed from the previous studies by highlighting that the participants considered VR as a better fit to an enjoyable experience rather than a useful tool for performing serious tasks.Item Open Access Analyzing occupants’ control over lighting systems in office settings using virtual environments(Bilkent University, 2020-12) Mahmoudzadeh, ParisaThis study systematically analyzed the impact of having personal control over lighting system on occupants’ lighting choices, lighting satisfaction, and task performance in a virtual office setting. For this purpose, 30 participants took part in a 3-phased experiment with immersive virtual environments (IVEs). Each phase of the experiment offered a different degree of control over the lighting. Personality traits were also studied in relation to lighting choices. Finally, a technology acceptance model (TAM) was employed to further investigate the participants’ attitude towards the virtual reality (VR) technology. The findings of this study showed that using an interactive lighting system, which was as satisfactory compared to a conventional lighting system, encouraged the participants to use more natural light. The interactive lighting system imposed the same amount of cognitive load on the participants for performing a reading task as a conventional lighting system, which was significantly lower than their cognitive load scores for performing the task with automated lighting system. Personality analyses demonstrated that the participants with a high score on openness had a wide range of lighting choices either with conventional or with interactive lighting. This study’s results differed from the previous studies by highlighting that the participants considered VR as a better fit to an enjoyable experience rather than as a useful tool for performing serious tasks.Item Open Access Investigation of how task related programs affect activation of frontoparietal regions(Bilkent University, 2023-01) Çiftçi, İpekWe prepare breakfast, take a shower, do grocery shopping. While completing these daily goals we don’t individually execute many components. For instance, while preparing instant coffee we sequentially execute subtask such as ’take the coffee, boil water, put coffee and water to a mug, take a spoon, mix it with spoon’ under the goal of preparing the coffee but we don’t individually execute them. We execute this whole temporally extended task as one entity which is called ’preparing instant coffee’ in this example. We execute a temporally extended, goal-directed behavior as one entity. The construction of this extended behavior in cognition is hierarchical since it consists of subtasks that complete the subgoals in different levels. For example, the step ’put coffee and water to a mug’ completes the subgoal of putting necessary ingredients together. Mixing them completes the actual goal. In terms of goal completion, former one is in a lower level than latter one. Execution of extended behavior that subsumes the entire task occurs via programs. Programs are related to the entire task. These programs are constructed in the beginning of episode. A program of a longer task requires larger programs than same but shorter task. Executing a longer task as one entity is more demanding than a shorter task. So, the program load of the longer task higher than the shorter one. it has been shown that the reaction time of the first item in a longer task is greater than the same but a shorter task [1]. A set of fronto-parietal regions (also known as Multiple Demands (MD) regions) activates in response to goal-directed tasks that require cognitive control and attention. Activation in MD regions higher for more demanding tasks. Demanding task here can be the tasks that have more working memory load or requires more cognitive control demands. In other words, a higher cognitive load is associated with higher activity in MD regions. Can it be a different cognitive load processing differently than the defined above? If the program loads differently than the typical cognitive load defined in the literature, the activity pattern in MD regions should be different than the typical effect of cognitive load in MD regions. In this study, we investigated this issue. In the experiment, participants executed 3-back task in 2 conditions. One condition had high working memory load (high cognitive control demands) and high program load. The other condition had low working memory load (low cognitive control demands) and low program load. Results showed that activity in low working memory load conditions in MD regions was higher than the activity in high working memory load condition. This indicates that the program load has different construction from working memory load because, it reflects different pattern of activity in MD regions.