Abstract
This study focused on older adults’ cognitive workload of mobile devices. An experiment was conducted to investigate the influence of website complexity and task complexity on users’ visual search behavior. 15 older adults needed to perform a simple shopping task and a complex shopping task on different mobile websites in this experiment. Three findings were derived. First, compared with simple tasks, participants spent more time on complex tasks and experienced heavier mental workload; Second, the color of mobile websites did affect participants’ workload on the websites with fewer links whereas it did not affect participants’ workload on the websites with more links, and 85 % of the participants preferred the mobile websites with color; Third, as the number of links on the mobile websites increased, participants spent more time in finding the target and experienced heavier mental workload.
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1 Introduction
Mobile devices were promising tools to provide many opportunities to meet the need of older adults in an aging society [1]. Older adults would like to use mobile technology (e.g. E-readers and tablets) when they found it useful, as they wanted to keep in touch with family members [2]. However, older adults had some disadvantages in effectively utilizing those technical products because of their cognitive decline. For instance, older adults experienced age-related decreases in the speed of information processing [3], and they were less able to resolve details and were less sensitive to critical environmental characteristics such as color and luminance [4]. Therefore, considering the growing number of older technical product users [5], it was instructive to take older adults’ cognitive decline into account in the website design process.
Website complexity was one of the common factors that designers needed to consider in the website design process. Besides, mobile devices were expected to perform different tasks in a more complicated environment than personal computer. Therefore, task complexity was another factor which needed to be considered in the website design process. Previous studies mostly aimed at the influence of task type and task complexity [6, 7] on users’ visual search behavior of websites on the personal computer, however, there were limited studies investigating how task complexity influenced older adults’ visual search behavior on mobile devices. In order to tailor website complexity and task complexity to older adults’ ability for the mobile surfing environment, an experiment was conducted. Results of this study presented suggestions to improve the design for older adults’ visual behavior on mobile devices websites for designers.
2 Literature Review
Previous studies had found that website complexity did affect users’ attitudes and visual search behavior [8]. However, the relationship between website complexity and user experience was still unclear. There were researchers believed that websites with lower complexity were more effective [9, 10], whereas others thought that websites with high complexity increased the richness of the information and thereby strengthened the requirement and satisfaction of users [11, 12].
The website complexity was somehow related to the visual complexity and the amount of information. Previous study had found that visual complexity of websites influenced users’ cognition and emotion in different ways (e.g. facial expression, task performance, and memory) [13]. Sicilia and Ruiz (2010) had found that participants’ information processing followed a pattern “inverted U-shape”, where workload first increased and then decreased as the amount of information increased [14].
Task complexity was related to the “increase in information load, information diversity, or rate of information change” [15]. Considering the task complexity from the perspective of devices, compared with watches, PDAs (personal digital assistant) could represent the situation with a high level of task complexity, because the PDA had 17 experiential features (e.g. address book, notepad, and mail) whereas watches only had six experiential features [16].
Age-related perceptual changes in vision such as visual acuity, color vision, and useful field of view were happened in older adults [4]. Previous studies had found that older adults’ ability to discriminate and perceive shorter wavelength light (e.g. blues and greens) decreased [17]. Fisk et al. (2009) had found that perceptual speed of older adults decreased more than younger adults as task complexity increased. And they recommended designer to avoid information overload for older learners according to their past experience of developing computer training programs for older adults [18].
3 Methodology
An experiment was conducted to investigate the influence of website complexity and task complexity on users’ visual search behavior. Participants’ performance was observed, and the self-report of cognitive workload and System Usability Scale (SUS) were collected.
3.1 Participants
A total of 15 older adults from Yuzui Citizen School in Jiangbei District of Chongqing, China were recruited as participants. Older adults who were literate and aged above 60 were eligible for this study. The age of the participants ranged from 60 to 74 years old (Mean = 65.3, SD = 5.31). In total, there were eight male participants and seven female participants.
3.2 Dependent Variables
The dependent variables of the experiment were task completion time, scores of SUS, and scores of NASA Task Load Index (NASA-TLX) [19]. Specifically, the task completion time was analyzed through video playback, which was recorded through the application - Mirroring360 (version 1.5.1.4). The SUS questionnaire was used to measure the satisfaction of the participants and usability of websites. The NASA-TLX was used to measure participants’ cognitive workload. Figure 1 showed that a participant was doing a simple shopping task on the mobile website with low complexity and the synchronous application was recording participant’s operation on the mobile devices.
A participant was doing a simple task on the low-complexity website
3.3 Independent Variables
The independent variables of the experiment were website complexity and task complexity. There were three factors in this experiment. Visual complexity (with or without color) and the number of links (fewer or more links) were two factors to measure website complexity. Simple tasks (find and match without decision making) and complex tasks (find and compare with decision making) were used to measure task complexity.
The levels of website complexity were mainly varied by page length, the number of pictures and links, and the amount of animation of websites on the personal computer [20]. Considering the screen size of mobile devices, the experiment here mainly took the number of links (fewer or more links) and the visual complexity (with or without color) as the factors to distinguish different website complexity (low and high level). Specifically, there were six pictures and links on the low-complexity website, where the product overview page was one page and could not be scrolled. And there were 24 pictures and links on the high-complexity website, where the product overview page were four pages and could be scrolled. Visual complexity (with or without color) was the other factor to distinguish different levels of website complexity. Figure 2 showed the websites with high and low visual complexity.
Two mobile websites with high (left) and low (right) visual complexity
Simple and complex tasks as Leuthold et al. (2011) did in their study [21] would be manipulated in this experiment through two scenarios, and detailed information would be presented in the next section.
3.4 Experimental Design and Task
The purposes of this study were tested through a laboratory experiment with a 2*2*2 within-subject design (i.e., 2 level of task complexity * 2 level of number of links * 2 level of visual complexity). During the experiment, participants were asked to buy a product on the mobile websites. Specifically, they needed to perform one simple task and one complex task, which represented two online shopping scenarios in real life.
In the situation of simple shopping task, participants were asked to buy a specific product on the mobile websites. This task represented a scenario in real life where users knew clearly what they needed to buy before shopping on the mobile websites. In the situation of complex tasks, participants were given a series of features of the products (e.g. price, product size, and brand) to shop online. Those limited features would ask them to make comparisons before making shopping decisions. There were multiple eligible products that matched the features on the mobile websites, which would force participants to make comparisons and considerations among different products and to find a product that matched the features.
4 Equipment and Procedures
The websites were running on an iPad with iOS 7.1 operating system. A notebook computer (MacBook Air) with OS X EI Capitan operating system and a synchronous recording application (Mirroring360, version 1.5.1.4) was used to record participants operation on the iPad in the experiment.
The experiment took each participant about 40 min. Firstly, each participant began the experiment by filling out a consent form and a general questionnaire about his/her demographic information and experience of using technology products and online shopping. Secondly, a short introduction of the experiment was conducted. Thirdly, participants started to perform the experimental tasks, and they were asked to conduct two tasks on different websites separately. Finally, a five-minute exploratory interview was conducted.
5 Results and Discussions
5.1 Descriptive Statistics
There were a total of 15 participants in this experiment (eight males, seven females). 80 % of the participants were junior high school education and 20 % were primary school education. Basically most of the participants had little online shopping experience. 20 % of the participants had two-year experience with smart phones. However, all of the participants had not experience with tablets. On average, participants spent 3.6 h (SD = 2.23) in watching TV per day.
5.2 Statistic Analysis of Performance and Cognitive Workload
Repeated ANOVA was used to analyze data. Table 1 showed the means and standard deviation of task completion time, scores of cognitive workload, and scores of SUS when participants performed different tasks on mobile websites with different levels of website complexity.
Visual complexity (with or without color) and the number of links (fewer or more links) were chosen as the factors to distinguish different levels of website complexity. Results of repeated ANOVA for testing the effects of three factors (task complexity, visual complexity, and the number of links) on task completion time, scores of cognitive workload, and scores of SUS were shown in Table 2. And the paired t-test was conducted for the purpose of fully understanding the interaction effects of three factors.
As to the task completion time, Fig. 3 showed the estimated marginal means of task completion time in different treatments. Compared with simple tasks, participants spent more time on complex tasks. As the number of links on the mobile websites increased, participants spent more time in finding the target. Specifically, under the simple task, the task completion time increased while the number of links increased and visual complexity decreased. Under the complex task, the task completion time increased while the number of links and visual complexity increased. Task completion time and the cognitive workload were kept in a similar tendency.
The marginal means of task completion time
As to the cognitive workload, Fig. 4 showed the estimated marginal means of scores of cognitive workload in different treatments. The interaction effects of task complexity and the number of links for cognitive workload were found significant. Participants experienced heavier mental workload to complete complex task than the simple task. As the number of links on the websites increased, participants experienced heavier mental workload to complete the tasks. And the influence caused by the changes of these two factors was different.
The marginal means of scores of cognitive workload
The interaction effects of visual complexity and the number of links for cognitive workload were found significant. On the websites with fewer links, from the results of paired t-test, participants experienced heavier workload on the websites without color than the websites with color (t = 2.850, p = 0.008). On the websites with more links, there was no significant difference between websites with color and websites without color. This indicated that website color did not affect participants’ visual behavior on the websites with more links.
Previous study had found that website color would affect users’ satisfaction within different cultures on a personal computer website [22]. This finding was fitted to the situation where participants performed tasks on the websites with fewer links. However, it could not work on the websites with more links. According to the load theory of attention proposed by Lavie et al. [23], a cognitive selection mechanism existed in the human mind, which would help an individual ignore irrelevant information when the individual was under environments of heavier cognitive workload [24]. For websites with more links, participants were suffering heavier workload, and they put their cognitive abilities on searching task in the experiment. Therefore there were insufficient abilities to notice irrelevant factors (the color of the website). Besides, the interview results found that 85 % of the participants preferred the websites with color (Fig. 5).
The marginal means of scores of cognitive workload
As to the scores of SUS, the interaction effects of task complexity and visual complexity for SUS were found significant. On the websites with color, compared with complex tasks, participants’ scores of SUS were higher than simple tasks (t = 2.861, p = 0.008). As shown in Fig. 6, under the simple task, scores of SUS decreased while visual complexity decreased (t = 3.107, p = 0.004).
The marginal means of scores of SUS
6 Conclusion
This study investigated older adults’ cognitive workload of mobile devices. To provide good user experience of mobile devices for older adults, an experiment was conducted to investigate the influence of website complexity and task complexity on users’ visual search behavior. Based on the results, three main findings were derived.
First, compared with simple tasks, participants spent more time on complex tasks. As the number of links on the mobile websites increased, participants spent more time in finding the target.
Second, participants experienced heavier mental workload to complete the complex task than the simple task. As the number of links on the websites increased, participants experienced heavier mental workload to complete the tasks. Besides, the influence caused by the changes of task complexity and website complexity was different.
Third, the color of mobile websites did affect participants’ workload using the websites with fewer links (six links) whereas it did not influence participants’ workload using the websites with more links (24 links). And the interview results also found that 85 % of the participants preferred the websites with color.
There were two limitations of this study. First, the sample size was small and the participants had low education level. It could not be considered as very representative for the whole group of older users. Second, websites in the prototypes were different from the real situation of mobile devices websites.
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Acknowledgment
This work was supported with funding from a National Science Foundation China grant 71401018.
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Huang, J., Zhou, J. (2016). Impact of Website Complexity and Task Complexity on Older Adult’s Cognitive Workload on Mobile Devices. In: Zhou, J., Salvendy, G. (eds) Human Aspects of IT for the Aged Population. Design for Aging. ITAP 2016. Lecture Notes in Computer Science(), vol 9754. Springer, Cham. https://doi.org/10.1007/978-3-319-39943-0_32
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