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Description
The International Standards Organization (ISO) documentation utilizes Fitts’ law to determine the usability of traditional input devices like mouse and touchscreens for one- or two-dimensional operations. To test the hypothesis that Fitts’ Law can be applied to hand/air gesture based computing inputs, Fitts’ multi-directional target acquisition task is applied to three gesture based input devices that utilize different technologies and two baseline devices, mouse and touchscreen. Three target distances and three target sizes were tested six times in a randomized order with a randomized order of the five input technologies. A total of 81 participants’ data were collected for the within subjects design study. Participants were instructed to perform the task as quickly and accurately as possible according to traditional Fitts’ testing procedures. Movement time, error rate, and throughput for each input technology were calculated.
Additionally, no standards exist for equating user experience with Fitts’ measures such as movement time, throughput, and error count. To test the hypothesis that a user’s experience can be predicted using Fitts’ measures of movement time, throughput and error count, an ease of use rating using a 5-point scale for each input type was collected from each participant. The calculated Mean Opinion Scores (MOS) were regressed on Fitts’ measures of movement time, throughput, and error count to understand the extent to which they can predict a user’s subjective rating.
Additionally, no standards exist for equating user experience with Fitts’ measures such as movement time, throughput, and error count. To test the hypothesis that a user’s experience can be predicted using Fitts’ measures of movement time, throughput and error count, an ease of use rating using a 5-point scale for each input type was collected from each participant. The calculated Mean Opinion Scores (MOS) were regressed on Fitts’ measures of movement time, throughput, and error count to understand the extent to which they can predict a user’s subjective rating.
ContributorsBurno, Rachael A (Author) / Wu, Bing (Thesis advisor) / Cooke, Nancy J. (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2015
Description
Traditional usability methods in Human-Computer Interaction (HCI) have been extensively used to understand the usability of products. Measurements of user experience (UX) in traditional HCI studies mostly rely on task performance and observable user interactions with the product or services, such as usability tests, contextual inquiry, and subjective self-report data, including questionnaires, interviews, and usability tests. However, these studies fail to directly reflect a user’s psychological involvement and further fail to explain the cognitive processing and the related emotional arousal. Thus, capturing how users think and feel when they are using a product remains a vital challenge of user experience evaluation studies. Conversely, recent research has revealed that sensor-based affect detection technologies, such as eye tracking, electroencephalography (EEG), galvanic skin response (GSR), and facial expression analysis, effectively capture affective states and physiological responses. These methods are efficient indicators of cognitive involvement and emotional arousal and constitute effective strategies for a comprehensive measurement of UX. The literature review shows that the impacts of sensor-based affect detection systems to the UX can be categorized in two groups: (1) confirmatory to validate the results obtained from the traditional usability methods in UX evaluations; and (2) complementary to enhance the findings or provide more precise and valid evidence. Both provided comprehensive findings to uncover the issues related to mental and physiological pathways to enhance the design of product and services. Therefore, this dissertation claims that it can be efficient to integrate sensor-based affect detection technologies to solve the current gaps or weaknesses of traditional usability methods. The dissertation revealed that the multi-sensor-based UX evaluation approach through biometrics tools and software corroborated user experience identified by traditional UX methods during an online purchasing task. The use these systems enhanced the findings and provided more precise and valid evidence to predict the consumer purchasing preferences. Thus, their impact was “complementary” on overall UX evaluation. The dissertation also provided information of the unique contributions of each tool and recommended some ways user experience researchers can combine both sensor-based and traditional UX approaches to explain consumer purchasing preferences.
ContributorsKula, Irfan (Author) / Atkinson, Robert K (Thesis advisor) / Roscoe, Rod D. (Thesis advisor) / Branaghan, Russell J (Committee member) / Arizona State University (Publisher)
Created2018
Description
Decades of research in cyberpsychology and human-computer interaction has pointed to a strong distinction between the online and offline worlds, suggesting that attitudes and behaviors in one domain do not necessarily generalize to the other. However, as humans spend increasing amounts of time in the digital world, psychological understandings of safety may begin to influence human perceptions of threat while online. This dissertation therefore examines whether perceived threat generalizes between domains across archival, correlational, and experimental research methods. Four studies offer insight into the relationship between objective indicators of physical and online safety on the levels of nation and state; the relationship between perceptions of these forms of safety on the individual level; and whether experimental manipulations of one form of threat influence perceptions of threat in the opposite domain. In addition, this work explores the impact of threat perception-related personal and situational factors, as well as the impact of threat type (i.e., self-protection, resource), on this hypothesized relationship.
Collectively, these studies evince a positive relationship between physical and online safety in macro-level actuality and individual-level perception. Among individuals, objective indicators of community safety—as measured by zip code crime data—were a positive reflection of perceptions of physical safety; these perceptions, in turn, mapped onto perceived online safety. The generalization between perceived physical threat and online threat was stronger after being exposed to self-protection threat manipulations, possibly underscoring the more dire nature of threats to bodily safety than those to valuable resources. Most notably, experimental findings suggest that it is not the physical that informs the digital, but rather the opposite: Online threats blur more readily into physical domains, possibly speaking to the concern that dangers specific to the digital world will bleed into the physical one. This generalization of threat may function as a strategy to prepare oneself for future dangers wherever they might appear; and indeed, perceived threat in either world positively influenced desires to act on recommended safety practices. Taken together, this research suggests that in the realm of threat perception, the boundaries between physical and digital are less rigid than may have been previously believed.
Collectively, these studies evince a positive relationship between physical and online safety in macro-level actuality and individual-level perception. Among individuals, objective indicators of community safety—as measured by zip code crime data—were a positive reflection of perceptions of physical safety; these perceptions, in turn, mapped onto perceived online safety. The generalization between perceived physical threat and online threat was stronger after being exposed to self-protection threat manipulations, possibly underscoring the more dire nature of threats to bodily safety than those to valuable resources. Most notably, experimental findings suggest that it is not the physical that informs the digital, but rather the opposite: Online threats blur more readily into physical domains, possibly speaking to the concern that dangers specific to the digital world will bleed into the physical one. This generalization of threat may function as a strategy to prepare oneself for future dangers wherever they might appear; and indeed, perceived threat in either world positively influenced desires to act on recommended safety practices. Taken together, this research suggests that in the realm of threat perception, the boundaries between physical and digital are less rigid than may have been previously believed.
ContributorsBodford, Jessica E (Author) / Kwan, Virginia S. Y. (Thesis advisor) / Adame, Bradley (Committee member) / Kenrick, Douglas T. (Committee member) / Shakarian, Paulo (Committee member) / Arizona State University (Publisher)
Created2017
Description
Affect signals what humans care about and is involved in rational decision-making and action selection. Many technologies may be improved by the capability to recognize human affect and to respond adaptively by appropriately modifying their operation. This capability, named affect-driven self-adaptation, benefits systems as diverse as learning environments, healthcare applications, and video games, and indeed has the potential to improve systems that interact intimately with users across all sectors of society. The main challenge is that existing approaches to advancing affect-driven self-adaptive systems typically limit their applicability by supporting the creation of one-of-a-kind systems with hard-wired affect recognition and self-adaptation capabilities, which are brittle, costly to change, and difficult to reuse. A solution to this limitation is to leverage the development of affect-driven self-adaptive systems with a manufacturing vision.
This dissertation demonstrates how using a software product line paradigm can jumpstart the development of affect-driven self-adaptive systems with that manufacturing vision. Applying a software product line approach to the affect-driven self-adaptive domain provides a comprehensive, flexible and reusable infrastructure of components with mechanisms to monitor a user’s affect and his/her contextual interaction with a system, to detect opportunities for improvements, to select a course of action, and to effect changes. It also provides a domain-specific architecture and well-documented process guidelines, which facilitate an understanding of the organization of affect-driven self-adaptive systems and their implementation by systematically customizing the infrastructure to effectively address the particular requirements of specific systems.
The software product line approach is evaluated by applying it in the development of learning environments and video games that demonstrate the significant potential of the solution, across diverse development scenarios and applications.
The key contributions of this work include extending self-adaptive system modeling, implementing a reusable infrastructure, and leveraging the use of patterns to exploit the commonalities between systems in the affect-driven self-adaptation domain.
This dissertation demonstrates how using a software product line paradigm can jumpstart the development of affect-driven self-adaptive systems with that manufacturing vision. Applying a software product line approach to the affect-driven self-adaptive domain provides a comprehensive, flexible and reusable infrastructure of components with mechanisms to monitor a user’s affect and his/her contextual interaction with a system, to detect opportunities for improvements, to select a course of action, and to effect changes. It also provides a domain-specific architecture and well-documented process guidelines, which facilitate an understanding of the organization of affect-driven self-adaptive systems and their implementation by systematically customizing the infrastructure to effectively address the particular requirements of specific systems.
The software product line approach is evaluated by applying it in the development of learning environments and video games that demonstrate the significant potential of the solution, across diverse development scenarios and applications.
The key contributions of this work include extending self-adaptive system modeling, implementing a reusable infrastructure, and leveraging the use of patterns to exploit the commonalities between systems in the affect-driven self-adaptation domain.
ContributorsGonzalez-Sanchez, Javier (Author) / Burleson, Winslow (Thesis advisor) / Collofello, James (Thesis advisor) / Garlan, David (Committee member) / Sarjoughian, Hessam S. (Committee member) / Atkinson, Robert (Committee member) / Arizona State University (Publisher)
Created2016
Description
ABSTRACT
The present studies investigated the separate effects of two types of visual feedback delay – increased latency and decreased updating rate – on performance – both actual (e.g. response time) and subjective (i.e. rating of perceived input device performance) – in 2-dimensional pointing tasks using a mouse as an input device. The first sub-study examined the effects of increased latency on performance using two separate experiments. In the first experiment the effects of constant latency on performance were tested, wherein participants completed blocks of trials with a constant level of latency. Additionally, after each block, participants rated their subjective experience of the input device performance at each level of latency. The second experiment examined the effects of variable latency on performance, where latency was randomized within blocks of trials.
The second sub-study investigated the effects of decreased updating rates on performance in the same manner as the first study, wherein experiment one tested the effect of constant updating rate on performance as well as subjective rating, and experiment two tested the effect of variable updating rate on performance. The findings suggest that latency is negative correlated with actual performance as well as subjective ratings of performance, and updating rate is positively correlated with actual performance as well as subjective ratings of performance.
The present studies investigated the separate effects of two types of visual feedback delay – increased latency and decreased updating rate – on performance – both actual (e.g. response time) and subjective (i.e. rating of perceived input device performance) – in 2-dimensional pointing tasks using a mouse as an input device. The first sub-study examined the effects of increased latency on performance using two separate experiments. In the first experiment the effects of constant latency on performance were tested, wherein participants completed blocks of trials with a constant level of latency. Additionally, after each block, participants rated their subjective experience of the input device performance at each level of latency. The second experiment examined the effects of variable latency on performance, where latency was randomized within blocks of trials.
The second sub-study investigated the effects of decreased updating rates on performance in the same manner as the first study, wherein experiment one tested the effect of constant updating rate on performance as well as subjective rating, and experiment two tested the effect of variable updating rate on performance. The findings suggest that latency is negative correlated with actual performance as well as subjective ratings of performance, and updating rate is positively correlated with actual performance as well as subjective ratings of performance.
ContributorsBrady, Kyle J (Author) / Wu, Bing (Thesis advisor) / Hout, Michael C (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2015
Description
As technology increases, so does the concern that the humanlike virtual characters and android robots being created today will fall into the uncanny valley. The current study aims to determine whether uncanny feelings from modern virtual characters and robots can be significantly affected by the mere exposure effect. Previous research shows that mere exposure can increase positive feelings toward novel stimuli (Zajonc, 1968). It is predicted that the repeated exposure to virtual characters and robots can cause a significant decrease in uncanny feelings. The current study aimed to show that modern virtual characters and robots possessing uncanny traits will be rated significantly less uncanny after being viewed multiple times.
ContributorsCorral, Christopher (Author) / Song, Hyunjin (Thesis advisor) / Wu, Bing (Committee member) / Kuzel, Michael (Committee member) / Arizona State University (Publisher)
Created2014