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- Creators: Arizona State University
- Creators: Turaga, Pavan
Description
Although there are many forms of organization on the Web, one of the most prominent ways to organize web content and websites are tags. Tags are keywords or terms that are assigned to a specific piece of content in order to help users understand the common relationships between pieces of content. Tags can either be assigned by an algorithm, the author, or the community. These tags can also be organized into tag clouds, which are visual representations of the structure and organization contained implicitly within these tags. Importantly, little is known on how we use these different tagging structures to understand the content and structure of a given site. This project examines 2 different characteristics of tagging structures: font size and spatial orientation. In order to examine how these different characteristics might interact with individual differences in attentional control, a measure of working memory capacity (WMC) was included. The results showed that spatial relationships affect how well users understand the structure of a website. WMC was not shown to have any significant effect; neither was varying the font size. These results should better inform how tags and tag clouds are used on the Web, and also provide an estimation of what properties to include when designing and implementing a tag cloud on a website.
ContributorsBanas, Steven (Author) / Sanchez, Christopher A (Thesis advisor) / Branaghan, Russell (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2011
Description
The wide adoption and continued advancement of information and communications technologies (ICT) have made it easier than ever for individuals and groups to stay connected over long distances. These advances have greatly contributed in dramatically changing the dynamics of the modern day workplace to the point where it is now commonplace to see large, distributed multidisciplinary teams working together on a daily basis. However, in this environment, motivating, understanding, and valuing the diverse contributions of individual workers in collaborative enterprises becomes challenging. To address these issues, this thesis presents the goals, design, and implementation of Taskville, a distributed workplace game played by teams on large, public displays. Taskville uses a city building metaphor to represent the completion of individual and group tasks within an organization. Promising results from two usability studies and two longitudinal studies at a multidisciplinary school demonstrate that Taskville supports personal reflection and improves team awareness through an engaging workplace activity.
ContributorsNikkila, Shawn (Author) / Sundaram, Hari (Thesis advisor) / Byrne, Daragh (Committee member) / Davulcu, Hasan (Committee member) / Olson, Loren (Committee member) / Arizona State University (Publisher)
Created2013
Description
The Game As Life - Life As Game (GALLAG) project investigates how people might change their lives if they think of and/or experience their life as a game. The GALLAG system aims to help people reach their personal goals through the use of context-aware computing, and tailored games and applications. To accomplish this, the GALLAG system uses a combination of sensing technologies, remote audio/video feedback, mobile devices and an application programming interface (API) to empower users to create their own context-aware applications. However, the API requires programming through source code, a task that is too complicated and abstract for many users. This thesis presents GALLAG Strip, a novel approach to programming sensor-based context-aware applications that combines the Programming With Demonstration technique and a mobile device to enable users to experience their applications as they program them. GALLAG Strip lets users create sensor-based context-aware applications in an intuitive and appealing way without the need of computer programming skills; instead, they program their applications by physically demonstrating their envisioned interactions within a space using the same interface that they will later use to interact with the system, that is, using GALLAG-compatible sensors and mobile devices. GALLAG Strip was evaluated through a study with end users in a real world setting, measuring their ability to program simple and complex applications accurately and in a timely manner. The evaluation also comprises a benchmark with expert GALLAG system programmers in creating the same applications. Data and feedback collected from the study show that GALLAG Strip successfully allows users to create sensor-based context-aware applications easily and accurately without the need of prior programming skills currently required by the GALLAG system and enables them to create almost all of their envisioned applications.
ContributorsGarduno Massieu, Luis (Author) / Burleson, Winslow (Thesis advisor) / Hekler, Eric (Committee member) / Gupta, Sandeep (Committee member) / Arizona State University (Publisher)
Created2012
Design and development of an immersive virtual reality team trainer for advance cardiac life support
Description
Technology in the modern day has ensured that learning of skills and behavior may be both widely disseminated and cheaply available. An example of this is the concept of virtual reality (VR) training. Virtual Reality training ensures that learning can be provided often, in a safe simulated setting, and it may be delivered in a manner that makes it engaging while negating the need to purchase special equipment. This thesis presents a case study in the form of a time critical, team based medical scenario known as Advanced Cardiac Life Support (ACLS). A framework and methodology associated with the design of a VR trainer for ACLS is detailed. In addition, in order to potentially provide an engaging experience, the simulator was designed to incorporate immersive elements and a multimodal interface (haptic, visual, and auditory). A study was conducted to test two primary hypotheses namely: a meaningful transfer of skill is achieved from virtual reality training to real world mock codes and the presence of immersive components in virtual reality leads to an increase in the performance gained. The participant pool consisted of 54 clinicians divided into 9 teams of 6 members each. The teams were categorized into three treatment groups: immersive VR (3 teams), minimally immersive VR (3 teams), and control (3 teams). The study was conducted in 4 phases from a real world mock code pretest to assess baselines to a 30 minute VR training session culminating in a final mock code to assess the performance change from the baseline. The minimally immersive team was treated as control for the immersive components. The teams were graded, in both VR and mock code sessions, using the evaluation metric used in real world mock codes. The study revealed that the immersive VR groups saw greater performance gain from pretest to posttest than the minimally immersive and control groups in case of the VFib/VTach scenario (~20% to ~5%). Also the immersive VR groups had a greater performance gain than the minimally immersive groups from the first to the final session of VFib/VTach (29% to -13%) and PEA (27% to 15%).
ContributorsVankipuram, Akshay (Author) / Li, Baoxin (Thesis advisor) / Burleson, Winslow (Committee member) / Kahol, Kanav (Committee member) / Arizona State University (Publisher)
Created2012
Description
In the modern age, where teams consist of people from disparate locations, remote team training is highly desired. Moreover, team members' overlapping schedules force their mentors to focus on individual training instead of team training. Team training is an integral part of collaborative team work. With the advent of modern technologies such as Web 2.0, cloud computing, etc. it is possible to revolutionize the delivery of time-critical team training in varied domains of healthcare military and education. Collaborative Virtual Environments (CVEs), also known as virtual worlds, and the existing worldwide footprint of high speed internet, would make remote team training ubiquitous. Such an integrated system would potentially help in assisting actual mentors to overcome the challenges in team training. ACLS is a time-critical activity which requires a high performance team effort. This thesis proposes a system that leverages a virtual world (VW) and provides an integrated learning platform for Advanced Cardiac Life Support (ACLS) case scenarios. The system integrates feedback devices such as haptic device so that real time feedback can be provided. Participants can log in remotely and work in a team to diagnose the given scenario. They can be trained and tested for ACLS within the virtual world. This system is well equipped with persuasive elements which aid in learning. The simulated training in this system was validated to teach novices the procedural aspect of ACLS. Sixteen participants were divided into four groups (two control groups and two experimental groups) of four participants. All four groups went through didactic session where they learned about ACLS and its procedures. A quiz after the didactic session revealed that all four groups had equal knowledge about ACLS. The two experimental groups went through training and testing in the virtual world. Experimental group 2 which was aided by the persuasive elements performed better than the control group. To validate the training capabilities of the virtual world system, final transfer test was conducted in real world setting at Banner Simulation Center on high fidelity mannequins. The test revealed that the experimental groups (average score 65/100) performed better than the control groups (average score 16/100). The experimental group 2 which was aided by the persuasive elements (average score 70/100) performed better than the experimental group 1 (average score 55/100). This shows that the persuasive technology can be useful for training purposes.
ContributorsParab, Sainath (Author) / Kahol, Kanav (Thesis advisor) / Burleson, Wnslow (Thesis advisor) / Li, Baioxin (Committee member) / Arizona State University (Publisher)
Created2010
Description
Traditional sports coaching involves face-to-face instructions with athletes or playingback 2D videos of athletes’ training. However, if the coach is not in the same area
as the athlete, then the coach will not be able to see the athlete’s full body and thus
cannot give precise guidance to the athlete, limiting the athlete’s improvement. To
address these challenges, this paper proposes Augmented Coach, an augmented reality
platform where coaches can view, manipulate and comment on athletes’ movement
volumetric video data remotely via the network. In particular, this work includes a).
Capturing the athlete’s movement video data with Kinects and converting it into point
cloud format b). Transmitting the point cloud data to the coach’s Oculus headset via
5G or wireless network c). Coach’s commenting on the athlete’s joints. In addition,
the evaluation of Augmented Coach includes an assessment of its performance from
five metrics via the wireless network and 5G network environment, but also from the
coaches’ and athletes’ experience of using it. The result shows that Augmented Coach
enables coaches to instruct athletes from a distance and provide effective feedback for
correcting athletes’ motions under the network.
ContributorsQiao, Yunhan (Author) / LiKamWa, Robert (Thesis advisor) / Bansal, Ajay (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2023
Description
Research has shown that the learning processes can be enriched and enhanced with the presence of affective interventions. The goal of this dissertation was to design, implement, and evaluate an affective agent that provides affective support in real-time in order to enrich the student’s learning experience and performance by inducing and/or maintaining a productive learning path. This work combined research and best practices from affective computing, intelligent tutoring systems, and educational technology to address the design and implementation of an affective agent and corresponding pedagogical interventions. It included the incorporation of the affective agent into an Exploratory Learning Environment (ELE) adapted for this research.
A gendered, three-dimensional, animated, human-like character accompanied by text- and speech-based dialogue visually represented the proposed affective agent. The agent’s pedagogical interventions considered inputs from the ELE (interface, model building, and performance events) and from the user (emotional and cognitive events). The user’s emotional events captured by biometric sensors and processed by a decision-level fusion algorithm for a multimodal system in combination with the events from the ELE informed the production-rule-based behavior engine to define and trigger pedagogical interventions. The pedagogical interventions were focused on affective dimensions and occurred in the form of affective dialogue prompts and animations.
An experiment was conducted to assess the impact of the affective agent, Hope, on the student’s learning experience and performance. In terms of the student’s learning experience, the effect of the agent was analyzed in four components: perception of the instructional material, perception of the usefulness of the agent, ELE usability, and the affective responses from the agent triggered by the student’s affective states.
Additionally, in terms of the student’s performance, the effect of the agent was analyzed in five components: tasks completed, time spent solving a task, planning time while solving a task, usage of the provided help, and attempts to successfully complete a task. The findings from the experiment did not provide the anticipated results related to the effect of the agent; however, the results provided insights to improve diverse components in the design of affective agents as well as for the design of the behavior engines and algorithms to detect, represent, and handle affective information.
A gendered, three-dimensional, animated, human-like character accompanied by text- and speech-based dialogue visually represented the proposed affective agent. The agent’s pedagogical interventions considered inputs from the ELE (interface, model building, and performance events) and from the user (emotional and cognitive events). The user’s emotional events captured by biometric sensors and processed by a decision-level fusion algorithm for a multimodal system in combination with the events from the ELE informed the production-rule-based behavior engine to define and trigger pedagogical interventions. The pedagogical interventions were focused on affective dimensions and occurred in the form of affective dialogue prompts and animations.
An experiment was conducted to assess the impact of the affective agent, Hope, on the student’s learning experience and performance. In terms of the student’s learning experience, the effect of the agent was analyzed in four components: perception of the instructional material, perception of the usefulness of the agent, ELE usability, and the affective responses from the agent triggered by the student’s affective states.
Additionally, in terms of the student’s performance, the effect of the agent was analyzed in five components: tasks completed, time spent solving a task, planning time while solving a task, usage of the provided help, and attempts to successfully complete a task. The findings from the experiment did not provide the anticipated results related to the effect of the agent; however, the results provided insights to improve diverse components in the design of affective agents as well as for the design of the behavior engines and algorithms to detect, represent, and handle affective information.
ContributorsChavez Echeagaray, Maria Elena (Author) / Atkinson, Robert K (Thesis advisor) / Burleson, Winslow (Thesis advisor) / Graesser, Arthur C. (Committee member) / VanLehn, Kurt (Committee member) / Walker, Erin A (Committee member) / Arizona State University (Publisher)
Created2018
Description
Reading partners’ actions correctly is essential for successful coordination, but interpretation does not always reflect reality. Attribution biases, such as self-serving and correspondence biases, lead people to misinterpret their partners’ actions and falsely assign blame after an unexpected event. These biases thus further influence people’s trust in their partners, including machine partners. The increasing capabilities and complexity of machines allow them to work physically with humans. However, their improvements may interfere with the accuracy for people to calibrate trust in machines and their capabilities, which requires an understanding of attribution biases’ effect on human-machine coordination. Specifically, the current thesis explores how the development of trust in a partner is influenced by attribution biases and people’s assignment of blame for a negative outcome. This study can also suggest how a machine partner should be designed to react to environmental disturbances and report the appropriate level of information about external conditions.
ContributorsHsiung, Chi-Ping (M.S.) (Author) / Chiou, Erin (Thesis advisor) / Cooke, Nancy J. (Thesis advisor) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2019
Description
Highly automated vehicles require drivers to remain aware enough to takeover
during critical events. Driver distraction is a key factor that prevents drivers from reacting
adequately, and thus there is need for an alert to help drivers regain situational awareness
and be able to act quickly and successfully should a critical event arise. This study
examines two aspects of alerts that could help facilitate driver takeover: mode (auditory
and tactile) and direction (towards and away). Auditory alerts appear to be somewhat
more effective than tactile alerts, though both modes produce significantly faster reaction
times than no alert. Alerts moving towards the driver also appear to be more effective
than alerts moving away from the driver. Future research should examine how
multimodal alerts differ from single mode, and see if higher fidelity alerts influence
takeover times.
during critical events. Driver distraction is a key factor that prevents drivers from reacting
adequately, and thus there is need for an alert to help drivers regain situational awareness
and be able to act quickly and successfully should a critical event arise. This study
examines two aspects of alerts that could help facilitate driver takeover: mode (auditory
and tactile) and direction (towards and away). Auditory alerts appear to be somewhat
more effective than tactile alerts, though both modes produce significantly faster reaction
times than no alert. Alerts moving towards the driver also appear to be more effective
than alerts moving away from the driver. Future research should examine how
multimodal alerts differ from single mode, and see if higher fidelity alerts influence
takeover times.
ContributorsBrogdon, Michael A (Author) / Gray, Robert (Thesis advisor) / Branaghan, Russell (Committee member) / Chiou, Erin (Committee member) / Arizona State University (Publisher)
Created2018
Description
An old proverb claims that “two heads are better than one”. Crowdsourcing research and practice have taken this to heart, attempting to show that thousands of heads can be even better. This is not limited to leveraging a crowd’s knowledge, but also their creativity—the ability to generate something not only useful, but also novel. In practice, there are initiatives such as Free and Open Source Software communities developing innovative software. In research, the field of crowdsourced creativity, which attempts to design scalable support mechanisms, is blooming. However, both contexts still present many opportunities for advancement.
In this dissertation, I seek to advance both the knowledge of limitations in current technologies used in practice as well as the mechanisms that can be used for large-scale support. The overall research question I explore is: “How can we support large-scale creative collaboration in distributed online communities?” I first advance existing support techniques by evaluating the impact of active support in brainstorming performance. Furthermore, I leverage existing theoretical models of individual idea generation as well as recommender system techniques to design CrowdMuse, a novel adaptive large-scale idea generation system. CrowdMuse models users in order to adapt itself to each individual. I evaluate the system’s efficacy through two large-scale studies. I also advance knowledge of current large-scale practices by examining common communication channels under the lens of Creativity Support Tools, yielding a list of creativity bottlenecks brought about by the affordances of these channels. Finally, I connect both ends of this dissertation by deploying CrowdMuse in an Open Source online community for two weeks. I evaluate their usage of the system as well as its perceived benefits and issues compared to traditional communication tools.
This dissertation makes the following contributions to the field of large-scale creativity: 1) the design and evaluation of a first-of-its-kind adaptive brainstorming system; 2) the evaluation of the effects of active inspirations compared to simple idea exposure; 3) the development and application of a set of creativity support design heuristics to uncover creativity bottlenecks; and 4) an exploration of large-scale brainstorming systems’ usefulness to online communities.
In this dissertation, I seek to advance both the knowledge of limitations in current technologies used in practice as well as the mechanisms that can be used for large-scale support. The overall research question I explore is: “How can we support large-scale creative collaboration in distributed online communities?” I first advance existing support techniques by evaluating the impact of active support in brainstorming performance. Furthermore, I leverage existing theoretical models of individual idea generation as well as recommender system techniques to design CrowdMuse, a novel adaptive large-scale idea generation system. CrowdMuse models users in order to adapt itself to each individual. I evaluate the system’s efficacy through two large-scale studies. I also advance knowledge of current large-scale practices by examining common communication channels under the lens of Creativity Support Tools, yielding a list of creativity bottlenecks brought about by the affordances of these channels. Finally, I connect both ends of this dissertation by deploying CrowdMuse in an Open Source online community for two weeks. I evaluate their usage of the system as well as its perceived benefits and issues compared to traditional communication tools.
This dissertation makes the following contributions to the field of large-scale creativity: 1) the design and evaluation of a first-of-its-kind adaptive brainstorming system; 2) the evaluation of the effects of active inspirations compared to simple idea exposure; 3) the development and application of a set of creativity support design heuristics to uncover creativity bottlenecks; and 4) an exploration of large-scale brainstorming systems’ usefulness to online communities.
Contributorsda Silva Girotto, Victor Augusto (Author) / Walker, Erin A (Thesis advisor) / Burleson, Winslow (Thesis advisor) / Maciejewski, Ross (Committee member) / Hsiao, Sharon (Committee member) / Bigham, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2019