CS/Psych-770 Human-Computer Interaction Poster Session
Room:
CS Lobby, West Entrance Ramp We invite graduate students and faculty to the CS/Psych-770 Human-Computer Interaction Poster Session to hear about 11 very interesting research projects completed by interdisciplinary groups of students. The Poster Session will be on the West Entrance Ramp of the Computer Sciences Building at 3-5 pm on Tuesday, December 18, 2012. There will be chocolate and cookies. Below are abstract for the projects.
The effects of Robot Orientation on Robot-mediated Group Conversations
Tsu-Lun Huang & Guru Subramani
Abstract: Although telepresence robot mediated communication is sparsely used at present, it is expected to be pervasive in the future. The goal of this study is to investigate the effect of ability to control the orientation of a telepresence robot has on group discussions. We tested (1) how telepresence robot mediated communication can be improved in terms of conversation quality and involvement, and (2) how the group perceived the utilization of a telepresence robot. We compared conversations mediated through traditional video conferences with conversations mediated through telepresence robot. Two experiments were conducted to examine the perception of both members on screen and physically in the group. A higher level of involvement was found when the robot can move its orientation. It is suggested that the utilization of telepresence robot with orienting features can be beneficial in group scenarios. More research is warranted with regards to the add-on feature of a telepresence robot.
The Effects of Agents on Lying
Monica Thompson & Le Yu
Abstract: Studies have shown that people have a tendency to lie on a regular basis. However, how does this behavior change when the entity being lied to happens to be a computer? Furthermore, will the tendency to lie change if the content of the lie is changed? Participants were asked to evaluate their willingness to lie to a text-based computer agent in ten different scenarios. Five of these scenarios dealt with situations in which the participants were potentially motivated to lie about a personal fact, such as weight, income, and schedule, while the remaining five involved lying about a personal opinion, which included musical taste, politics, and religion. These participants were then compared to a control group that evaluated the same scenarios, except they evaluated their willingness to lie to a person over text-mediated communication.
Accommodating Learning Styles: The Effect of Personalization on Learning Performance
Maggie Simon & Zexian Zeng
Abstract: Does personalization of a learning task according to a user’s learning style affect the learning performance of students? The literature shows students’ learning styles can affect overall performance in a Computer Science class. We focus on two main learning styles: visual and verbal. Twenty-five undergraduate students in CS 302 Introduction to Programming completed an online study, which included a learning styles inventory, pre-test, learning task, post-test, and a questionnaire about the study. Visual learners received a more visually oriented learning task while verbal learners received a more verbally oriented learning task. Those in the control group randomly received either the visual or verbal task. The primary measures include the percentage of questions answered correctly on the learning task and subjective self-report measures from the questionnaire. With this information, we evaluate the effect of personalization based on learning style.
The Effects of Background Environment and Gender on Social Presence and Trust During Telecollaboration
Rebecca Perkins & Alex Peer
Abstract: "Social presence refers simply to the feeling of being together with other parties engaged in a communication activity.” (Isgro et al. 2004, p.288) and is desirable during telecollaboration as it has been associated with increased trust and self-disclosure (Gunawardena, 2001, p.115). During telecollaboration, images of participants may highlight differences in user environments. This experiment examined how varying levels of environment similarity affect users’ sense of social presence and trust during telecollaboration and whether those effects vary based on participant gender. Participants were asked to complete a self-disclosure interview followed by a survey designed to measure social presence and trust. Subjective measures were the survey results and objective measures were answer duration and number of items shared with the interviewer. No significant effect of environment on social presence or trust was found and no significant interaction effect was found between environment and gender.
Effects of Computer-Mediated Communication Software Reliability on Trust Between Collaborators
Sarah Gilliland & Taylor Patterson
Abstract: It is becoming more frequent in industry and academia for collaboration to occur across considerable spacial and temporal separations. Previous research has shown that in the absence of face-to-face contact, the establishment and maintenance of trust between two or more people is observably more difficult. In addition, many software applications used for distance collaboration suffer from poor reliability. The goal of this study was to determine whether faulty or unreliable software affects the trust between two people collaborating on a project. We performed a between-participants study in which two people, a participant and a confederate, played a social dilemma game with only an instant messaging system to communicate with each other. In the control group, the communication software worked flawlessly while the evaluation group was subjected to frequent connection issues and failed message delivery. Objective and subjective analyses were completed in order to evaluate participants' trust in their collaboration partner.
The effects of Cognitive Load and Error Correcting Mode on User Preference for Voice Recognition Agents
Shiyu Luo & Theodora Hinkle
Abstract: Voice recognition technology is growing rapidly nowadays, it gives rise to growing groups of users. However, this technology is far from being perfect, thus error correction is necessary. We are interested in investigating people's attitudes towards this technology and their preferences for different error correction modes under different cognitive loads. A 2x2 factor design is conducted. Participants are asked to dictate different script to a voice recognition agent while they are playing a game, which simulates cognitive load in reality. Our study shows that people generally have a grown positive attitude in terms of accuracy and satisfaction towards voice recognition after completing our experiments. Also, our analysis shows that people lean toward the agent that offers suggestions when an error occurs, as oppose to the one that simple asks for repetition.
Effects of using computer agents vs. human on participant’s information exposure in health interviews
Xishuo Liu & Guangyu Liu
Abstract: Agent technologies have been widely considered in health care area. However there is little scientific research that considers information disclosures by people when interviewed by computer agents. In this work, we study information disclosures from male and female when interviewed by human versus computer agent. We recruit participants from the University of Wisconsin-Madison and Amazon Mechanical Turks. In our experiments, participants are interviewed on health care questions by a human interviewer or a computer agent. Participants answer interview questions by typing their answers into text boxes. From our data analyses, we show that the people are more likely to disclose information to human interviewer than computer agent. We also see that female participants disclose more information than male participants on normal health care questions but less likely to answer much on health related questions.
Leveraging Users Preference over Cloud Collaborative Software
Xiayuan Huang & Xiujun Li
Abstract: The advent of cloud collaborative software or platform has brought convenience to people for file storage, sharing and document collaboration, and it is being more and more popular among people. However, not all their functionalities and features are inspiring. We conduct an explorative study to leverage users preference and trust over some certain features (system encryption, user controls and service payment) to get an idea about people’s tradeoff when they are using this kind of software, to explore the correlationship among these features.
Effect of guidance from an agent for online foreign language study
Daniel Crowell & Jignwei Li
Abstract: The emergence of new interactive technologies could bring an opportunity to improve traditional learning methods and be the bright future for studying a foreign language. Our goal of the study is to see how much effect an agent or an avatar can have to assist people learning and memorizing foreign language words. The foreign language that we chose to conduct the research is Dutch. We used text and audio methods to make comparisons with the agent guidance. In the text option, participants only saw the Dutch word with a corresponding English word. The audio setting involved the participants seeing the word and the corresponded English word as well as hearing the word pronunciation and definition. For the last option, the participants saw agents presenting the meaning of the word. The 36 Dutch words and their presentation type (text, audio, or agent) were both randomly shuffled. At the end of the experiment, a memory test aimed to evaluate how well the participants memorized the words. We want to explore whether the presentations given by an agent would help the participant on memory retention. We are also curious if the words that were shown earlier would end up with higher correctness in the test than the ones that were shown later. The participants were gathered through Amazon Mechanical Turk, and agents were made through thevoki.com, a website for creating virtual speaking avatars.
Effects of information representation on recall in learning environment: a study of text, audio, multimedia, and human-like embodied agent
Yuqi He & Nai-Wen Yu
Abstract: A multimedia instructional message is a presentation consisting of words and pictures that is designed to foster meaningful learning. There is increasing interest in use of human embodied agents, also known as avatars, in the learning environment, specifically, in e-learning environment. Human-embodied agents have effects on human cognition and potentially increase students’ enjoyment of the learning experiences and students’ motivation. Our team notices this future trend; therefore, the goal of this study is to compare how different learning strategies— text, audio, multimedia and human like embodied agent—would affect students’ recall ability and examine whether human embodied agents would be superior than other learning strategies on recall. The topic we choose to test is a rare disease: Golloway-Mowat Syndrome. Thirty two native speakers were recruited in our study. We conducted a between-participant experimental design to evaluate which method has a stronger impact on recall performances.
The Effects of False Accusation in Automated Adjustment Notices on Procedural Fairness Perceptions of the IRS, Social Representations of Taxes, and Future Compliance
Cass Hausserman
Abstract: This study examines how an error by the IRS accusing taxpayers of owing additional money affects perceptions of procedural fairness, social representations of taxes, and ultimately future compliance. In a 2 x 2 fully factorial design, I manipulate whether the IRS system making the error is automated or not, as well as the party at fault for the error – either the IRS or the taxpayer’s employer. Twenty participants complete this study in which they are randomly assigned to conditions and receive hypothetical information about a scenario. Participants make compliance decisions and provide information about their feelings, as well as various demographic data and other potential controls. Both independent variables are marginally significant in predicting future compliance, but not necessarily in the expected directions. Automation is marginally significant in predicting social representations of taxes, and both automation and source of error are significant in predicting procedural fairness. Specifically, procedural fairness is higher when the system is automated and lower when the IRS made the error. In addition to these preliminary findings, results and feedback from this study provide insight into necessary instrument improvements.
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