Person:
Gajos, Krzysztof

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Gajos

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Krzysztof

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Gajos, Krzysztof

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Now showing 1 - 10 of 51
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    DERBI: A Digital Method to Help Researchers Offer “Right-to-Know” Personal Exposure Results
    (National Institute of Environmental Health Sciences, 2017) Boronow, Katherine E.; Susmann, Herbert P.; Gajos, Krzysztof; Rudel, Ruthann A.; Arnold, Kenneth; Brown, Phil; Morello-Frosch, Rachel; Havas, Laurie; Brody, Julia Green
    Summary: Researchers and clinicians in environmental health and medicine increasingly show respect for participants and patients by involving them in decision-making. In this context, the return of personal results to study participants is becoming ethical best practice, and many participants now expect to see their data. However, researchers often lack the time and expertise required for report-back, especially as studies measure greater numbers of analytes, including many without clear health guidelines. In this article, our goal is to demonstrate how a prototype digital method, the Digital Exposure Report-Back Interface (DERBI), can reduce practical barriers to high-quality report-back. DERBI uses decision rules to automate the production of personalized summaries of notable results and generates graphs of individual results with comparisons to the study group and benchmark populations. Reports discuss potential sources of chemical exposure, what is known and unknown about health effects, strategies for exposure reduction, and study-wide findings. Researcher tools promote discovery by drawing attention to patterns of high exposure and offer novel ways to increase participant engagement. DERBI reports have been field tested in two studies. Digital methods like DERBI reduce practical barriers to report-back thus enabling researchers to meet their ethical obligations and participants to get knowledge they can use to make informed choices.
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    Doodle Around the World: Online Scheduling Behavior Reflects Cultural Differences in Time Perception and Group Decision-Making
    (ACM Press, 2013) Reinecke, Katharina; Nguyen, Minh Khoa; Bernstein, Abraham; Näf, Michael; Gajos, Krzysztof
    Event scheduling is a group decision-making process in which social dynamics influence people's choices and the overall outcome. As a result, scheduling is not simply a matter of finding a mutually agreeable time, but a process that is shaped by social norms and values, which can highly vary between countries. To investigate the influence of national culture on people's scheduling behavior we analyzed more than 1.5 million Doodle date/time polls from 211 countries. We found strong correlations between characteristics of national culture and several behavioral phenomena, such as that poll participants from collectivist countries respond earlier, agree to fewer options but find more consensus than predominantly individualist societies. Our study provides empirical evidence of behavioral differences in group decision-making and time perception with implications for cross-cultural collaborative work.
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    SPRWeb: preserving subjective responses to website colour schemes through automatic recolouring
    (ACM Press, 2013) Flatla, David R.; Reinecke, Katharina; Gutwin, Carl; Gajos, Krzysztof
    Colours are an important part of user experiences on the Web. Colour schemes influence the aesthetics, first impressions and long-term engagement with websites. However, five percent of people perceive a subset of all colours because they have colour vision deficiency (CVD), resulting in an unequal and less-rich user experience on the Web. Traditionally, people with CVD have been supported by recolouring tools that improve colour differentiability, but do not consider the subjective properties of colour schemes while recolouring. To address this, we developed SPRWeb, a tool that recolours websites to preserve subjective responses and improve colour differentiability - thus enabling users with CVD to have similar online experiences. To develop SPRWeb, we extended existing models of non-CVD subjective responses to CVD, then used this extended model to steer the recolouring process. In a lab study, we found that SPRWeb did significantly better than a standard recolouring tool at preserving the temperature and naturalness of websites, while achieving similar weight and differentiability preservation. We also found that recolouring did not preserve activity, and hypothesize that visual complexity influences activity more than colour. SPRWeb is the first tool to automatically preserve the subjective and perceptual properties of website colour schemes thereby equalizing the colour-based web experience for people with CVD.
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    Crowdsourcing performance evaluations of user interfaces
    (ACM Press, 2013) Komarov, Steven; Reinecke, Katharina; Gajos, Krzysztof
    Online labor markets, such as Amazon's Mechanical Turk (MTurk), provide an attractive platform for conducting human subjects experiments because the relative ease of recruitment, low cost, and a diverse pool of potential participants enable larger-scale experimentation and faster experimental revision cycle compared to lab-based settings. However, because the experimenter gives up the direct control over the participants' environments and behavior, concerns about the quality of the data collected in online settings are pervasive. In this paper, we investigate the feasibility of conducting online performance evaluations of user interfaces with anonymous, unsupervised, paid participants recruited via MTurk. We implemented three performance experiments to re-evaluate three previously well-studied user interface designs. We conducted each experiment both in lab and online with participants recruited via MTurk. The analysis of our results did not yield any evidence of significant or substantial differences in the data collected in the two settings: All statistically significant differences detected in lab were also present on MTurk and the effect sizes were similar. In addition, there were no significant differences between the two settings in the raw task completion times, error rates, consistency, or the rates of utilization of the novel interaction mechanisms introduced in the experiments. These results suggest that MTurk may be a productive setting for conducting performance evaluations of user interfaces providing a complementary approach to existing methodologies.
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    Predicting users' first impressions of website aesthetics with a quantification of perceived visual complexity and colorfulness
    (ACM Press, 2013) Reinecke, Katharina; Yeh, Tom; Miratrix, Luke; Mardiko, Rahmatri; Zhao, Yuechen; Liu, Jenny; Gajos, Krzysztof
    Users make lasting judgments about a website's appeal within a split second of seeing it for the first time. This first impression is influential enough to later affect their opinions of a site's usability and trustworthiness. In this paper, we demonstrate a means to predict the initial impression of aesthetics based on perceptual models of a website's colorfulness and visual complexity. In an online study, we collected ratings of colorfulness, visual complexity, and visual appeal of a set of 450 websites from 548 volunteers. Based on these data, we developed computational models that accurately measure the perceived visual complexity and colorfulness of website screenshots. In combination with demographic variables such as a user's education level and age, these models explain approximately half of the variance in the ratings of aesthetic appeal given after viewing a website for 500ms only.
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    Leveraging Video Interaction Data and Content Analysis to Improve Video Learning
    (2014) Gajos, Krzysztof; Kim, Juho; Li, Shang-Wen; Cai, Carrie J.; Miller, Robert C.
    Video has emerged as a dominant medium for online education, as witnessed by millions of students learning from educational videos on Massive Open Online Courses (MOOCs), Khan Academy, and YouTube. The large-scale data collected from students' interactions with video provide a unique opportunity to analyze and improve the video learning experience. We combine click-level interaction data, such as pausing, resuming, or navigating between points in the video, and video content analysis, such as visual, text, and speech, to analyze peaks in viewership and student activity. Such analysis can reveal points of interest or confusion in the video, and suggest production and editing improvements. Furthermore, we envision novel video interfaces and learning platforms that automatically adapt to learners' collective watching behaviors.
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    Preference elicitation for interface optimization
    (ACM, 2005) Gajos, Krzysztof; Weld, Daniel S.
    Decision-theoretic optimization is becoming a popular tool in the user interface community, but creating accurate cost (or utility) functions has become a bottleneck --- in most cases the numerous parameters of these functions are chosen manually, which is a tedious and error-prone process. This paper describes ARNAULD, a general interactive tool for eliciting user preferences concerning concrete outcomes and using this feedback to automatically learn a factored cost function. We empirically evaluate our machine learning algorithm and two automatic query generation approaches and report on an informal user study.
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    Automatically personalizing user interfaces
    (ACM, 2003) Weld, Daniel; Anderson, Corin; Domingos, Pedro; Etzioni, Oren; Gajos, Krzysztof; Lau, Tessa; Wolfman, Steve
    Todays computer interfaces are one-size-fits-all. Users with little programming experience have very limited opportunities to customize an interface to their task and work habits. Furthermore, the overhead induced by generic interfaces will be proportionately greater on small form-factor PDAs, embedded applications and wearable devices. Automatic personalization may greatly enhance user productivity, but it requires advances in customization (explicit, user-initiated change) and adaptation (interface-initiated change in response to routine user behavior). In order to improve customization, we must make it easier for users to direct these changes. In order to improve adaptation, we must better predict user behavior and navigate the inherent tension between the dynamism of automatic adaptation and the stability required in order for the user to predict the computers behavior and maintain control. This paper surveys a decade's work on customization and adaptation at the University of Washington, distilling the lessons we have learned.
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    From Care Plans to Care Coordination: Opportunities for Computer Support of Teamwork in Complex Healthcare
    (2015) Amir, Ofra; Grosz, Barbara; Gajos, Krzysztof; Swenson, Sonja M.; Sanders, Lee M.
    Children with complex health conditions require care from a large, diverse team of caregivers that includes multiple types of medical professionals, parents and community support organizations. Coordination of their outpatient care, essential for good outcomes, presents major challenges. Extensive healthcare research has shown that the use of integrated, team-based care plans improves care coordination, but such plans are rarely deployed in practice. This paper reports on a study of care teams treating children with complex conditions at a major university tertiary care center. This study investigated barriers to plan implementation and resultant care coordination problems. It revealed the complex nature of teamwork in complex care, which poses challenges to team coordination that extend beyond those identified in prior work and handled by existing coordination systems. The paper builds on a computational teamwork theory to identify opportunities for technology to support increased plan-based complex-care coordination and to propose design approaches for systems that enable and enhance such coordination.
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    Adaptive click-and-cross
    (Association of Computing Machinery, 2014) Li, Louis; Gajos, Krzysztof
    Computer users with impaired dexterity often have difficulty accessing small, densely packed user interface elements. Past research in software-based solutions has mainly employed two approaches: modifying the interface and modifying the interaction with the cursor. Each approach, however, has limitations. Modifying the user interface by enlarging interactive elements makes access efficient for simple interfaces but increases the cost of navigation for complex ones by displacing items to screens that require tabs or scrolling to reach. Modifying the interaction with the cursor makes access possible to unmodified interfaces but may perform poorly on densely packed targets or require the user to perform multiple steps. We developed a new approach that combines the strengths of the existing approaches while minimizing their shortcomings, introducing only minimal distortion to the original interface while making access to frequently used parts of the user interface efficient and access to all other parts possible. We instantiated this concept as Adaptive Click-and-Cross, a novel interaction technique. Our user study demonstrates that, for sufficiently complex interfaces, Adaptive Click-and-Cross slightly improves the performance of users with impaired dexterity compared to only modifying the interface or only modifying the cursor.