Eun Kyoung Choe
Pennsylvania State University
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Publication
Featured researches published by Eun Kyoung Choe.
ubiquitous computing | 2012
Matthew Kay; Eun Kyoung Choe; Jesse Shepherd; Benjamin Greenstein; Nathaniel F. Watson; Sunny Consolvo; Julie A. Kientz
The bedroom environment can have a significant impact on the quality of a persons sleep. Experts recommend sleeping in a room that is cool, dark, quiet, and free from disruptors to ensure the best quality sleep. However, it is sometimes difficult for a person to assess which factors in the environment may be causing disrupted sleep. In this paper, we present the design, implementation, and initial evaluation of a capture and access system, called Lullaby. Lullaby combines temperature, light, and motion sensors, audio and photos, and an off-the-shelf sleep sensor to provide a comprehensive recording of a persons sleep. Lullaby allows users to review graphs and access recordings of factors relating to their sleep quality and environmental conditions to look for trends and potential causes of sleep disruptions. In this paper, we report results of a feasibility study where participants (N=4) used Lullaby in their homes for two weeks. Based on our experiences, we discuss design insights for sleep technologies, capture and access applications, and personal informatics tools.
human factors in computing systems | 2011
Eun Kyoung Choe; Sunny Consolvo; Nathaniel F. Watson; Julie A. Kientz
Getting the right amount of quality sleep is a key aspect of good health, along with a healthy diet and regular exercise. Human-computer interaction (HCI) researchers have recently designed systems to support diet and exercise, but sleep has been relatively under-studied in the HCI community. We conducted a literature review and formative study aimed at uncovering opportunities for computing to support the important area of promoting healthy sleep. We present results from interviews with sleep experts, as well as a survey (N = 230) and interviews with potential users (N = 16) to indicate what people would find practical and useful for sleep. Based on these results, we identify a number of design considerations, challenges, and opportunities for using computing to support healthy sleep behaviors, as well as a design framework for mapping the design space of technologies for sleep.
ubiquitous computing | 2011
Eun Kyoung Choe; Sunny Consolvo; Jaeyeon Jung; Beverly L. Harrison; Julie A. Kientz
As advances in technology accelerate, sensors and recording devices are increasingly being integrated into homes. Although the added benefit of sensing is often clear (e.g., entertainment, security, encouraging sustainable behaviors, etc.), the home is a private and intimate place, with multiple stakeholders who may have competing priorities and tolerances for what is acceptable and useful. In an effort to develop systems that account for the needs and concerns of householders, we conducted an anonymous survey (N = 475) focusing on the activities and habits that people do at home that they would not want to be recorded. In this paper, we discuss those activities and where in the home they are performed, and offer suggestions for the design of UbiComp systems that rely on sensing and recording.
ubiquitous computing | 2015
Eun Kyoung Choe; Bongshin Lee; Matthew Kay; Wanda Pratt; Julie A. Kientz
Manual tracking of health behaviors affords many benefits, including increased awareness and engagement. However, the capture burden makes long-term manual tracking challenging. In this study on sleep tracking, we examine ways to reduce the capture burden of manual tracking while leveraging its benefits. We report on the design and evaluation of SleepTight, a low-burden, self-monitoring tool that leverages the Androids widgets both to reduce the capture burden and to improve access to information. Through a four-week deployment study (N = 22), we found that participants who used SleepTight with the widgets enabled had a higher sleep diary compliance rate (92%) than participants who used SleepTight without the widgets (73%). In addition, the widgets improved information access and encouraged self-reflection. We discuss how to leverage widgets to help people collect more data and improve access to information, and more broadly, how to design successful manual self-monitoring tools that support self-reflection.
international conference on human-computer interaction | 2013
Eun Kyoung Choe; Jaeyeon Jung; Bongshin Lee; Kristie Fisher
Smartphone users visit application marketplaces (or app stores) to search and install applications. However, these app stores are not free from privacy-invasive apps, which collect personal information without sufficient disclosure or people’s consent. To nudge people away from privacy-invasive apps, we created a visual representation of the mobile app’s privacy rating. Inspired by “Framing Effects,” we designed semantically equivalent visuals that are framed in either a positive or negative way. We investigated the effect of the visual privacy rating, framing, and user rating on people’s perception of an app (e.g., trustworthiness) through two experiments. In Study 1, participants were able to understand the intended meaning of the visual privacy ratings. In Study 2, we found a strong main effect for visual privacy rating on participants’ perception of an app, and framing effects in a low privacy rating app. We discuss implications for designing visual privacy ratings, including the use of positive visual framing to nudge people away from privacy-invasive apps.
IEEE Computer Graphics and Applications | 2015
Eun Kyoung Choe; Bongshin Lee; m.c. schraefel
Data visualization and analytics research has great potential to empower people to improve their lives by leveraging their own personal data. However, most quantified selfers (Q-Selfers) are neither visualization experts nor data scientists. Consequently, visualizations Q-Selfers created with their data are often not ideal for conveying insights. Aiming to design a visualization system to help nonexperts gain and communicate personal data insights, the authors conducted a predesign empirical study. Through the lens of Q-Selfers, they examined what insights people gain specifically from their personal data and how they use visualizations to communicate their insights. Based on their analysis of 30 quantified self-presentations, they characterized eight insight types (detail, self-reflection, trend, comparison, correlation, data summary, distribution, and outlier) and mapped the visual annotations used to communicate them. They further discussed four areas for the design of personal visualization systems, including support for encouraging self-reflection, gaining valid insight, communicating insight, and using visual annotations.
international health informatics symposium | 2010
Julie A. Kientz; Eun Kyoung Choe; Brennen Birch; Robert Maharaj; Amanda Fonville; Chelsey Glasson; Jen Mundt
Persuasive technologies for promoting physical fitness, good nutrition, and other healthy behaviors have been growing in popularity. Despite their appeal, the evaluation of these technologies remains a challenge and typically requires a fully functional prototype and long-term deployment. In this paper, we attempt to help bridge this gap by presenting a method for using heuristic evaluation to evaluate persuasive technologies. We developed a set of 10 heuristics intended to find problems in persuasive technologies that would affect persuasive elements, adoption, or long-term effectiveness of the technologies. We compared the performance of Nielsens heuristics to our heuristics on two persuasive technologies using 10 different evaluators. Using our heuristics, evaluators found more severe problems more frequently. In addition, the issues that found only by our heuristics were more severe and more relevant to persuasive, cultural, and informational issues of the interfaces evaluated. Our method can be helpful in finding problems in persuasive technologies for promoting healthy behaviors earlier in the design process.
human factors in computing systems | 2010
Eun Kyoung Choe; Julie A. Kientz; Sajanee Halko; Amanda Fonville; Dawn Sakaguchi; Nathaniel F. Watson
Getting the right amount of quality sleep is one of the key aspects of good health, along with a healthy diet and regular exercise. We conducted a literature review and formative study aimed at uncovering the opportunities for technology to support healthy sleep behaviors. We present the results of interviews with sleep experts, a large survey, and interviews with potential users that indicate what people would find practical and useful for sleep. We identified a number of functional and non-functional requirements for technology for sleep. We explored three possible technology ideas for healthy sleep behaviors: a sleep tracking tool, game to promote sleep, and sleep condition assessment tool.
international conference on pervasive computing | 2017
Eun Kyoung Choe; Bongshin Lee; Haining Zhu; Nathalie Henry Riche; Dominikus Baur
Rapid advancements in consumer technologies enable people to collect a wide range of personal data. With a proper means for people to ask questions and explore their data, longitudinal data feeds from multiple self-tracking tools pose great opportunities to foster deep self-reflection. However, most self-tracking tools lack support for self-reflection beyond providing simple feedback. Our overarching goal is to support self-trackers in reflecting on their data and gaining rich insights through visual data exploration. As a first step toward the goal, we built a web-based application called Visualized Self, and conducted an in-lab think-aloud study (N = 11) to examine how people reflect on their personal data and what types of insights they gain throughout the reflection. We discuss lessons learned from studying with Visualized Self, and suggest directions for designing visual data exploration tools for fostering self-reflection.
ieee pacific visualization symposium | 2017
Donghao Ren; Matthew Brehmer; Bongshin Lee; Tobias Höllerer; Eun Kyoung Choe
Annotation plays an important role in conveying key points in visual data-driven storytelling; it helps presenters explain and emphasize core messages and specific data. However, the visualization research community has a limited understanding of annotation and its role in data-driven storytelling, and existing charting software provides limited support for creating annotations. In this paper, we characterize a design space of chart annotations, one informed by a survey of 106 annotated charts published by six prominent news graphics desks. Using this design space, we designed and developed ChartAccent, a tool that allows people to quickly and easily augment charts via a palette of annotation interactions that generate manual and data-driven annotations. We also report on a study in which participants reproduced a series of annotated charts using ChartAccent, beginning with unadorned versions of the same charts. Finally, we discuss the lessons learned during the process of designing and evaluating ChartAccent, and suggest directions for future research.