Joanna McGrenere

Mobile devices deliver ‘notifications’ that interrupt the user for events like receivingtext messages and emails. However, frequent interruptions reduce productivityand can increase stress. Notification management tools can reduce this distractionbut substantial barriers, such as time and effort, prevent most users from managingtheir notifications.In this dissertation, I present three projects that aim to understand how to bettersupport proactive notification management and I systematically design a novelnotification management tool to better address user needs. We used a qualitative,user-centered approach consisting of interviews (N=71) and surveys (N=140).First, we explored how the notification management needs of older adults comparedto the general population because other forms of distraction disproportionatelyimpact older adults but their notification management needs had not beenstudied. Through semi-structured interviews (N=20) with both younger and olderadults, we identified that many users desire a sense of control and agency overtheir attention that was difficult to achieve with current notification managementtechnology.Second, we characterized how users could proactively control notificationsthrough four design axes. We created five notification management design conceptsthat included design elements from under-explored areas of our design axes.Through semi-structured interviews (N=30), we probed user reactions to our designconcepts to identify what design elements help address user concerns, such asa lack of control in notification management. The results of this study suggestedthere was strong interest to include reflective design elements within notificationmanagement.Lastly, we leveraged these results and a supplementary survey of users’ notificationpreferences (N=140) to design a novel notification management tool.The Reflective Spring Cleaning design supported infrequent notification managementwith visualizations of notification usage data and suggestions for personalization.We evaluated this design through a longitudinal study organized aroundsemi-structured interviews (N=21). Our results demonstrated how the concept encouragedand supported users to proactively manage notifications through criticalreflection on the impact of notifications.Our work outlines key design directions for how notification management toolscan support proactive notification management and provide users a sense of controlover their attention.

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People are creating and storing a growing amount of personal data, from photos and documents to messages and applications, on a growing number of devices. Storage space, often in the cloud, is cheap or free. But previous research shows that a degree of selectivity and curation is necessary to build personal archives that have value over time.In this dissertation, we ask: How do different people decide what personal data to keep or discard? What drives their decisions? And how can data management tools better support individual preferences?We used a qualitative and design-based approach to conduct four studies consisting of 64 interviews in total and a survey (n=349).First, we identified a spectrum of tendencies that informed how participants (n=23) decided what to keep or discard, with two extremes: “hoarding” (keep- ing most of data), and “minimalism” (keeping as little as possible). We extended this spectrum with a set of five behavioral styles that capture contextual curation patterns: taking a casual approach to data, feeling overwhelmed, collecting data, purging data, and trying to be frugal. This model of behaviors (based on the 64 interviews) highlights a key role for data curation: what people keep or discard informs how they think about their own identity.We used these insights to map a design space for data curation and create five design concepts for different user needs, exploring automation and other key design dimensions. Participants’ reactions (n=16) varied: some welcomed technology and automation, others opposed it, with context informing their reactions.Inspired by these results and using a taxonomy of data types and decluttering criteria based on the survey (n=349), we designed Data Dashboard, a tool that aggregates data from a user’s multitude of devices and cloud platforms, providing customizable functions for different goals. We evaluated a prototype of the system with 18 participants and found that a personalized approach to data curation is promising, so long as it respects users’ boundaries.Our work outlines key design directions and opportunities that can help envision new tools, prioritize user needs, and redefine our relationship with personal data in a world full of it.

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Interactive technologies have become prevalent in all aspects of life including managing our tasks, looking for information, and connecting with others. We often adapt our behaviors, consciously or unconsciously, to accommodate the technology. The unique nature of our needs and preferences, and how they change over time are better supported with technologies that are designed to be personalizable. Lack of personalization facilities limits our range of behaviors. In this dissertation, we focus on understanding and supporting differences in individuals’ behaviors through forms of personalization that are beyond choosing among a set of predefined options, by allowing users to author new functionalities. We refer to such personalizations as “advanced personalizations.” Authoring advanced personalizations, when supported, is often time-consuming and requires programming skills. Consequently, either because of lack of ability or time, many users take advantage of personalizations created and shared by others. The overarching goal of this dissertation is to design for authoring and sharing of advanced personalizations. We explore this goal in the domain of personal task management (PTM), where rich individual differences deeply influence user behavior and tool use. First, to gain insights into individual differences in PTM as well as changes in PTM behaviors over time, we conducted a series of studies: a focus group and contextual interviews in an academic setting, a large survey questionnaire with a broader population, and follow-up interviews with some of the survey respondents. These studies provide insights into different types of advanced perosnalizations that a PTM tool needs to support. Next, we designed a personalizable PTM tool with two key components for authoring advanced personalizations, building on ideas from end user programming approaches, and following theoretical guidelines on designing personalizable tools such as meta-design guidelines. A controlled user study of our design revealed opportunities and challenges in supporting advanced personalization, and our detailed design process provides a practical starting point for designing personalizable tools. Finally, through studying personalization sharing practices, we characterized the multi-faceted nature of online personalization sharing ecosystems, which include multiple components for hosting personalizations, discussing, and managing them. Our findings also highlight tradeoffs and design considerations in such ecosystems.

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Why do people visualize data? People visualize data either to consume or produce information relevant to a domain-specific problem or interest. Visualization design and evaluation involves a mapping between domain problems or interests and appropriate visual encoding and interaction design choices. This mapping translates a domain-specific situation into abstract visualization tasks, which allows for succinct descriptions of tasks and task sequences in terms of why data is visualized, what dependencies a task might have in terms of input and output, and how the task is supported in terms of visual encoding and interaction design choices. Describing tasks in this way facilitates the comparison and cross-pollination of visualization design choices across application domains; the mapping also applies in reverse, whenever visualization researchers aim to contextualize novel visualization techniques. In this dissertation, we present multiple instances of visualization task abstraction, each integrating our proposed typology of abstract visualization tasks. We apply this typology as an analysis tool in an interview study of individuals who visualize dimensionally reduced data in different application domains, in a post-deployment field study evaluation of a visual analysis tool in the domain of investigative journalism, and in a visualization design study in the domain of energy management. In the interview study, we draw upon and demonstrate the descriptive power of our typology to classify five task sequences relating to visualizing dimensionally reduced data. This classification is intended to inform the design of new tools and techniques for visualizing this form of data. In the field study, we draw upon and demonstrate the descriptive and evaluative power of our typology to evaluate Overview, a visualization tool for investigating large text document collections. After analyzing its adoption by investigative journalists, we characterize two abstract tasks relating to document mining and present seven lessons relating to the design of visualization tools for document data. In the design study, we demonstrate the descriptive, evaluative, and generative power of our typology and identify matches and mismatches between visualization design choices and three abstract tasks relating to time series data. Finally, we reflect upon the impact of our task typology.

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Mobile computing devices, such as smart phones, offer benefits that may be especially valuable to older adults (age 65+). However older adults have been shown to have difficulty learning to use these devices, which is a barrier for technology adoption. The main goal of the research reported in this dissertation was to investigate three promising design approaches – increasing the interpretability of graphical icons, incorporating a multi-layered interface, and augmenting the mobile device’s display – to determine whether each can improve the learnability of mobile devices for older adults. We involved both older and younger adults in our studies to uncover benefits unique to older adults. In our investigation of graphical icons, we conducted an experiment to determine which icon characteristics affect initial icon interpretability for older adults. We found that icon interpretability can be improved for older adults by reducing the semantic distance between the objects depicted in the icon and the icon’s function, and by labelling icons. In our investigation of multi-layered interfaces, we prototyped a two-layer smart phone address book and conducted an experiment to assess its learnability over four learning phases. We found that the multi-layered interface, compared to a non-layered full-functionality control interface, provided greater benefits for older participants than for younger participants in terms of faster task completion times during initial learning, lower perceived interface complexity, and greater interface preference for learning. In our investigation of augmenting a mobile device display with a larger display to help older adults learn new devices, we conducted a comprehensive survey of older adults’ learning needs and preferences. Based on the survey findings, we designed and prototyped Help Kiosk, an augmented display system for helping older adults to learn to use a smart phone. An informal evaluation found preliminary evidence that Help Kiosk may be able to assist older adults in performing new mobile phone tasks. Through these three investigations, our research identified and validated design approaches that researchers and developers can use to improve the learnability of mobile devices for older adults, which should increase the chances of technology adoption.

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Technology is increasingly being promoted as a means of addressing age-related cognitive and sensory impairments and enabling seniors to live more independently. Pen-based devices such as Personal Digital Assistants and Tablet PCs are appealing platforms for these endeavors because they are small, mobile, and powerful. Relative to the mouse, pen-based devices have been shown to be particularly beneficial for older adults. However, in terms of garnering wide-spread adoption, the mouse has historically dominated, leading researchers to focus chiefly on identifying and addressing its age- and motor-related limitations. In contrast, pen-based limitations for older users have been relatively unexplored. This thesis begins to fill that gap in the literature. Our first experiment, an empirical evaluation of pen-based target acquisition across the adult lifespan, identified three main sources of pen-based target acquisition difficulty—missing-just-below, slipping, and drifting—and demonstrated how these difficulties vary across task situation and age. In addition, this work showed that including older adults as participants can help uncover general pen-interaction problems: the missing-just-below and drifting difficulties were evident in both younger and older users alike. We next developed seven new target acquisition techniques to improve pen-based interaction, specifically addressing the three difficulties identified, and particularly targeting older adults. Our techniques built upon existing mouse-based techniques developed for older users and pen techniques for younger users. In total, we conducted three experiments to evaluate the seven new pen-based techniques: Reassigned and Deactivated (for missing-just-below), Tap and Glide (for drifting), and Steady, Bubble, and Steadied-Bubble (for slipping). Through these evaluations, we established where our proposed designs were successful at reducing errors, and where further refinement is needed. Finally, we reflected on our findings across studies to identify age-related, contextual, and technological factors which contributed to our results. These factors help illuminate the underlying reasons for pen-based targeting difficulties and shed light onto areas still needing attention. Overall, the results of this research support our main thesis that the accessibility of pen-based interfaces can be improved for older adults by first examining the sources of age-related acquisition difficulty, and then using the results of this examination to develop improved techniques.

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Personalized graphical user interfaces have the potential to reduce visualcomplexity and improve efficiency by modifying the interface to better suit anindividual user's needs. Working in a personalized interface can make usersfaster, more accurate and more satisfied; in practice, however, personalizationalso comes with costs, such as a reliance on user effort to control thepersonalization, or the introduction of spatial instability when interface itemsare reorganized automatically. We conducted a series of studies to examine boththe costs and benefits of personalization, and to identify techniques andcontexts that would be the most likely to provide an overall benefit.We first interviewed long-term users of a software application that providesadaptable (user-controlled) personalization. A design trade-off that emerged isthat while personalization can increase the accessibility of features useful to auser's current task, it may in turn negatively impact the user's awareness of thefull set of available features. To assess this potential trade-off, we introducedawareness as an evaluation metric to be used alongside more standard performancemeasures and we ran a series of three studies to understand how awareness relatesto core task performance. These studies used two different measures to assessawareness, showing that personalization can impact both the recognition rate ofunused features in the interface and user performance on new tasks requiringthose features. We investigated both adaptive (system-controlled) and adaptablepersonalization techniques to help us understand the generalizability of theawareness concept.In addition to introducing and incorporating awareness into our evaluations, westudied how specific contextual and design characteristics impact the user'sexperience with adaptive interfaces. In one study, we evaluated the impact ofscreen size on performance and user satisfaction with adaptive split menus.Results showed that the performance and satisfaction benefits of spatiallyreorganizing items in the interface are more likely to outweigh the costs whenscreen size is small. We also introduced a new adaptive personalization techniquethat maintains spatial stability, called ephemeral adaptation, and evaluated itthrough two studies. Ephemeral adaptation improves performance over bothanother closely related adaptive technique and a traditional interface.

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