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    LiquidText: supporting active reading through flexible document representations

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    tashman_craig_s_201205_phd.pdf (16.94Mb)
    Date
    2012-04-03
    Author
    Tashman, Craig Stuart
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    Abstract
    Knowledge workers are frequently called upon to perform deep, critical reading involving a heightened level of interaction with the reading media and other tools. This process, known as active reading, entails highlighting, commenting upon, and flipping through a text, in addition to other actions. While paper is traditionally seen as the ideal medium for active reading, computers have recently become comparable to paper through replicating the latter’s affordances. But even paper is not a panacea; it offers an inflexible document representation that supports some things well, such as embellishment, but supports others very poorly, like comparison and large scale annotation. In response to this, I developed a prototype system, called LiquidText, to embody a flexible, high degree-of-freedom visual representation that seeks to alleviate some of the problems in paper and paper-like representations. To provide efficient control of this representation, LiquidText runs on a multi-finger touch and gesture based platform. To guide the development of this system, I conducted a formative study of current active reading practice. I investigated knowledge workers’ active reading habits, perceptions, and the problems they face with current reading media. I also inquired into what they would like in a future active reading environment. I used these results in conjunction with multiple design iterations and formative system evaluations to refine LiquidText for use in a summative study. The summative study assessed, through a controlled, laboratory evaluation, LiquidText’s impact on 1) the subjective experience of active reading, 2) the process of active reading, and 3) the outputs resulting from active reading. Generally, the study found a strong participant preference for LiquidText, and a focus on the creation of a summary of the original document as part of the reading process. On average, reading outputs were not significantly better or worse with LiquidText, but some conditions were observed that may help identify the subset of people for whom LiquidText will result in an improvement.
    URI
    http://hdl.handle.net/1853/51732
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    • Georgia Tech Theses and Dissertations [22398]
    • School of Interactive Computing Theses and Dissertations [106]

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