UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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    Exploring The Role Of Generative Artificial Intelligence In Cultural Relevant Storytelling For Native Language Learning Among Children
    (2024) Nanduri, Dinesh Kumar; Marsh, Diana E; Information Studies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In an era marked by the rapid disappearance of languages, UNESCO warns that nearly half of the world's linguistic heritage might soon become dormant. Despite its current health, Telugu has seen a decline in usage, reduced focus in India's educational systems, and overshadowing by dominant global languages. This thesis explores Generative Artificial Intelligence (GenAI) to counter this trend, focusing on its application in native language learning for children, key carriers of their ancestral tongues. Through scoping reviews and participatory design sessions with young Telugu-speaking learners and their guardians, the study investigates GenAI's role in enhancing language learning tailored to individual and cultural contexts. It highlights storytelling as a potent mechanism for language acquisition, facilitated by GenAI's ability to personalize learning experiences and bridge generational gaps. The research also addresses ethical considerations vital for designing GenAI tools, promoting inclusivity, bias mitigation, and cultural integrity protection. It showcases a future where technology helps prevent linguistic dormancy and empowers children to celebrate human language and cultural diversity.
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    DATA-DRIVEN STORYTELLING FOR CASUAL USERS
    (2019) Zhao, Zhenpeng; Elmqvist, Niklas; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Today’s overwhelming volume of data has made effective analysis virtually inaccessible for the general public. The emerging practice of data-driven storytelling is addressing this by framing data using familiar mechanisms such as slideshows, videos, and comics to make even highly complex phenomena understandable. However, current data stories still do not utilize the full potential of the storytelling domain. One reason for this is that current data-driven storytelling practice does not leverage the full repertoire of media that can be used for storytelling, such as speech, e-learning, and video games. In this dissertation, we propose a taxonomy focused specifically on media types for the purpose of widening the purview of data-driven storytelling by putting more tools in the hands of designers. We expand the idea of data-driven storytelling into the group of casual users, who are the consumers of information and non-professionals with limited time, skills, and motivation , to bridge the data gap between the advanced data analytics tools and everyday internet users. To prove the effectiveness and the wide acceptance of our taxonomy and data-driven storytelling among the casual users, we have collected examples for data-driven storytelling by finding, reviewing, and classifying ninety-one examples. Using our taxonomy as a generative tool, we also explored two novel storytelling mechanisms, including live-streaming analytics videos—DataTV—and sequential art (comics) that dynamically incorporates visual representations—Data Comics. Meanwhile, we widened the genres we explored to fill the gaps in the literature. We also evaluated Data Comics and DataTV with user studies and expert reviews. The results show that Data Comics facilitates data-driven storytelling in terms of inviting reading, aiding memory, and viewing as a story. The results also show that an integrated system as DataTV encourages authors to create and present data stories.
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    Art Criticism Through Storytelling
    (2006-05-12) Schappelle, Laura Scott; Hendricks, Susan; Curriculum and Instruction; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This Action Research study focused on the use of storytelling as a means of critically analyzing a work of art. The participants in this study were elementary students in the Fifth Grade. The participants wrote a story and verbally told a story in response to looking at a work of art. The researcher then compared the written and oral forms of communication to determine which yielded better results in terms of producing an effective art criticism. These responses will be compared to Feldman's Model, a popular approach of art criticism. The primary goal of the study was to see whether storytelling would prove to be an effective format for an art criticism. The secondary goal of this study was to analyze the difference between written and verbal forms of communication.