6 resultados para Interpersonal computer

em DRUM (Digital Repository at the University of Maryland)


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Human relationships have long been studied by scientists from domains like sociology, psychology, literature, etc. for understanding people's desires, goals, actions and expected behaviors. In this dissertation we study inter-personal relationships as expressed in natural language text. Modeling inter-personal relationships from text finds application in general natural language understanding, as well as real-world domains such as social networks, discussion forums, intelligent virtual agents, etc. We propose that the study of relationships should incorporate not only linguistic cues in text, but also the contexts in which these cues appear. Our investigations, backed by empirical evaluation, support this thesis, and demonstrate that the task benefits from using structured models that incorporate both types of information. We present such structured models to address the task of modeling the nature of relationships between any two given characters from a narrative. To begin with, we assume that relationships are of two types: cooperative and non-cooperative. We first describe an approach to jointly infer relationships between all characters in the narrative, and demonstrate how the task of characterizing the relationship between two characters can benefit from including information about their relationships with other characters in the narrative. We next formulate the relationship-modeling problem as a sequence prediction task to acknowledge the evolving nature of human relationships, and demonstrate the need to model the history of a relationship in predicting its evolution. Thereafter, we present a data-driven method to automatically discover various types of relationships such as familial, romantic, hostile, etc. Like before, we address the task of modeling evolving relationships but don't restrict ourselves to two types of relationships. We also demonstrate the need to incorporate not only local historical but also global context while solving this problem. Lastly, we demonstrate a practical application of modeling inter-personal relationships in the domain of online educational discussion forums. Such forums offer opportunities for its users to interact and form deeper relationships. With this view, we address the task of identifying initiation of such deeper relationships between a student and the instructor. Specifically, we analyze contents of the forums to automatically suggest threads to the instructors that require their intervention. By highlighting scenarios that need direct instructor-student interactions, we alleviate the need for the instructor to manually peruse all threads of the forum and also assist students who have limited avenues for communicating with instructors. We do this by incorporating the discourse structure of the thread through latent variables that abstractly represent contents of individual posts and model the flow of information in the thread. Such latent structured models that incorporate the linguistic cues without losing their context can be helpful in other related natural language understanding tasks as well. We demonstrate this by using the model for a very different task: identifying if a stated desire has been fulfilled by the end of a story.

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Gemstone Team ILL (Interactive Language Learning)

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Gemstone Team MICE (Modifying and Improving Computer Ergonomics)

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Gemstone Team FACE

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Gemstone Team FLIP (File Lending in Proximity)

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Behavioral Parent Training (BPT) is a well-established therapy that reduces child externalized behaviors and parent stress. Although BPT was originally developed for parents of children with defiant behaviors, the program’s key concepts are relevant to parenting all children. Since parents might not fully utilize BPT due to cost and program location, we created an online game as a low-cost, easily accessible alternative or complement to BPT. We tested the game with nineteen undergraduate students at the University of Maryland. The experimental group completed pretest survey on core BPT knowledge, played the game, and completed a BPT posttest, while the control group completed a pretest and posttest survey over a three week period. Participants in the experimental group also completed a survey to indicate their satisfaction with the overall program. The experimental group demonstrated significantly higher levels of BPT knowledge than the control group and high levels of satisfaction. This suggests that an interactive, online BPT platform is an engaging and accessible way for parents to learn key concepts.