Theses and Dissertations from UMD
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Item THANK YOU FOR BEING A FRIEND: THE RELATIONS BETWEEN FRIENDSHIP NETWORK CENTRALITY, READING ACHIEVEMENT, AND EXECUTIVE FUNCTIONING IN ELEMENTARY SCHOOL STUDENTS(2021) Archer, Casey Jonathan; Blazar, David; Education Policy, and Leadership; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Peer relationships form the bedrock for numerous developmental outcomes, including students’ social-emotional wellness, their sense of belonging, their decision-making, and the development of their sense of self. While educators acknowledge the importance of students’ social-emotional well-being and their relationship building, these concepts are often thought of as secondary to developing students’ academic achievement, particularly considering the oversized role of high-stakes testing in the US educational system. However, the divide between social interactions and academic achievement is not as stark as policymakers may make it seem. Indeed, research by developmental psychologists and education researchers has long documented that having strong peer relationships will allow children to thrive, including on academic development. This three-paper dissertation aims to provide evidence demonstrating the relation between being connected to one’s peers, reading achievement, and the development of executive functioning skills for elementary-aged students, including on a sample of primarily English Learners. Throughout all three studies, data were collected as part of Project LEARN, a three-year longitudinal study that measured various components of reading development alongside executive functioning and other variables, ultimately aiming to compare reading trajectories for elementary-aged English Learners and English Monolinguals. Paper 1, “Peer Effects on Oral Language Comprehension in Elementary School: A Social Network Analysis” uses student friendship nominations across three semesters (N=414) as well as students’ oral comprehension scores. This paper asks, What is the relation between student centrality (i.e., being connected to one’s classroom peers) and change in academic achievement, as measured by oral language skills? After generating social networks using the friendship nominations, I calculated how central each student was within their classroom friendship network. Using a student fixed effects model comparing students’ oral comprehension growth as a function of their classroom centrality, I find that students’ predicted oral comprehension growth is significantly greater when students are more central within their classroom network, even after controlling for other reading variables in the model. This paper supports the connection between peer relationships and academics (using oral language as a proxy), suggesting that reading interventions and pedagogy should leverage peer relationships as one way to improve student learning. Paper 2, “The Differential Relation between Friendship Centrality and Reading Outcomes for English Learners,” uses the same data as Paper 1, focusing on whether student centrality differentially predicts reading outcomes for English Learners and English Monolinguals. This paper asks, a) To what extent does classroom friendship centrality predict reading achievement gains for English Learners? and b) To what extent does the relationship between classroom friendship centrality and reading achievement gains differ between English Learners and English Monolinguals? I used a series of multiple linear regression models, with students nested in homeroom classrooms, to answer the two research questions. First, using a sample of only English Learners (N=160), I find that English Learners are more likely to experience significant gains in oral language comprehension—but not reading comprehension—when they are more central within their classroom network. Using the full sample of students (N=229), I find that English Monolinguals are significantly more likely to experience gains in reading comprehension when they are more central within their classroom friendship network, but there is no relation between friendship centrality and reading comprehension development for English Learners. This surprising finding, that friendship centrality predicts English Learners’ oral language development but not their reading comprehension development, raises pedagogical questions about how best to support English Learners’ reading outcomes. More research is needed, with particular attention focused on whether English Learners who are more connected within their classrooms experience similar levels of self-efficacy and sense of belonging as their connected English Monolingual peers. Paper 3, “Do Executive Functioning Skills Predict Reading Comprehension Growth?” uses students’ executive functioning composites—consisting of inhibitory control, cognitive flexibility, and memory scores—and reading comprehension scores in two subsequent semesters. This paper asks, To what extent do students’ growth in executive functioning predict their reading comprehension growth? Using two methods that aim to limit omitted variable bias—multiple regression with covariate adjustment and propensity score matching—I find that students’ growth in executive functioning significantly predicts their reading comprehension growth. This study provides support that interventions targeting students’ executive functioning may also contribute to their reading development.Item LEVERAGING SOCIAL NETWORKS TO FIGHT HIV: THE BATTLE OF FEMALE SEX WORKERS(2020) Li, Yuruo; Liu, Hongjie; Epidemiology and Biostatistics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation aims to assess the applicability of the social network method on HIV research among female sex workers (FSWs). Manuscript 1 reported the findings from a systematic literature review which examined the application of social network method in HIV studies focusing on FSWs. The majority of the identified studies were limited to local social networks or FSW establishments and did not use sophisticated statistical approaches to analyze sociocentric network data. The discrepancies in network definitions and data collections made it difficult in interpreting their findings and assessing validity. Most of the analytic plans for egocentric studies were limited to information at the individual level rather than that at the ego-alter ties. The project reported in manuscripts 2 and 3 used empirical data from a multi-center egocentric network study among mid-age FSWs in China to assess the extent to which social network components influence HIV testing behaviors (paper 2), and the associations between Chinese collectivist culture and FSWs’ social networks (paper 3). As reported in the manuscript 2, among 1,245 FSWs, 62.2% of them received an HIV test. HIV testing was positively associated with higher network transitivity (AOR: 1.77; 95% CI: 1.18-2.64) and inversely associated with network trust (AOR: 0.74; 95% CI: 0.56-0.97). Although social support was not associated with HIV testing, the increase in social cohesion may provide substantial support for HIV testing. As documented in manuscript 3, Chinese collectivism tendency was negatively associated with their perceived social support (95% CI: -0.33, -0.04), network effective size (95% CI: -0.30, -0.01), and network betweenness (95% CI: -0.33, -0.09). FSWs who had the highest level of collectivistic tendency and perceived a higher level of stigma are more likely to stay at a “bridging” position and connect with weak social ties rather than a strong cohesive group. This dissertation projects provide empirical evidence that social networks can be used to analyze the social environment of FSWs and its impact on HIV preventive behaviors among this HIV vulnerable population. The findings make additional contributions to the application of social network methods in social and behavioral research with a focus on FSWs.Item EMERGENCE OF PRIVATE SECTOR IN PUBLIC-PRIVATE PARTNERSHIP PROJECTS AND ANALYSIS OF RELATIONSHIP BETWEEN STAKEHOLDER NETWORK CENTRALITY AND PROJECT PERFORMANCE(2019) Suwal, Sirish; Cui, Qingbin; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Infrastructure and construction projects are large, complex, and arduous ventures involving various actors or stakeholders. However, taking decisions based on the individual attributes of stakeholders is insufficient. The emergence of the private sector in Public-Private Partnership (PPP) projects reveal the need to consider how multiple stakeholders in an inter-reliant network can impact the project’s performance. This research uses stakeholder and social network theories, and analyzes the centrality measures – total-degree, betweenness, closeness – of the key public and private entities against two project performance criteria: cost and schedule. Findings reveal that private sector becomes significantly more central in PPP projects, and there is a statistically significant correlation between private sector centrality measures and project schedule performance. In addition, the research reveals that the number of public agencies or sponsors involved in the project also plays a significant role in determining project performanceItem INVESTIGATING HOW INDIVIDUAL SCHOOL INTERNAL SOCIAL NETWORKS CONTRIBUTE TO THE COMMUNICATION OF SYSTEMIC INITIATIVES IN A LARGE URBAN SCHOOL DISTRICT(2015) Kochanowski, Melissa Lynn; McLaughlin, Margaret J.; Education Policy, and Leadership; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Implementation of initiatives and mandates in schools and districts has increased over the last decade and districts are constantly tasked with disseminating new information to staff in the schools. Recently studies have been conducted in the field of education using Social Network Analysis (SNA) to explore how information and knowledge flow between people in schools and districts in order to identify key disseminators, brokers, and hinders of information, as well as the overall patterns of communication. The purpose of this study was to examine the informal communication networks and key actors used to disseminate information about the Common Core State Standards (CCSS) in four elementary schools in a large urban school district. The study was based on the premise that obtaining a better understanding of the informal communication pathways in these schools would allow school and district leaders to better understand how information flows throughout schools and to determine whether the positions intended to communicate new information in a school were actually being used. This exploratory study used an online survey and SNA to identify the flow of and key actors for communication around two initiatives, CCSS and Data Wise. The findings suggest that each of the four schools had highly centralized networks where only a few key staff members were integral for sharing information about initiatives. The key people in each school tended to be administrators and individuals who held two positions. One of the key positions in each school was the Professional Development Lead Teacher (PDLT), which is the position the District had created to ensure information about key initiatives was disseminated.Item Declarative Cleaning, Analysis, and Querying of Graph-structured Data(2013) Moustafa, Walaa Eldin; Deshpande, Amol; Getoor, Lise; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Much of today's data including social, biological, sensor, computer, and transportation network data is naturally modeled and represented by graphs. Typically, data describing these networks is observational, and thus noisy and incomplete. Therefore, methods for efficiently managing graph-structured data of this nature are needed, especially with the abundance and increasing sizes of such data. In my dissertation, I develop declarative methods to perform cleaning, analysis and querying of graph-structured data efficiently. For declarative cleaning of graph-structured data, I identify a set of primitives to support the extraction and inference of the underlying true network from observational data, and describe a framework that enables a network analyst to easily implement and combine new extraction and cleaning techniques. The task specification language is based on Datalog with a set of extensions designed to enable different graph cleaning primitives. For declarative analysis, I introduce 'ego-centric pattern census queries', a new type of graph analysis query that supports searching for structural patterns in every node's neighborhood and reporting their counts for further analysis. I define an SQL-based declarative language to support this class of queries, and develop a series of efficient query evaluation algorithms for it. Finally, I present an approach for querying large uncertain graphs that supports reasoning about uncertainty of node attributes, uncertainty of edge existence, and a new type of uncertainty, called identity linkage uncertainty, where a group of nodes can potentially refer to the same real-world entity. I define a probabilistic graph model to capture all these types of uncertainties, and to resolve identity linkage merges. I propose 'context-aware path indexing' and 'join-candidate reduction' methods to efficiently enable subgraph matching queries over large uncertain graphs of this type.Item Ekphrastic Revisions: Verbal-Visual Networks in 20th Century Poetry by Women(2012) Rhody, Lisa Marie Antonille; Loizeaux, Elizabeth B; English Language and Literature; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This study considers contemporary ekphrastic poetry--poems to, for, and about visual art--particularly by female poets in the U.S. and theorizes a broader, more complex model of how the genre operates. I suggest a network model that attends to the multiple, simultaneous, and often dynamic relationships inherent in verbalizing the visual arts, where historically inter-aesthetic relations have been understood as an act of transgression and a desire to subsume a representational "other." Continuing to explore ekphrasis as a socially-inscribed encounter, as critics have since W.J.T Mitchell's field-defining essay "Ekphrasis and the Other," I recast the definition of ekphrasis as an elaborate network of relationships not only between poems, images, and readers, but also literary traditions, social contexts, individual artists, related works of art, textual conditions, and historical events. This expanded conception of networked ekphrasis allows for a nuanced understanding of the relationships between the arts, where speaking for another, as ekphrastic verse does for visual art, is more than an act of gendered contest, but can be a recovery against historical erasure, as with Elizabeth Alexander's "The Venus Hottentot," an act of empathetic collusion, as in the verse of Lisel Mueller, or the deliberate decentering of poetic authority, as in Elizabeth Bishop's "The Map" and "The Monument." Thus, I position the ekphrastic network as a site of social discourse where the spectrum of possible outcomes between poetry and images is broader and more complex than accounted for in previous theorizations. "Ekphrastic Revisions" presents methodological opportunities for scholars interested in reshaping the genre's tradition. Where Part I introduces the tradition and genre of ekphrasis through methods of close readings alongside textual, biographical, and archival studies, Part II introduces a digital humanities project called "Revising Ekphrasis," which establishes best practices for using LDA topic modeling and social network analysis to read the ekphrastic genre at scale using a curated dataset of more than 4700 poems. In using tools available to the digital humanities, I take into consideration the range of possible questions that can be asked best through close and distant reading in order to revise the ekphrastic tradition.Item An Agent-Based Modeling Approach to Reducing Pathogenic Transmission in Medical Facilities and Community Populations(2012) Barnes, Sean; Golden, Bruce; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The spread of infectious diseases is a significant and ongoing problem in human populations. In hospitals, the cost of patients acquiring infections causes many downstream effects, including longer lengths of stay for patients, higher costs, and unexpected fatalities. Outbreaks in community populations cause more significant problems because they stress the medical facilities that need to accommodate large numbers of infected patients, and they can lead to the closing of schools and businesses. In addition, epidemics often require logistical considerations such as where to locate clinics or how to optimize the distribution of vaccinations and food supplies. Traditionally, mathematical modeling is used to explore transmission dynamics and evaluate potential infection control measures. This methodology, although simple to implement and computationally efficient, has several shortcomings that prevent it from adequately representing some of the most critical aspects of disease transmission. Specifically, mathematical modeling can only represent groups of individuals in a homogenous manner and cannot model how transmission is affected by the behavior of individuals and the structure of their interactions. Agent-based modeling and social network analysis are two increasingly popular methods that are well-suited to modeling the spread of infectious diseases. Together, they can be used to model individuals with unique characteristics, behavior, and levels of interaction with other individuals. These advantages enable a more realistic representation of transmission dynamics and a much greater ability to provide insight to questions of interest for infection control practitioners. This dissertation presents several agent-based models and network models of the transmission of infectious diseases at scales ranging from hospitals to networks of medical facilities and community populations. By employing these methods, we can explore how the behavior of individual healthcare workers and the structure of a network of patients or healthcare facilities can affect the rate and extent of hospital-acquired infections. After the transmission dynamics are properly characterized, we can then attempt to differentiate between different types of transmission and assess the effectiveness of infection control measures.