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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Item Parent- and Teacher-Rated Social Skills and Theory of Mind in Kindergarteners(2018) Caputo, Maryke Haasbroek; Teglasi, Hedwig; Counseling and Personnel Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This study investigated how kindergartners’ use of Theory of Mind (ToM; understanding and inferring others’ mental states to predict and explain behavior) relate to their Social Competence (SC), as rated by parents and teachers. This study aimed to determine whether social skills items could be classified as more or less conventional (knowledge of emotions and social conventions) or intentional (requires noticing and interpreting other’s beliefs and intentions) based on their correlates with more or less structured performance measures of ToM, respectively. Results partially supported this this distinction. Patterns suggested that parents and teachers judge children’s social skills differently. This study also explored relations of language with SC and ToM. Language accounted for much of the variance in the more structured ToM task and teacher-rated social skills, but not the less structured ToM task or parent-rated social skills. Implications for SC conceptualization and scale construction and interpretation are discussed.Item Continuous, Effort-Aware Prediction of Software Security Defects(2015) Stuckman, Jeffrey Charles; Purtilo, James; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Software security defects are coding flaws which allow for a system's security to be compromised. Due to the potential severity of these defects, it is important to discover them quickly; therefore, they are a good focus for software quality improvement efforts such as code inspection. Our research focuses on vulnerability prediction models, which use machine learning to identify code that has an elevated likelihood of containing these defects. In particular, we study continuous prediction models, which repeatedly search for vulnerable code over a period of time, rather than being used at just one particular moment. To empirically evaluate the prediction methodologies that we define, we collected a fine-grained dataset of vulnerabilities in PHP applications. We then defined and implemented a method for defining families of features, or metrics, which characterize both the change in code over time and the state of the code at a given moment, enabling a systematic and fair comparison of continuous and traditional prediction models. We also introduce a methodology for effort-sensitive learning, which optimizes to minimize the expected cost of inspecting the code that is ultimately flagged by the model. Our results show that the security defects in our dataset were long-lived, with a median lifetime of 871 days. Continuous prediction more readily discriminated vulnerable from non-vulnerable code than traditional static prediction did, and prediction was more efficient when changes were broken apart by file than when they were aggregated together. However, high code churn negated some of the efficiency gains of continuous predictors in simulations, and the optimal prediction method in a given scenario depended on making a tradeoff between speed of detection and cost savings. As an additional contribution, we have released the fine-grained defect dataset -- the first of its kind -- to the public, in order to encourage future work in this field.Item A COMPARISON OF EX-ANTE, LABORATORY, AND FIELD METHODS FOR EVALUATING SURVEY QUESTIONS(2014) Maitland, Aaron; Presser, Stanley; Survey Methodology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A diverse range of evaluation methods is available for detecting measurement error in survey questions. Ex-ante question evaluation methods are relatively inexpensive, because they do not require data collection from survey respondents. Other methods require data collection from respondents either in the laboratory or in the field setting. Research has explored how effective some of these methods are at identifying problems with respect to one another. However, a weakness of most of these studies is that they do not compare the range of question evaluation methods that are currently available to researchers. The purpose of this dissertation is to understand how the methods researchers use to evaluate survey questions influence the conclusions they draw about the questions. In addition, the dissertation seeks to identify more effective ways to use the methods together. It consists of three studies. The first study examines the extent of agreement between ex-ante and laboratory methods in identifying problems and compares the methods in how well they predict differences between questions whose validity has been estimated in record-check studies. The second study evaluates the extent to which ex-ante and laboratory methods predict the performance of questions in the field as measured by indirect assessments of data quality such as behavior coding, response latency and item nonresponse. The third study evaluates the extent to which ex-ante, laboratory, and field methods predict the reliability of answers to survey questions as measured by stability over time. The findings suggest (1) that a multiple method approach to question evaluation is the best strategy given differences in the ability to detect different types of problems between the methods and (2) how to combine methods more effectively in the future.Item Analyzing the Wikisphere: Tools and Methods for Wiki Research(2010) Stuckman, Jeffrey Charles; Purtilo, James; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)We present tools and techniques that facilitate wiki research and an analysis of wikis found on the internet. We developed WikiCrawler, a tool that downloads and analyzes wikis. With this tool, we built a corpus of 151 Mediawiki wikis. We also developed a wiki analysis toolkit in R, which, among other tasks, fits probability distributions to discrete data, and uses a Monte Carlo method to test the fit. From the corpus we determined that, like Wikipedia, most wikis were authored collaboratively, but users contributed at unequal rates. We proposed a distribution-based method for measuring wiki inequality and compared it to the Gini coefficient. We also analyzed distributions of edits across pages and users, producing data which can motivate or verify future mathematical models of behavior on wikis. Future research could also analyze user behavior and establish measurement baselines, facilitating evaluation, or generalize Wikipedia research by testing hypotheses across many wikis.Item A STUDY OF OPTICAL, PHYSICAL AND CHEMICAL PROPERTIES OF AEROSOLS USING IN SITU MEASUREMENTS(2009) Chaudhry, Zahra; Li, Zhanqing; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Using a simple sampling apparatus, aerosol particles were collected on a polycarbonate substrate in various locations around the world. The focus of this study was Xianghe, China, an industrial town 70 km southeast of Beijing. The Nuclepore filters were collected in two size ranges (coarse, 2.5μm < d < 10μm, and fine, d < 2.5μm) from January-December 2005, with a focus on the Intensive Observation Campaign (IOC) in March 2005. The collected filters were analyzed for aerosol mass concentration and aerosol absorption efficiency; selected filters were analyzed for chemical composition. For fine mode aerosols measured during the Xianghe 2005 IOC, the average spectral absorption efficiency equates well to a &lamda;-1 model, while the coarse mode shows a much flatter spectral dependence, consistent with large particle models. The coarse mode absorption efficiency was compatible with that of the fine mode in the near-IR region, indicating the much stronger absorption of the coarse mode due to its composition and sizeable mass. Ground-based measurements were compared to remote sensing instruments that measure similar parameters for the total column. A co-located lidar assisted in determination of vertical homogeneity. For cases of vertical homogeneity, the ground-based measurements were able to represent total column measurements well. For cases of vertical inhomogeneity, ground-based measurements did not equate well to total column measurements. The layers of aerosols that form in the atmosphere have significant effects on the temperature profile. An instrument was developed to measure aerosol absorption and scattering, the Scattering and Absorption Sonde (SAS). This instrument was launched seven times at two locations in China in 2008. Vertical profiles of scattering coefficient were measured and several aerosol layers were identified. The aerosol characterized at Xianghe, China was compared to aerosol characteristics from Kanpur, India and Mexico City, Mexico. The aerosol at Mexico City differs greatly from that at Xianghe, based on the measured mass concentration, aerosol size distribution from AERONET, and measured aerosol absorption efficiency. The aerosol at Kanpur resembles well the aerosol characterized at Xianghe in the fine mode, with a correlation of 0.998 for the aerosol absorption efficiency.Item Measuring Wishful Thinking: The Development and Validation of a New Scale(2007-06-05) Eichelberger, Angela H; Sigall, Harold; Psychology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation describes the development and validation of a 10-item scale measuring individual differences in wishful thinking, or the degree to which individuals' desires bias their judgments. A study was conducted to investigate the new scale's psychometric properties, as well as its relationships with other self-report measures. The wishful thinking measure demonstrated convergent validity with other measures of bias, including self-deceptive enhancement, belief in a just world, and social desirability. Wishful thinking showed discriminant validity with several dimensions of problem-focused coping. Wishful thinking was related to optimism and greater use of positive reinterpretation and growth, an emotion-focused coping response. Next, the new measure was used to distinguish optimists who were wishful thinkers from those who were realistic. An experimental study was conducted to investigate hypothesized differences between wishful thinkers and realistic optimists. In this study, participants were asked to make judgments about their future performance. When success at the task was important to wishful thinkers, they judged success as more likely than when success was not important to them. Realistic optimists did not vary their judgments as a function of importance. The optimal margin of illusion hypothesis was not supported; extreme levels of optimism and wishful thinking were not associated with overconfidence and poor performance. Potential uses of the wishful thinking measure for future research are discussed.