Theses and Dissertations from UMD
Permanent URI for this communityhttp://hdl.handle.net/1903/2
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 give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item A META-DATA INFORMED EXPERT JUDGMENT AGGREGATION AND CALIBRATION TECHNIQUE(2016) Feldman, Ellis; Mosleh, Ali; Reliability Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Policy makers use expert judgment opinions elicited from experts as probability distributions, quantiles or point estimates, as inputs to decisions that may have economic or life and death impacts. While challenges in estimating probabilities in general have been studied, research that distinguished between non-probabilistic, i.e., physical, variables and probabilistic variables specifically in the context of meta-data based expert judgment aggregation techniques, and the errors associated with the predictions developed from such variables, was not identified. This research demonstrated that for two combined expert judgment meta-data bases, the distinction between physical and probabilistic variables was significant in terms of the extent of multiplicative error between elicited medians and realized values both before and after aggregation. The distinction also impacts the widths of bounds around aggregated point estimates. The research compared nine methods of aggregating estimates and obtaining calibrated bounds, including ones based on alpha stable distributions, quantile regression, and a Bayesian model. Simple parametric distributions were also fit to the meta-data. Methods were compared against criteria including accuracy, bounds coverage and width, sensitivity to outliers, and complexity. No single method dominated all criteria for either variable type. The research investigated sensitivity of results to level of realized value for a variable, such as infrequent events for probabilistic variables, as well as sensitivity of results to number of experts.Item A COMPARISON OF THE EXPERTISE OF UNIVERSITY FACULTY AND STUDENTS IN AMERICAN POLITICAL SCIENCE: IMPLICATIONS FOR FUTURE RESEARCH ON HIGH SCHOOL CIVICS AND GOVERNMENT(2012) Budano, Christopher; Monte-Sano, Chauncey; Curriculum and Instruction; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This study investigated the disciplinary knowledge and nature of expertise among political science experts studying American political science. A comparison group of students who had completed an introductory undergraduate course in American political science also participated in the study. Numerous research studies have found that civics and government courses often focus on the transmission of information from textbooks and teachers to students. The result of this type of teaching, at least according to the measures we currently utilize, has been the failure of the majority of students to learn about American government, become invested in our system of government, and indicate their desire to participate in the future. Civic and educational leaders have called for the development of curriculum to promote critical thinking and improve student learning and participation. Yet, there is no research base for understanding what critical thinking looks like in civics and government and its related discipline of political science or what activities and methods will lead to increased student achievement. With history education as a model, where defining the discipline has led to a better understanding of critical thinking in history and a more robust approach to teaching, the author investigated what expertise in this subfield of political science looks like, how experts conceptualize the discipline, and what cognitive processes they use in their work using a concept sorting and mapping task, two problem-solving tasks, and an open-ended interview. Experts defined political science as an empirical discipline focused on phenomena related to government, power, and the allocation of resources. Experts also recognized relationships and connections between concepts in the discipline and used a variety of conceptual knowledge and strategic processing when engaging in their work, including recognition of context, the identification of sub-problems and constraints, and an acknowledgement of what they did not know. A comparison to the students allowed for the description of different levels of expertise. Implications of the study include the need for additional research on the strategic processing of political science experts and the potential to define educational outcomes for teaching and learning in civics and government classes.