Theses and Dissertations from UMD
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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
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Item Semantic integration of geospatial concepts - a study on land use land cover classification systems(2011) Wei, Hua; Townshend, John; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In GI Science, one of the most important interoperability is needed in land use and land cover (LULC) data, because it is key to the evaluation of LULC's many environmental impacts throughout the globe (Foley et al. 2005). Accordingly, this research aims to address the interoperability of LULC information derived by different authorities using different classificatory approaches. LULC data are described by LULC classification systems. The interoperability of LULC data hinges on the semantic integration of LULC classification systems. Existing works on semantically integrating LULC classification systems has a major drawback in finding comparable semantic representations from textual descriptions. To tackle this problem, we borrowed the method of comparing documents in information retrieval, and applied it to comparing LULC category names and descriptions. The results showed significant improvement comparing to previous works. However, lexical semantic methods are not able to solve the semantic heterogeneities in LULC classification systems: the confounding conflict - LULC categories under similar labels and descriptions have different LULC status in reality, and the naming conflict - LULC categories under different labels represent similar LULC type. Without confirmation of their actual land cover status from remote sensing, lexical semantic method cannot achieve reliable matching. To discover confounding conflicts and reconcile naming conflicts, we developed an innovative method of applying remote sensing to the integration of LULC classification systems. Remote sensing is a means of observation on actual LULC status of individual parcels. We calculated parcel level statistics from spectral and textural data, and used these statistics to calculate category similarity. The matching results showed this approach fulfilled its goal - to overcome semantic heterogeneities and achieve more reliable and accurate matching between LULC classifications in the majority of cases. To overcome the limitations of either method, we combined the two by aggregating their output similarities, and achieve better integration. LULC categories that post noticeable differences between lexical semantics and remote sensing once again remind us of semantic heterogeneities in LULC classification systems that must to be overcome before LULC data from different sources become interoperable and serve as the key to understanding our highly interrelated Earth system.Item MULTIDIMENSIONALITY IN THE NAEP SCIENCE ASSESSMENT:SUBSTANTIVE PERSPECTIVES, PSYCHOMETRIC MODELS, AND TASK DESIGN(2008-03-05) Wei, Hua; Mislevy, Robert J; Measurement, Statistics and Evaluation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Educational assessments are characterized by the interplay among substantive theories, task design, and measurement models. Substantive theories define the nature of inferences to be made about students and types of observations that lend support to the targeted inferences. Task design represents the schemes for the design of tasks and extraction of evidence from student behaviors in the task situations. Measurement models are the tools by which observations of students' performances are synthesized to derive the targeted inferences. This dissertation elaborates on the interplay by specifying the entities that are involved and how they work in concert to produce an effective assessment and sound inferences. Developments in several areas are contributing to interest in more complex educational assessments: Advances in cognitive psychology spark interest in more complex inferences about students' knowledge, advances in technology make it possible to collect richer performance data, and advances in statistical methods make fitting more complex models feasible. The question becomes how to construct and analyze assessments to take advantage of this potential. In particular, a framework is required for understanding how to think about selecting and reasoning through the multivariate measurement models that are now available. Illustrations of the idea are made through explicating and analyzing the 1996 National Assessment of Educational Progress (NAEP) Science Assessment. Three measurement models, each of which reflects a particular perspective for thinking about the structure of the assessment, are used to model the item responses. Each model sheds light on a particular aspect of student proficiencies, addresses certain inferences for a particular purpose, and delivers a significant story about the examinees and their learning of science. Each model highlights certain patterns at the expense of hiding other potentially interesting patterns that reside in the data. Model comparison is conducted in terms of conceptual significance and degree of fit. The two criteria are used in complement to check the coherence of the data with the substantive theories underlying the use of the models.