ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Description
This qualitative, action research study examines how teacher-writers' identities are constructed through the practice of revision in an extra-curriculum writing group. The writing group was designed to support the teacher-writers as they revised classroom research projects for submission for a scholarly journal. Using discourse analysis, the researcher explores how the teacher-writers' identities are constructed in the contested spaces of revision. This exploration focuses on contested issues that invariably emerge in a dynamic binary of reader/writer, issues of authority, ownership, and unstable reader and writer identities. By negotiating these contested spaces--these contact zones--the teacher-writers construct opportunities to flex their rhetorical agency. Through rhetorical agency, the teacher-writers shift their discoursal identities by discarding and acquiring a variety of discourses. As a result, the practice of revision constructs the teacher-writers identities as hybrid, as consisting of self and other.
ContributorsClark-Oates, Angela (Author) / Smith, Karen (Thesis advisor) / Roen, Duane (Thesis advisor) / Fischman, Gustavo (Committee member) / Early, Jessica (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
A simple passion for reading compels many to enter the university literature classroom. What happens once they arrive may fuel that passion, or possibly destroy it. A romanticized relationship with literature proves to be an obstacle that hinders a deeper and richer engagement with texts. Primary research consisting of personal interviews, observations, and surveys, form the source of data for this dissertation project which was designed to examine how literature teachers engage their students with texts, discussion, and assignments in the university setting. Traditionally text centered and resolute, literature courses will need refashioning if they are to advance beyond erstwhile conventions. The goal of this study is to create space for a dialogue about the need for a pedagogy of literature.
ContributorsSanchez, Shillana (Author) / Goggin, Maureen (Thesis advisor) / Tobin, Beth (Thesis advisor) / Rose, Shirley (Committee member) / Arizona State University (Publisher)
Created2013
Description
This work presents two complementary studies that propose heuristic methods to capture characteristics of data using the ensemble learning method of random forest. The first study is motivated by the problem in education of determining teacher effectiveness in student achievement. Value-added models (VAMs), constructed as linear mixed models, use students’ test scores as outcome variables and teachers’ contributions as random effects to ascribe changes in student performance to the teachers who have taught them. The VAMs teacher score is the empirical best linear unbiased predictor (EBLUP). This approach is limited by the adequacy of the assumed model specification with respect to the unknown underlying model. In that regard, this study proposes alternative ways to rank teacher effects that are not dependent on a given model by introducing two variable importance measures (VIMs), the node-proportion and the covariate-proportion. These VIMs are novel because they take into account the final configuration of the terminal nodes in the constitutive trees in a random forest. In a simulation study, under a variety of conditions, true rankings of teacher effects are compared with estimated rankings obtained using three sources: the newly proposed VIMs, existing VIMs, and EBLUPs from the assumed linear model specification. The newly proposed VIMs outperform all others in various scenarios where the model was misspecified. The second study develops two novel interaction measures. These measures could be used within but are not restricted to the VAM framework. The distribution-based measure is constructed to identify interactions in a general setting where a model specification is not assumed in advance. In turn, the mean-based measure is built to estimate interactions when the model specification is assumed to be linear. Both measures are unique in their construction; they take into account not only the outcome values, but also the internal structure of the trees in a random forest. In a separate simulation study, under a variety of conditions, the proposed measures are found to identify and estimate second-order interactions.
ContributorsValdivia, Arturo (Author) / Eubank, Randall (Thesis advisor) / Young, Dennis (Committee member) / Reiser, Mark R. (Committee member) / Kao, Ming-Hung (Committee member) / Broatch, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study compares some sites, structures, theories and praxis of transnational feminisms in India and the U.S., simultaneously guided by and interrogating contemporary academic feminist theoretical and methodological trends. The goal is twofold: to understand similarities and differences in feminist praxis of two geo-epistemological spaces; and to interrogate the notion and currency of the "transnational" within feminist knowledge-creation. The phenomenon of transnational feminist knowledge-making is interrogated from a philosophical/theoretical and phenomenological/experiential standpoint. The philosophical inquiry is concentrated on the theoretical texts produced on transnational/global/postcolonial feminisms. This inquiry also focuses on some unpublished, uncirculated archival materials that trace the history of academic feminisms and their transnationalization. The phenomenological side focuses on interview and survey data on transnational feminism, gathered from feminist practitioners working in the U.S. and India, as well as being "transmigrant," or "traveling scholars." Digital/institutional ethnography is used to ground the findings in operational spaces of knowledge-making, including cyberspace. This research shows that the global logic of circulation and visibility organize the flow of knowledge as data, narratives and reports from the global south, which are analyzed, clarified and theorized in the global north. Perhaps responding to many critiques on "speaking of" and "speaking for" the "other," the trend to represent third world women as perpetual victims has given way to newer representations and accounts of resistance, collaboration, and activism. However, this creates a fresh "theory-here-activism-there" model of transnational feminism that preserves unequal feminist division of labor. This comparative and critical study focuses not just on feminist discourses in two countries but also their relationships, suggests some viable models of transnational feminism that can preserve epistemic justice, and aims to contribute to the theoretical corpus of transnational feminism.
ContributorsChakravarty, Debjani (Author) / Kitch, Sally L (Thesis advisor) / Fonow, Mary M (Committee member) / Koblitz, Ann H (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation provides a critical analysis of public administration's understanding of the relationship between rational thought and action in its discourse on ethics. It argues that rationalist ethics assume a particular relationship between thought and action: that good knowledge leads to good, proper action. While there have been many critiques of rationalist administrative ethics, scholars have not examined the way in which rationalism persists in the way in which the teaching of ethics is conducted. The use of the case study figures prominently in this. Thus, the dissertation explores the historical and theoretical intersection of rationalism, ethics, and teaching through the lens of the case study. It begins with a history of the pedagogical use of the case study and the institutional transformations of the university. While conventional accounts of the field locate its founding in the United States in the municipal reform movement, here the founding of the field of public administration is recast through connections to reforms in the university including changes in epistemic assumptions, pedagogical methods, and curricular changes in ethics in which the case study is central and remains so as the field develops. The dissertation then considers scholarship in public administration that raises questions about rationalist ethics. Three critical approaches are explored: recognition of the uncertainty and complexity of administrative practice, critique as unmasking of power relationships, and the shift of ethics from an epistemological to an ontological inquiry. The dissertation builds on the work in this third approach and shows how it attempts to articulate a non-rationalist, or immanent, ethics. This ethics is concerned with exploring the conditions that make possible mutually beneficial relationships and meaningful lives from which categorical norms of the good life could emerge. Drawing on the philosophy of Gilles Deleuze and Felix Guattari, it is argued that the distinction Deleuze and Guattari make between "arborescent" and "rhizomatic" knowledge gets to the root of the tension between thought and action and offers an innovative and useful way to advance an immanent, non-rational ethics. The challenge digital technologies and the information society present to the field is considered to illustrate the need to rethink administrative ethics and also the particular usefulness of Deleuze and Guattari in doing so. The dissertation concludes with a discussion of pedagogical practices and classroom examples that encourage a rhizomatic understanding of the theory and practice of public administration.
ContributorsCallen, Jeffrey Craig (Author) / Catlaw, Thomas J (Thesis advisor) / Corley, Elizabeth (Committee member) / Kim, Yushim (Committee member) / Arizona State University (Publisher)
Created2013
Description
Image understanding has been playing an increasingly crucial role in vision applications. Sparse models form an important component in image understanding, since the statistics of natural images reveal the presence of sparse structure. Sparse methods lead to parsimonious models, in addition to being efficient for large scale learning. In sparse modeling, data is represented as a sparse linear combination of atoms from a "dictionary" matrix. This dissertation focuses on understanding different aspects of sparse learning, thereby enhancing the use of sparse methods by incorporating tools from machine learning. With the growing need to adapt models for large scale data, it is important to design dictionaries that can model the entire data space and not just the samples considered. By exploiting the relation of dictionary learning to 1-D subspace clustering, a multilevel dictionary learning algorithm is developed, and it is shown to outperform conventional sparse models in compressed recovery, and image denoising. Theoretical aspects of learning such as algorithmic stability and generalization are considered, and ensemble learning is incorporated for effective large scale learning. In addition to building strategies for efficiently implementing 1-D subspace clustering, a discriminative clustering approach is designed to estimate the unknown mixing process in blind source separation. By exploiting the non-linear relation between the image descriptors, and allowing the use of multiple features, sparse methods can be made more effective in recognition problems. The idea of multiple kernel sparse representations is developed, and algorithms for learning dictionaries in the feature space are presented. Using object recognition experiments on standard datasets it is shown that the proposed approaches outperform other sparse coding-based recognition frameworks. Furthermore, a segmentation technique based on multiple kernel sparse representations is developed, and successfully applied for automated brain tumor identification. Using sparse codes to define the relation between data samples can lead to a more robust graph embedding for unsupervised clustering. By performing discriminative embedding using sparse coding-based graphs, an algorithm for measuring the glomerular number in kidney MRI images is developed. Finally, approaches to build dictionaries for local sparse coding of image descriptors are presented, and applied to object recognition and image retrieval.
ContributorsJayaraman Thiagarajan, Jayaraman (Author) / Spanias, Andreas (Thesis advisor) / Frakes, David (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
The teaching of singing remained remarkably stable until, at the end of the twentieth century, advances in the understanding of voice science stimulated dramatic changes in approach to vocal pedagogy. Previously, the technology needed to accurately measure physiologic change within the larynx and breath-support musculature during the process of singing simply did not exist. Any prior application of scientific study to the voice was based primarily upon auditory evaluation, rather than objective data accumulation and assessment. After a centuries-long history, within a span of twenty years, vocal pedagogy evolved from an approach solely derived from subjective, auditory evidence to an application grounded in scientific data. By means of analysis of significant publications by Richard Miller, Robert Sataloff, and Ingo Titze, as well as articles from The Journal of Singing and The Journal of Voice, I establish a baseline of scientific knowledge and pedagogic practice ca. 1980. Analysis and comparison of a timeline of advancement in scientific insight and the discussion of science in pedagogical texts, 1980-2000, reveal the extent to which voice teachers have dramatically changed their method of instruction. I posit that voice pedagogy has undergone a fundamental change, from telling the student only what to do, via auditory demonstration and visual imagery, to validating with scientific data how and why students should change their vocal approach. The consequence of this dramatic pedagogic evolution has produced singers who comprehend more fully the science of their art.
ContributorsVelarde, Rachel (Author) / Doan, Jerry (Thesis advisor) / Campbell, Andrew (Committee member) / Solis, Theodore (Committee member) / Elgar Kopta, Anne (Committee member) / Britton, David (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study examines the multiple and complicated ways that Native American students engage, accept, and/or reject the teachings of a Native American literature course, as they navigate complex cultural landscapes in a state that has banned the teaching of ethnic studies. This is the only classroom of its kind in this major metropolitan area, despite a large Native American population. Like many other marginalized youth, these students move through "borderlands" on a daily basis from reservation to city and back again; from classrooms that validate their knowledges to those that deny, invalidate and silence their knowledges, histories and identities. I am examining how their knowledges are shared or denied in these spaces. Using ethnographic, participatory action and grounded research methods, and drawing from Safety Zone Theory (Lomawaima and McCarty, 2006) and Bakhtin's (1981) dialogism, I focus on students' counter-storytelling to discover how they are generating meanings from a curriculum that focuses on the comprehension of their complicated and often times contradicting realities. This study discusses the need for schools to draw upon students' cultural knowledges and offers implications for developing and implementing a socio-culturally sustaining curriculum.
ContributorsSan Pedro, Timothy Jose (Author) / Paris, Django (Thesis advisor) / Romero-Little, Mary Eunice (Thesis advisor) / Mccarty, Teresa (Committee member) / Ortiz, Simon (Committee member) / Chin, Beverly A (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the increase in computing power and availability of data, there has never been a greater need to understand data and make decisions from it. Traditional statistical techniques may not be adequate to handle the size of today's data or the complexities of the information hidden within the data. Thus knowledge discovery by machine learning techniques is necessary if we want to better understand information from data. In this dissertation, we explore the topics of asymmetric loss and asymmetric data in machine learning and propose new algorithms as solutions to some of the problems in these topics. We also studied variable selection of matched data sets and proposed a solution when there is non-linearity in the matched data. The research is divided into three parts. The first part addresses the problem of asymmetric loss. A proposed asymmetric support vector machine (aSVM) is used to predict specific classes with high accuracy. aSVM was shown to produce higher precision than a regular SVM. The second part addresses asymmetric data sets where variables are only predictive for a subset of the predictor classes. Asymmetric Random Forest (ARF) was proposed to detect these kinds of variables. The third part explores variable selection for matched data sets. Matched Random Forest (MRF) was proposed to find variables that are able to distinguish case and control without the restrictions that exists in linear models. MRF detects variables that are able to distinguish case and control even in the presence of interaction and qualitative variables.
ContributorsKoh, Derek (Author) / Runger, George C. (Thesis advisor) / Wu, Tong (Committee member) / Pan, Rong (Committee member) / Cesta, John (Committee member) / Arizona State University (Publisher)
Created2013