Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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Description
Researchers across a variety of fields are often interested in determining if data are of a random nature or if they exhibit patterning which may be the result of some alternative and potentially more interesting process. This dissertation explores a family of statistical methods, i.e. space-time interaction tests, designed to detect structure within three-dimensional event data. These tests, widely employed in the fields of spatial epidemiology, criminology, ecology and beyond, are used to identify synergistic interaction across the spatial and temporal dimensions of a series of events. Exploration is needed to better understand these methods and determine how their results may be affected by data quality problems commonly encountered in their implementation; specifically, how inaccuracy and/or uncertainty in the input data analyzed by the methods may impact subsequent results. Additionally, known shortcomings of the methods must be ameliorated. The contributions of this dissertation are twofold: it develops a more complete understanding of how input data quality problems impact the results of a number of global and local tests of space-time interaction and it formulates an improved version of one global test which accounts for the previously identified problem of population shift bias. A series of simulation experiments reveal the global tests of space-time interaction explored here to be dramatically affected by the aforementioned deficiencies in the quality of the input data. It is shown that in some cases, a conservative degree of these common data problems can completely obscure evidence of space-time interaction and in others create it where it does not exist. Conversely, a local metric of space-time interaction examined here demonstrates a surprising robustness in the face of these same deficiencies. This local metric is revealed to be only minimally affected by the inaccuracies and incompleteness introduced in these experiments. Finally, enhancements to one of the global tests are presented which solve the problem of population shift bias associated with the test and better contextualize and visualize its results, thereby enhancing its utility for practitioners.
ContributorsMalizia, Nicholas (Author) / Anselin, Luc (Thesis advisor) / Murray, Alan (Committee member) / Rey, Sergio (Committee member) / Arizona State University (Publisher)
Created2013
Description
The objective of this dissertation is to empirically analyze the results of the retail location decision making process and how chain networks evolve given their value platform. It employs one of the largest cross-sectional databases of retailers ever assembled, including 50 US retail chains and over 70,000 store locations. Three closely related articles, which develop new theory explaining location deployment and behaviors of retailers, are presented. The first article, "Regionalism in US Retailing," presents a comprehensive spatial analysis of the domestic patterns of retailers. Geographic Information Systems (GIS) and statistics examine the degree to which the chains are deployed regionally versus nationally. Regional bias is found to be associated with store counts, small market deployment, and the location of the founding store, but not the age of the chain. Chains that started in smaller markets deploy more stores in other small markets and vice versa for chains that started in larger markets. The second article, "The Location Types of US Retailers," is an inductive analysis of the types of locations chosen by the retailers. Retail locations are classified into types using cluster analysis on situational and trade area data at the geographical scale of the individual stores. A total of twelve distinct location types were identified. A second cluster analysis groups together the chains with the most similar location profiles. Retailers within the same retail business often chose similar types of locations and were placed in the same clusters. Retailers generally restrict their deployment to one of three overall strategies including metropolitan, large retail areas, or market size variety. The third article, "Modeling Retail Chain Expansion and Maturity through Wave Analysis: Theory and Application to Walmart and Target," presents a theory of retail chain expansion and maturity whereby retailers expand in waves with alternating periods of faster and slower growth. Walmart diffused gradually from Arkansas and Target grew from the coasts inward. They were similar, however, in that after expanding into an area they reached a point of saturation and opened fewer stores, then moved on to other areas, only to revisit the earlier areas for new stores.
ContributorsJoseph, Lawrence (Author) / Kuby, Michael (Thesis advisor) / Matthews, Richard (Committee member) / Ó Huallacháin, Breandán (Committee member) / Kumar, Ajith (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and motivation. The 1st version was a business-as-usual traditional classroom teaching mathematics with direct instruction. The 2rd version of the course provided students with self-paced, individualized Algebra instruction with a web-based, intelligent tutor. The 3rd version of the course coupled self-paced, individualized instruction on the web-based, intelligent Algebra tutor coupled with a series of e-learning modules on self-regulated learning knowledge and skills that were distributed throughout the semester. A quasi-experimental, mixed methods evaluation design was used by assigning pre-registered, high-school remedial Algebra I class periods made up of an approximately equal number of students to one of the three study conditions or course versions: (a) the control course design, (b) web-based, intelligent tutor only course design, and (c) web-based, intelligent tutor + SRL e-learning modules course design. While no statistically significant differences on SRL skills, math achievement or motivation were found between the three conditions, effect-size estimates provide suggestive evidence that using the SRL e-learning modules based on ARCS motivation model (Keller, 2010) and Let Me Learn learning pattern instruction (Dawkins, Kottkamp, & Johnston, 2010) may help students regulate their learning and improve their study skills while using a web-based, intelligent Algebra tutor as evidenced by positive impacts on math achievement, motivation, and self-regulated learning skills. The study also explored predictive analyses using multiple regression and found that predictive models based on independent variables aligned to student demographics, learning mastery skills, and ARCS motivational factors are helpful in defining how to further refine course design and design learning evaluations that measure achievement, motivation, and self-regulated learning in web-based learning environments, including intelligent tutoring systems.
ContributorsBarrus, Angela (Author) / Atkinson, Robert K (Thesis advisor) / Van de Sande, Carla (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2013
Description
The dynamics of urban water use are characterized by spatial and temporal variability that is influenced by associated factors at different scales. Thus it is important to capture the relationship between urban water use and its determinants in a spatio-temporal framework in order to enhance understanding and management of urban water demand. This dissertation aims to contribute to understanding the spatio-temporal relationships between single-family residential (SFR) water use and its determinants in a desert city. The dissertation has three distinct papers to support this goal. In the first paper, I demonstrate that aggregated scale data can be reliably used to study the relationship between SFR water use and its determinants without leading to significant ecological fallacy. The usability of aggregated scale data facilitates scientific inquiry about SFR water use with more available aggregated scale data. The second paper advances understanding of the relationship between SFR water use and its associated factors by accounting for the spatial and temporal dependence in a panel data setting. The third paper of this dissertation studies the historical contingency, spatial heterogeneity, and spatial connectivity in the relationship of SFR water use and its determinants by comparing three different regression models. This dissertation demonstrates the importance and necessity of incorporating spatio-temporal components, such as scale, dependence, and heterogeneity, into SFR water use research. Spatial statistical models should be used to understand the effects of associated factors on water use and test the effectiveness of certain management policies since spatial effects probably will significantly influence the estimates if only non-spatial statistical models are used. Urban water demand management should pay attention to the spatial heterogeneity in predicting the future water demand to achieve more accurate estimates, and spatial statistical models provide a promising method to do this job.
ContributorsOuyang, Yun (Author) / Wentz, Elizabeth (Thesis advisor) / Ruddell, Benjamin (Thesis advisor) / Harlan, Sharon (Committee member) / Janssen, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT This study describes student interactions in the academic social network site Edmodo versus student interactions in Facebook. This qualitative case study relies upon four high school juniors enrolled in Advanced Placement Language and Composition who use Edmodo to complete assignments for their English class. Their experiences were gathered in an attempt to describe specific experiences in a complex system. Students were selected using an Internet Connectedness Index survey. Using a Virtual Community of Practice framework, students were asked about their experiences in Edmodo. This study concludes that Edmodo and Facebook can be compared in three categories: accessibility, functionality, and environment. Unlike Facebook, which students access regularly, students access Edmodo only to fulfill the teacher's participation expectations for the specific grade they wish to receive. Additionally, students appreciated the convenience of using Edmodo to complete assignments. The functionality of Edmodo is quite similar in layout and appearance to Facebook, yet students were unaware of the media sharing capability, wished for private messaging options, and desired the ability to tag peers for direct comment using the @ sign, all options that are available in Facebook. Students felt the environment in Edmodo could best be characterized as intellectual and academic, which some mentioned might best be used with honors or AP students. A surprising benefit of Edmodo is the lack of social cues enable students to feel free of judgment when composing writing. Some felt this allowed students to know their classmates better and share their true personae free from judgment of classmates. As a result of the case studies of four students, this study seeks to illustrate how students interact in Edmodo versus Facebook to provide a robust image of the academic social network site for teachers seeking to implement educational technology in their classes.
ContributorsCurran-Sejkora, Elizabeth (Author) / Blasingame, James (Thesis advisor) / Nilsen, Alleen (Committee member) / Rodrigo, Rochelle (Committee member) / Turchi, Laura (Committee member) / Arizona State University (Publisher)
Created2013
Description
Two critical limitations for hyperspatial imagery are higher imagery variances and large data sizes. Although object-based analyses with a multi-scale framework for diverse object sizes are the solution, more data sources and large amounts of testing at high costs are required. In this study, I used tree density segmentation as the key element of a three-level hierarchical vegetation framework for reducing those costs, and a three-step procedure was used to evaluate its effects. A two-step procedure, which involved environmental stratifications and the random walker algorithm, was used for tree density segmentation. I determined whether variation in tone and texture could be reduced within environmental strata, and whether tree density segmentations could be labeled by species associations. At the final level, two tree density segmentations were partitioned into smaller subsets using eCognition in order to label individual species or tree stands in two test areas of two tree densities, and the Z values of Moran's I were used to evaluate whether imagery objects have different mean values from near segmentations as a measure of segmentation accuracy. The two-step procedure was able to delineating tree density segments and label species types robustly, compared to previous hierarchical frameworks. However, eCognition was not able to produce detailed, reasonable image objects with optimal scale parameters for species labeling. This hierarchical vegetation framework is applicable for fine-scale, time-series vegetation mapping to develop baseline data for evaluating climate change impacts on vegetation at low cost using widely available data and a personal laptop.
ContributorsLiau, Yan-ting (Author) / Franklin, Janet (Thesis advisor) / Turner, Billie (Committee member) / Myint, Soe (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sustainable development in an American context implies an ongoing shift from quantitative growth in energy, resource, and land use to the qualitative development of social-ecological systems, human capital, and dense, vibrant built environments. Sustainable urban development theory emphasizes locally and bioregionally emplaced economic development where the relationships between people, localities, products, and capital are tangible to and controllable by local stakeholders. Critical theory provides a mature understanding of the political economy of land development in capitalist economies, representing a crucial bridge between urban sustainability's infill development goals and the contemporary realities of the development industry. Since its inception, Phoenix, Arizona has exemplified the quantitative growth paradigm, and recurring instances of land speculation, non-local capital investment, and growth-based public policy have stymied local, tangible control over development from Phoenix's territorial history to modern attempts at downtown revitalization. Utilizing property ownership and sales data as well as interviews with development industry stakeholders, the political economy of infill land development in downtown Phoenix during the mid-2000s boom-and-bust cycle is analyzed. Data indicate that non-local property ownership has risen significantly over the past 20 years and rent-seeking land speculation has been a significant barrier to infill development. Many speculative strategies monopolize the publicly created value inherent in zoning entitlements, tax incentives and property assessment, indicating that political and policy reforms targeted at a variety of governance levels are crucial for achieving the sustainable development of urban land. Policy solutions include reforming the interconnected system of property sales, value assessment, and taxation to emphasize property use values; replacing existing tax incentives with tax increment financing and community development benefit agreements; regulating vacant land ownership and deed transfers; and encouraging innovative private development and tenure models like generative construction and community land trusts.
ContributorsStanley, Benjamin W (Author) / Boone, Christopher G. (Thesis advisor) / Redman, Charles (Committee member) / Bolin, Robert (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation explores vulnerability to extreme heat hazards in the Maricopa County, Arizona metropolitan region. By engaging an interdisciplinary approach, I uncover the epidemiological, historical-geographical, and mitigation dimensions of human vulnerability to extreme heat in a rapidly urbanizing region characterized by an intense urban heat island and summertime heat waves. I first frame the overall research within global climate change and hazards vulnerability research literature, and then present three case studies. I conclude with a synthesis of the findings and lessons learned from my interdisciplinary approach using an urban political ecology framework. In the first case study I construct and map a predictive index of sensitivity to heat health risks for neighborhoods, compare predicted neighborhood sensitivity to heat-related hospitalization rates, and estimate relative risk of hospitalizations for neighborhoods. In the second case study, I unpack the history and geography of land use/land cover change, urban development and marginalization of minorities that created the metropolitan region's urban heat island and consequently, the present conditions of extreme heat exposure and vulnerability in the urban core. The third study uses computational microclimate modeling to evaluate the potential of a vegetation-based intervention for mitigating extreme heat in an urban core neighborhood. Several findings relevant to extreme heat vulnerability emerge from the case studies. First, two main socio-demographic groups are found to be at higher risk for heat illness: low-income minorities in sparsely-vegetated neighborhoods in the urban core, and the elderly and socially-isolated in the expansive suburban fringe of Maricopa County. The second case study reveals that current conditions of heat exposure in the region's urban heat island are the legacy of historical marginalization of minorities and large-scale land-use/land cover transformations of natural desert land covers into heat-retaining urban surfaces of the built environment. Third, summertime air temperature reductions in the range 0.9-1.9 °C and of up to 8.4 °C in surface temperatures in the urban core can be achieved through desert-adapted canopied vegetation, suggesting that, at the microscale, the urban heat island can be mitigated by creating vegetated park cool islands. A synthesis of the three case studies using the urban political ecology framework argues that climate changed-induced heat hazards in cities must be problematized within the socio-ecological transformations that produce and reproduce urban landscapes of risk. The interdisciplinary approach to heat hazards in this dissertation advances understanding of the social and ecological drivers of extreme heat by drawing on multiple theories and methods from sociology, urban and Marxist geography, microclimatology, spatial epidemiology, environmental history, political economy and urban political ecology.
ContributorsDeclet-Barreto, Juan (Author) / Harlan, Sharon L (Thesis advisor) / Bolin, Bob (Thesis advisor) / Hirt, Paul (Committee member) / Boone, Christopher (Committee member) / Arizona State University (Publisher)
Created2013
Description
Statistics is taught at every level of education, yet teachers often have to assume their students have no knowledge of statistics and start from scratch each time they set out to teach statistics. The motivation for this experimental study comes from interest in exploring educational applications of augmented reality (AR) delivered via mobile technology that could potentially provide rich, contextualized learning for understanding concepts related to statistics education. This study examined the effects of AR experiences for learning basic statistical concepts. Using a 3 x 2 research design, this study compared learning gains of 252 undergraduate and graduate students from a pre- and posttest given before and after interacting with one of three types of augmented reality experiences, a high AR experience (interacting with three dimensional images coupled with movement through a physical space), a low AR experience (interacting with three dimensional images without movement), or no AR experience (two dimensional images without movement). Two levels of collaboration (pairs and no pairs) were also included. Additionally, student perceptions toward collaboration opportunities and engagement were compared across the six treatment conditions. Other demographic information collected included the students' previous statistics experience, as well as their comfort level in using mobile devices. The moderating variables included prior knowledge (high, average, and low) as measured by the student's pretest score. Taking into account prior knowledge, students with low prior knowledge assigned to either high or low AR experience had statistically significant higher learning gains than those assigned to a no AR experience. On the other hand, the results showed no statistical significance between students assigned to work individually versus in pairs. Students assigned to both high and low AR experience perceived a statistically significant higher level of engagement than their no AR counterparts. Students with low prior knowledge benefited the most from the high AR condition in learning gains. Overall, the AR application did well for providing a hands-on experience working with statistical data. Further research on AR and its relationship to spatial cognition, situated learning, high order skill development, performance support, and other classroom applications for learning is still needed.
ContributorsConley, Quincy (Author) / Atkinson, Robert K (Thesis advisor) / Nguyen, Frank (Committee member) / Nelson, Brian C (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation research investigates both spatial and temporal aspects of Bronze Age land use and land cover in the Eastern Mediterranean using botanical macrofossils of charcoal and charred seeds as sources of proxy data. Comparisons through time and over space using seed and charcoal densities, seed to charcoal ratios, and seed and charcoal identifications provide a comprehensive view of island vs. mainland vegetative trajectories through the critical 1000 year time period from 2500 BC to 1500 BC of both climatic fluctuation and significant anthropogenic forces. This research focuses particularly on the Mediterranean island of Cyprus during this crucial interface of climatic and human impacts on the landscape. Macrobotanical data often are interpreted locally in reference to a specific site, whereas this research draws spatial comparisons between contemporaneous archaeological sites as well as temporal comparisons between non-contemporaneous sites. This larger perspective is particularly crucial on Cyprus, where field scientists commonly assume that botanical macrofossils are poorly preserved, thus unnecessarily limiting their use as an interpretive proxy. These data reveal very minor anthropogenic landscape changes on the island of Cyprus compared to those associated with contemporaneous mainland sites. These data also reveal that climatic forces influenced land use decisions on the mainland sites, and provides crucial evidence pertaining to the rise of early anthropogenic landscapes and urbanized civilization.
ContributorsKlinge, JoAnna M (Author) / Fall, Patricia L. (Thesis advisor) / Falconer, Steven E. (Committee member) / Brazel, Anthony J. (Committee member) / Pigg, Kathleen B (Committee member) / Arizona State University (Publisher)
Created2013