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 study explored female identity formation, of Ethiopian women and women of Ethiopian heritage as they participate in a coffee (buna) ceremony ritual. The study is anchored in the theoretical framework of a sociocultural perspective which enabled an examination of culture as what individuals do and believe as they participate in mutually constituted activities. Participants in Ethiopia were asked to photograph their daily routine beginning from the time they awoke until they retired for the night. Thematic analysis of the photographs determined that all participants depicted participation in the Ethiopian coffee ceremony in their photo study. Utilizing the photographs which specifically depicted the ceremony, eight focus groups and one interview consisting of women who have migrated from Ethiopia to Arizona, responded to the typicality of the photographs, as well as what they liked or did not like about the photographs. Focus groups were digitally recorded then transcribed for analysis. A combination of coding, extrapolation of rich texts, and identifying themes and patterns were used to analyze transcripts of the focus groups and interview. The findings suggest that this context is rich with shared meanings pertaining to: material artifacts, gender socialization, creation of a space for free expression, social expectations for communal contributions, and a female rite of passage.
ContributorsPlatt, Jennifer Brinkerhoff, 1971- (Author) / Arzubiaga, Angela (Thesis advisor) / Nakagawa, Kathryn (Thesis advisor) / Warriner, Doris (Committee member) / Arizona State University (Publisher)
Created2011
Description
In a large network (graph) it would be desirable to guarantee the existence of some local property based only on global knowledge of the network. Consider the following classical example: how many connections are necessary to guarantee that the network contains three nodes which are pairwise adjacent? It turns out that more than n^2/4 connections are needed, and no smaller number will suffice in general. Problems of this type fall into the category of ``extremal graph theory.'' Generally speaking, extremal graph theory is the study of how global parameters of a graph are related to local properties. This dissertation deals with the relationship between minimum degree conditions of a host graph G and the property that G contains a specified spanning subgraph (or class of subgraphs). The goal is to find the optimal minimum degree which guarantees the existence of a desired spanning subgraph. This goal is achieved in four different settings, with the main tools being Szemeredi's Regularity Lemma; the Blow-up Lemma of Komlos, Sarkozy, and Szemeredi; and some basic probabilistic techniques.
ContributorsDeBiasio, Louis (Author) / Kierstead, Henry A (Thesis advisor) / Czygrinow, Andrzej (Thesis advisor) / Hurlbert, Glenn (Committee member) / Kadell, Kevin (Committee member) / Fishel, Susanna (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this study was to investigate the impacts of visual cues and different types of self-explanation prompts on learning, cognitive load and intrinsic motivation, as well as the potential interaction between the two factors in a multimedia environment that was designed to deliver a computer-based lesson about the human cardiovascular system. A total of 126 college students were randomly assigned in equal numbers (N = 21) to one of the six experimental conditions in a 2 X 3 factorial design with visual cueing (visual cues vs. no cues) and type of self-explanation prompts (prediction prompts vs. reflection prompts vs. no prompts) as the between-subjects factors. They completed a pretest, subjective cognitive load questions, intrinsic motivation questions, and a posttest during the course of the experience. A subsample (49 out of 126) of the participants' eye movements were tracked by an eye tracker. The results revealed that (a) participants presented with visually cued animations had significantly higher learning outcome scores than their peers who viewed uncued animations; and (b) cognitive load and intrinsic motivation had different impacts on learning in multimedia due to the moderation effect of visual cueing. There were no other significant findings in terms of learning outcomes, cognitive load, intrinsic motivation, and eye movements. Limitations, implications and future directions are discussed within the framework of cognitive load theory, cognitive theory of multimedia learning and cognitive-affective theory of learning with media.
ContributorsLin, Lijia (Author) / Atkinson, Robert (Thesis advisor) / Nelson, Brian (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this exploratory study was to determine which social-emotional skills may predict postsecondary enrollment for students with disabilities. Students with disabilities are less likely to enroll in any form of postsecondary education and in turn experience poorer post-education outcomes than their general education peers. Using data from the second National Longitudinal Transition Study (NLTS2), a classification tree analysis was conducted on teacher-rated social-emotional behaviors in an attempt to determine which social-emotional skills were the strongest predictors of postsecondary enrollment. Items assessing social-emotional skills were selected from the second wave of teacher surveys based on their alignment with the broad taxonomy of social-emotional skills created by Caldarella and Merrell. The results of the classification tree analysis showed that one of the selected social-emotional items, teacher rated ability to follow directions, was the most significant predictor of postsecondary enrollment for students with disabilities. In general, the results suggest that compliance and, to a lesser extent, peer-relations skills, in addition to family income, predict postsecondary enrollment for students with high-incidence disabilities. This finding suggests that social-emotional skills play an important role in postsecondary enrollment for SWD, providing support for the use of social-emotional skills interventions in improving postsecondary enrollment rates and potentially post-educational outcomes for SWD.
ContributorsKaprolet, Charles M (Author) / Sullivan, Amanda L (Thesis advisor) / Caterino, Linda C (Committee member) / Yu, Chong Ho (Committee member) / Arizona State University (Publisher)
Created2011
Description
Designing studies that use latent growth modeling to investigate change over time calls for optimal approaches for conducting power analysis for a priori determination of required sample size. This investigation (1) studied the impacts of variations in specified parameters, design features, and model misspecification in simulation-based power analyses and (2) compared power estimates across three common power analysis techniques: the Monte Carlo method; the Satorra-Saris method; and the method developed by MacCallum, Browne, and Cai (MBC). Choice of sample size, effect size, and slope variance parameters markedly influenced power estimates; however, level-1 error variance and number of repeated measures (3 vs. 6) when study length was held constant had little impact on resulting power. Under some conditions, having a moderate versus small effect size or using a sample size of 800 versus 200 increased power by approximately .40, and a slope variance of 10 versus 20 increased power by up to .24. Decreasing error variance from 100 to 50, however, increased power by no more than .09 and increasing measurement occasions from 3 to 6 increased power by no more than .04. Misspecification in level-1 error structure had little influence on power, whereas misspecifying the form of the growth model as linear rather than quadratic dramatically reduced power for detecting differences in slopes. Additionally, power estimates based on the Monte Carlo and Satorra-Saris techniques never differed by more than .03, even with small sample sizes, whereas power estimates for the MBC technique appeared quite discrepant from the other two techniques. Results suggest the choice between using the Satorra-Saris or Monte Carlo technique in a priori power analyses for slope differences in latent growth models is a matter of preference, although features such as missing data can only be considered within the Monte Carlo approach. Further, researchers conducting power analyses for slope differences in latent growth models should pay greatest attention to estimating slope difference, slope variance, and sample size. Arguments are also made for examining model-implied covariance matrices based on estimated parameters and graphic depictions of slope variance to help ensure parameter estimates are reasonable in a priori power analysis.
ContributorsVan Vleet, Bethany Lucía (Author) / Thompson, Marilyn S. (Thesis advisor) / Green, Samuel B. (Committee member) / Enders, Craig K. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Nonlinear dispersive equations model nonlinear waves in a wide range of physical and mathematics contexts. They reinforce or dissipate effects of linear dispersion and nonlinear interactions, and thus, may be of a focusing or defocusing nature. The nonlinear Schrödinger equation or NLS is an example of such equations. It appears as a model in hydrodynamics, nonlinear optics, quantum condensates, heat pulses in solids and various other nonlinear instability phenomena. In mathematics, one of the interests is to look at the wave interaction: waves propagation with different speeds and/or different directions produces either small perturbations comparable with linear behavior, or creates solitary waves, or even leads to singular solutions. This dissertation studies the global behavior of finite energy solutions to the $d$-dimensional focusing NLS equation, $i partial _t u+Delta u+ |u|^{p-1}u=0, $ with initial data $u_0in H^1,; x in Rn$; the nonlinearity power $p$ and the dimension $d$ are chosen so that the scaling index $s=frac{d}{2}-frac{2}{p-1}$ is between 0 and 1, thus, the NLS is mass-supercritical $(s>0)$ and energy-subcritical $(s<1).$ For solutions with $ME[u_0]<1$ ($ME[u_0]$ stands for an invariant and conserved quantity in terms of the mass and energy of $u_0$), a sharp threshold for scattering and blowup is given. Namely, if the renormalized gradient $g_u$ of a solution $u$ to NLS is initially less than 1, i.e., $g_u(0)<1,$ then the solution exists globally in time and scatters in $H^1$ (approaches some linear Schr"odinger evolution as $ttopminfty$); if the renormalized gradient $g_u(0)>1,$ then the solution exhibits a blowup behavior, that is, either a finite time blowup occurs, or there is a divergence of $H^1$ norm in infinite time. This work generalizes the results for the 3d cubic NLS obtained in a series of papers by Holmer-Roudenko and Duyckaerts-Holmer-Roudenko with the key ingredients, the concentration compactness and localized variance, developed in the context of the energy-critical NLS and Nonlinear Wave equations by Kenig and Merle. One of the difficulties is fractional powers of nonlinearities which are overcome by considering Besov-Strichartz estimates and various fractional differentiation rules.
ContributorsGuevara, Cristi Darley (Author) / Roudenko, Svetlana (Thesis advisor) / Castillo_Chavez, Carlos (Committee member) / Jones, Donald (Committee member) / Mahalov, Alex (Committee member) / Suslov, Sergei (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT Cyberbullying has emerged as one of educators' and researchers' chief concerns as the use of computer mediated communication (CMC) has become ubiquitous among young people. Many undesirable outcomes have been identified as being linked to both traditional and cyberbullying, including depression,truancy, and suicide. America and Japan have both been identified as nations whose youth engage frequently in the use of CMC, and may be at a potentially higher risk to be involved in cyberbullying. Time spent using CMC has been linked to involvement in cyberbullying, and gender and age have, in turn, been linked to CMC use - these may play significant roles in determining who is at risk. In order to assess the effects of nationality, gender, and age on cyberbullying involvement among Japanese and American middle school students, a survey exploring these factors was developed and carried out with 590 American and Japanese middles school students (Japan: n = 433 and America: n = 157). MANOVA results indicated that that Americans tend to both use CMC more and be more involved in cyberbullying. In addition, Japanese involvement increased with age, while American involvement did not. There were minimal differences between Americans and Japanese with regards to traditional bullying.
ContributorsLerner, David (Author) / Nakagawa, Kathryn (Thesis advisor) / Caterino, Linda (Thesis advisor) / Ladd, Becky (Committee member) / Arizona State University (Publisher)
Created2011
Description
Over the past two decades, substantial research has documented the increase of students with disabilities enrolling in post-secondary education. The purpose of the study was to examine factors identified as significant in preparing individuals who fall on the autism spectrum for post-secondary experiences. The study was exploratory in nature and designed to identify perceived critical program elements needed to design successful post-secondary transition programs for students with an autism spectrum disorder (ASD). The study used archival research and grounded theory to look at expectations of parents with young adults with an ASD and young adults with an ASD on post-secondary transition and to discern whether expectations impact the successful post transition of young adults. More than likely, due to an overall increase in the prevalence of ASDs, many more students with an ASD will be attending a post-secondary educational setting in the near future. Understanding expectations and particular challenges faced by students with an ASD will be necessary for colleges to meet the unique needs of this population.
ContributorsFox, Catherine (Author) / McCoy, Kathleen (Thesis advisor) / Mathur, Sarup (Committee member) / Olsen, Morgan (Committee member) / Arizona State University (Publisher)
Created2011
Description
More than 30% of college entrants are placed in remedial mathematics (RM). Given that an explicit relationship exists between students' high school mathematics and college success in science, technology, engineering, and mathematical (STEM) fields, it is important to understand RM students' characteristics in high school. Using the Education Longitudinal Survey 2002/2006 data, this study evaluated more than 130 variables for statistical and practical significance. The variables included standard demographic data, prior achievement and transcript data, family and teacher perceptions, school characteristics, and student attitudinal variables, all of which are identified as influential in mathematical success. These variables were analyzed using logistic regression models to estimate the likelihood that a student would be placed into RM. As might be expected, student test scores, highest mathematics course taken, and high school grade point average were the strongest predictors of success in college mathematics courses. Attitude variables had a marginal effect on the most advantaged students, but their effect cannot be evaluated for disadvantaged students, due to a non-random pattern of missing data. Further research should concentrate on obtaining answers to the attitudinal questions and investigating their influence and interaction with academic indicators.
ContributorsBarber, Rebecca (Author) / Garcia, David R. (Thesis advisor) / Powers, Jeanne (Committee member) / Rodrigue Mcintyre, Lisa (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this study was to investigate the effect of complex structure on dimensionality assessment in compensatory and noncompensatory multidimensional item response models (MIRT) of assessment data using dimensionality assessment procedures based on conditional covariances (i.e., DETECT) and a factor analytical approach (i.e., NOHARM). The DETECT-based methods typically outperformed the NOHARM-based methods in both two- (2D) and three-dimensional (3D) compensatory MIRT conditions. The DETECT-based methods yielded high proportion correct, especially when correlations were .60 or smaller, data exhibited 30% or less complexity, and larger sample size. As the complexity increased and the sample size decreased, the performance typically diminished. As the complexity increased, it also became more difficult to label the resulting sets of items from DETECT in terms of the dimensions. DETECT was consistent in classification of simple items, but less consistent in classification of complex items. Out of the three NOHARM-based methods, χ2G/D and ALR generally outperformed RMSR. χ2G/D was more accurate when N = 500 and complexity levels were 30% or lower. As the number of items increased, ALR performance improved at correlation of .60 and 30% or less complexity. When the data followed a noncompensatory MIRT model, the NOHARM-based methods, specifically χ2G/D and ALR, were the most accurate of all five methods. The marginal proportions for labeling sets of items as dimension-like were typically low, suggesting that the methods generally failed to label two (three) sets of items as dimension-like in 2D (3D) noncompensatory situations. The DETECT-based methods were more consistent in classifying simple items across complexity levels, sample sizes, and correlations. However, as complexity and correlation levels increased the classification rates for all methods decreased. In most conditions, the DETECT-based methods classified complex items equally or more consistent than the NOHARM-based methods. In particular, as complexity, the number of items, and the true dimensionality increased, the DETECT-based methods were notably more consistent than any NOHARM-based method. Despite DETECT's consistency, when data follow a noncompensatory MIRT model, the NOHARM-based method should be preferred over the DETECT-based methods to assess dimensionality due to poor performance of DETECT in identifying the true dimensionality.
ContributorsSvetina, Dubravka (Author) / Levy, Roy (Thesis advisor) / Gorin, Joanna S. (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2011