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 philosophical inquiry explores the work of philosophers Gilles Deleuze and Félix Guattari and posits applications to music education. Through the concepts of multiplicities, becoming, bodies without organs, smooth spaces, maps, and nomads, Deleuze and Guattari challenge prior and current understandings of existence. In their writings on art, education, and how might one live, they assert a world consisting of variability and motion. Drawing on Deleuze and Guattari's emphasis on time and difference, I posit the following questions: Who and when are we? Where are we? When is music? When is education? Throughout this document, their philosophical figuration of a rhizome serves as a recurring theme, highlighting the possibilities of complexity, diverse connections, and continual processes. I explore the question "When and where are we?" by combining the work of Deleuze and Guattari with that of other authors. Drawing on these ideas, I posit an ontology of humans as inseparably cognitive, embodied, emotional, social, and striving multiplicities. Investigating the question "Where are we?" using Deleuze and Guattari's writings as well as that of contemporary place philosophers and other writers reveals that humans exist at the continually changing confluence of local and global places. In order to engage with the questions "When is music?" and "When is education?" I inquire into how humans as cognitive, embodied, emotional, social, and striving multiplicities emplaced in a glocalized world experience music and education. In the final chapters, a philosophy of music education consisting of the ongoing, interconnected processes of complicating, considering, and connecting is proposed. Complicating involves continually questioning how humans' multiple inseparable qualities and places integrate during musical and educative experiences. Considering includes imagining the multiple directions in which connections might occur as well as contemplating the quality of potential connections. Connecting involves assisting students in forming variegated connections between themselves, their multiple qualities, and their glocal environments. Considering a rhizomatic philosophy of music education includes continually engaging in the integrated processes of complicating, considering, and connecting. Through such ongoing practices, music educators can promote flourishing in the lives of students and the experiences of their multiple communities.
ContributorsRicherme, Lauren Kapalka (Author) / Stauffer, Sandra (Thesis advisor) / Gould, Elizabeth (Committee member) / Schmidt, Margaret (Committee member) / Sullivan, Jill (Committee member) / Tobias, Evan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Many longitudinal studies, especially in clinical trials, suffer from missing data issues. Most estimation procedures assume that the missing values are ignorable or missing at random (MAR). However, this assumption leads to unrealistic simplification and is implausible for many cases. For example, an investigator is examining the effect of treatment on depression. Subjects are scheduled with doctors on a regular basis and asked questions about recent emotional situations. Patients who are experiencing severe depression are more likely to miss an appointment and leave the data missing for that particular visit. Data that are not missing at random may produce bias in results if the missing mechanism is not taken into account. In other words, the missing mechanism is related to the unobserved responses. Data are said to be non-ignorable missing if the probabilities of missingness depend on quantities that might not be included in the model. Classical pattern-mixture models for non-ignorable missing values are widely used for longitudinal data analysis because they do not require explicit specification of the missing mechanism, with the data stratified according to a variety of missing patterns and a model specified for each stratum. However, this usually results in under-identifiability, because of the need to estimate many stratum-specific parameters even though the eventual interest is usually on the marginal parameters. Pattern mixture models have the drawback that a large sample is usually required. In this thesis, two studies are presented. The first study is motivated by an open problem from pattern mixture models. Simulation studies from this part show that information in the missing data indicators can be well summarized by a simple continuous latent structure, indicating that a large number of missing data patterns may be accounted by a simple latent factor. Simulation findings that are obtained in the first study lead to a novel model, a continuous latent factor model (CLFM). The second study develops CLFM which is utilized for modeling the joint distribution of missing values and longitudinal outcomes. The proposed CLFM model is feasible even for small sample size applications. The detailed estimation theory, including estimating techniques from both frequentist and Bayesian perspectives is presented. Model performance and evaluation are studied through designed simulations and three applications. Simulation and application settings change from correctly-specified missing data mechanism to mis-specified mechanism and include different sample sizes from longitudinal studies. Among three applications, an AIDS study includes non-ignorable missing values; the Peabody Picture Vocabulary Test data have no indication on missing data mechanism and it will be applied to a sensitivity analysis; the Growth of Language and Early Literacy Skills in Preschoolers with Developmental Speech and Language Impairment study, however, has full complete data and will be used to conduct a robust analysis. The CLFM model is shown to provide more precise estimators, specifically on intercept and slope related parameters, compared with Roy's latent class model and the classic linear mixed model. This advantage will be more obvious when a small sample size is the case, where Roy's model experiences challenges on estimation convergence. The proposed CLFM model is also robust when missing data are ignorable as demonstrated through a study on Growth of Language and Early Literacy Skills in Preschoolers.
ContributorsZhang, Jun (Author) / Reiser, Mark R. (Thesis advisor) / Barber, Jarrett (Thesis advisor) / Kao, Ming-Hung (Committee member) / Wilson, Jeffrey (Committee member) / St Louis, Robert D. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Nowadays product reliability becomes the top concern of the manufacturers and customers always prefer the products with good performances under long period. In order to estimate the lifetime of the product, accelerated life testing (ALT) is introduced because most of the products can last years even decades. Much research has been done in the ALT area and optimal design for ALT is a major topic. This dissertation consists of three main studies. First, a methodology of finding optimal design for ALT with right censoring and interval censoring have been developed and it employs the proportional hazard (PH) model and generalized linear model (GLM) to simplify the computational process. A sensitivity study is also given to show the effects brought by parameters to the designs. Second, an extended version of I-optimal design for ALT is discussed and then a dual-objective design criterion is defined and showed with several examples. Also in order to evaluate different candidate designs, several graphical tools are developed. Finally, when there are more than one models available, different model checking designs are discussed.
ContributorsYang, Tao (Author) / Pan, Rong (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Borror, Connie (Committee member) / Rigdon, Steve (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
ABSTRACT Two qualitative studies described the effects of parent's participation in the music therapy session on parent-child interaction during home-based musical experiences learned in music therapy session. Home-based musical play was based on two current programs: Sing & Grow (Abad & Williams, 2007; Nicolson, 2008 Abad, 2011; Williams, et al; 2012) and Musical Connection Programme(Warren & Nugent, 2010). The researcher utilized the core elements of these programs, such as session structures and parenting strategies for improving parent-child interaction during music therapy interventions. Several questions emerged as a result of these case studies as follows 1) does parent's participation affect parent-child interaction during music therapy interventions 2) does musical parenting strategies promote parent-child interaction while practicing musical play at home 3) does parent's interaction increase when they practice parental strategies listed on parent's self-check list. Music therapy session was provided once per week during an eight week period. The participants were referred by Arizona State University (ASU) music therapy clinic. Sessions took place either in the ASU music therapy treatment room or the participant's home. There were four participants- one diagnosed with Down syndrome and the other with Autism Spectrum Disorder (ASD) and two parents or caregivers (each subject was counted as one participant). The parent/caregiver filled out the parental self-checklist 3-4 times per week and the survey after the end of the program. The case study materials were gathered through with parent/caregiver. The case studies revealed that all of the parents responded that the parent's participation in music therapy helped to improve their interactions with their child. Furthermore, all parents became more responsive in interacting with their child through musical play, such as sing-a-long and movements. Second, musical parenting strategies encouraged parent-child interaction when practicing musical play at home. Third, the parent's self-checklist was shown to be effective material for increasing positive parent-child interaction. The self-checklist reminded the parents to practice using strategies in order to promote interaction with their child. Overall, it was found that the parent's participation in home-based musical play increased parent-child interaction and the musical parenting strategies enhanced parent-child interaction.
ContributorsChoi, Yoon Kyoung (Author) / Crowe, Barbara J. (Thesis advisor) / Rio, Robin (Committee member) / Sullivan, Jill (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
Dimensionality assessment is an important component of evaluating item response data. Existing approaches to evaluating common assumptions of unidimensionality, such as DIMTEST (Nandakumar & Stout, 1993; Stout, 1987; Stout, Froelich, & Gao, 2001), have been shown to work well under large-scale assessment conditions (e.g., large sample sizes and item pools; see e.g., Froelich & Habing, 2007). It remains to be seen how such procedures perform in the context of small-scale assessments characterized by relatively small sample sizes and/or short tests. The fact that some procedures come with minimum allowable values for characteristics of the data, such as the number of items, may even render them unusable for some small-scale assessments. Other measures designed to assess dimensionality do not come with such limitations and, as such, may perform better under conditions that do not lend themselves to evaluation via statistics that rely on asymptotic theory. The current work aimed to evaluate the performance of one such metric, the standardized generalized dimensionality discrepancy measure (SGDDM; Levy & Svetina, 2011; Levy, Xu, Yel, & Svetina, 2012), under both large- and small-scale testing conditions. A Monte Carlo study was conducted to compare the performance of DIMTEST and the SGDDM statistic in terms of evaluating assumptions of unidimensionality in item response data under a variety of conditions, with an emphasis on the examination of these procedures in small-scale assessments. Similar to previous research, increases in either test length or sample size resulted in increased power. The DIMTEST procedure appeared to be a conservative test of the null hypothesis of unidimensionality. The SGDDM statistic exhibited rejection rates near the nominal rate of .05 under unidimensional conditions, though the reliability of these results may have been less than optimal due to high sampling variability resulting from a relatively limited number of replications. Power values were at or near 1.0 for many of the multidimensional conditions. It was only when the sample size was reduced to N = 100 that the two approaches diverged in performance. Results suggested that both procedures may be appropriate for sample sizes as low as N = 250 and tests as short as J = 12 (SGDDM) or J = 19 (DIMTEST). When used as a diagnostic tool, SGDDM may be appropriate with as few as N = 100 cases combined with J = 12 items. The study was somewhat limited in that it did not include any complex factorial designs, nor were the strength of item discrimination parameters or correlation between factors manipulated. It is recommended that further research be conducted with the inclusion of these factors, as well as an increase in the number of replications when using the SGDDM procedure.
ContributorsReichenberg, Ray E (Author) / Levy, Roy (Thesis advisor) / Thompson, Marilyn S. (Thesis advisor) / Green, Samuel B. (Committee member) / Arizona State University (Publisher)
Created2013
Description
This mixed methods research study explores the experiences of Board Certified music therapists who completed a university-affiliated (UA) internship as part of their education and clinical training in music therapy. The majority of music therapy students complete a national roster (NR) internship as the final stage in clinical training. Limited data and research is available on the UA internship model. This research seeks to uncover themes identified by former university-affiliated interns regarding: (1) on-site internship supervision; (2) university support and supervision during internship; and (3) self-identified perceptions of professional preparedness following internship completion. The quantitative data was useful in creating a profile of interns interviewed. The qualitative data provided a context for understanding responses and experiences. Fourteen Board Certified music therapists were interviewed (N=14) and asked to reflect on their experiences during their university-affiliated internship. Commonalities discovered among former university-affiliated interns included: (1) the desire for peer supervision opportunities in internship; (2) an overall perception of being professionally prepared to sit for the Board Certification exam following internship; (3) a sense of readiness to enter the professional world after internship; and (4) a current or future desire to supervise university-affiliated interns.
ContributorsEubanks, Kymla (Author) / Rio, Robin (Thesis advisor) / Crowe, Barbara (Committee member) / Sullivan, Jill (Committee member) / Arizona State University (Publisher)
Created2013
Description
Parallel Monte Carlo applications require the pseudorandom numbers used on each processor to be independent in a probabilistic sense. The TestU01 software package is the standard testing suite for detecting stream dependence and other properties that make certain pseudorandom generators ineffective in parallel (as well as serial) settings. TestU01 employs two basic schemes for testing parallel generated streams. The first applies serial tests to the individual streams and then tests the resulting P-values for uniformity. The second turns all the parallel generated streams into one long vector and then applies serial tests to the resulting concatenated stream. Various forms of stream dependence can be missed by each approach because neither one fully addresses the multivariate nature of the accumulated data when generators are run in parallel. This dissertation identifies these potential faults in the parallel testing methodologies of TestU01 and investigates two different methods to better detect inter-stream dependencies: correlation motivated multivariate tests and vector time series based tests. These methods have been implemented in an extension to TestU01 built in C++ and the unique aspects of this extension are discussed. A variety of different generation scenarios are then examined using the TestU01 suite in concert with the extension. This enhanced software package is found to better detect certain forms of inter-stream dependencies than the original TestU01 suites of tests.
ContributorsIsmay, Chester (Author) / Eubank, Randall (Thesis advisor) / Young, Dennis (Committee member) / Kao, Ming-Hung (Committee member) / Lanchier, Nicolas (Committee member) / Reiser, Mark R. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Jazz continues, into its second century, as one of the most important musics taught in public middle and high schools. Even so, research related to how students learn, especially in their earliest interactions with jazz culture, is limited. Weaving together interviews and observations of junior and senior high school jazz players and teachers, private studio instructors, current university students majoring in jazz, and university and college jazz faculty, I developed a composite sketch of a secondary school student learning to play jazz. Using arts-based educational research methods, including the use of narrative inquiry and literary non-fiction, the status of current jazz education and the experiences by novice jazz learners is explored. What emerges is a complex story of students and teachers negotiating the landscape of jazz in and out of early twenty-first century public schools. Suggestions for enhancing jazz experiences for all stakeholders follow, focusing on access and the preparation of future jazz teachers.
ContributorsKelly, Keith B (Author) / Stauffer, Sandra (Thesis advisor) / Tobias, Evan (Committee member) / Kocour, Michael (Committee member) / Sullivan, Jill (Committee member) / Schmidt, Margaret (Committee member) / Arizona State University (Publisher)
Created2013