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
It is commonly known that the left hemisphere of the brain is more efficient in the processing of verbal information, compared to the right hemisphere. One proposal suggests that hemispheric asymmetries in verbal processing are due in part to the efficient use of top-down mechanisms by the left hemisphere. Most evidence for this comes from hemispheric semantic priming, though fewer studies have investigated verbal memory in the cerebral hemispheres. The goal of the current investigations is to examine how top-down mechanisms influence hemispheric asymmetries in verbal memory, and determine the specific nature of hypothesized top-down mechanisms. Five experiments were conducted to explore the influence of top-down mechanisms on hemispheric asymmetries in verbal memory. Experiments 1 and 2 used item-method directed forgetting to examine maintenance and inhibition mechanisms. In Experiment 1, participants were cued to remember or forget certain words, and cues were presented simultaneously or after the presentation of target words. In Experiment 2, participants were cued again to remember or forget words, but each word was repeated once or four times. Experiments 3 and 4 examined the influence of cognitive load on hemispheric asymmetries in true and false memory. In Experiment 3, cognitive load was imposed during memory encoding, while in Experiment 4, cognitive load was imposed during memory retrieval. Finally, Experiment 5 investigated the association between controlled processing in hemispheric semantic priming, and top-down mechanisms used for hemispheric verbal memory. Across all experiments, divided visual field presentation was used to probe verbal memory in the cerebral hemispheres. Results from all experiments revealed several important findings. First, top-down mechanisms used by the LH primarily used to facilitate verbal processing, but also operate in a domain general manner in the face of increasing processing demands. Second, evidence indicates that the RH uses top-down mechanisms minimally, and processes verbal information in a more bottom-up manner. These data help clarify the nature of top-down mechanisms used in hemispheric memory and language processing, and build upon current theories that attempt to explain hemispheric asymmetries in language processing.
ContributorsTat, Michael J (Author) / Azuma, Tamiko (Thesis advisor) / Goldinger, Stephen D (Committee member) / Liss, Julie M (Committee member) / Arizona State University (Publisher)
Created2013
Description
Perceptual learning by means of coherent motion training paradigms has been shown to produce plasticity in lower and higher-level visual systems within the human occipital lobe both supra- and subliminally. However, efficiency of training methods that produce consolidation in the visual system via coherent motion has yet to be experimentally determined. Furthermore, the effects of coherent motion training on reading comprehension, in clinical and normal populations, are still nascent. In the present study, 20 participants were randomly assigned to one of four experimental conditions. Two conditions had a participation requirement of four days while two conditions required eight days of participation. These conditions were further divided into 500 or 1000 trials per day (4 x 500, 4 x 1000, 8 x 500, 8 x 1000). Additional pre-test and post-test days were used to attain timed pre- and post-tests on the Wide Range Achievement Test IV (WRAT IV) reading comprehension battery. Furthermore, a critical flicker fusion threshold (CFFT) score was taken on a macular pigment densitometer on the pre-test and post-test day. Participants showed significant improvement in CFFT levels, WRAT IV reading comprehension, and speed of completion between pre-test and post-test; however, degree of improvement did not vary as a function of training condition. An interaction between training condition and degree of improvement was evident in coherent dot motion contrast scores, with significant training plasticity occurring in the 4 x 1000 and 8 x 500 conditions.
ContributorsGroth, Anthony (Author) / Náñez, José E. (Thesis advisor) / Hall, Deborah (Committee member) / Risko, Evan F. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Frequency effects favoring high print-frequency words have been observed in frequency judgment memory tasks. Healthy young adults performed frequency judgment tasks; one group performed a single task while another group did the same task while alternating their attention to a secondary task (mathematical equations). Performance was assessed by correct and error responses, reaction times, and accuracy. Accuracy and reaction times were analyzed in terms of memory load (task condition), number of repetitions, effect of high vs. low print-frequency, and correlations with working memory span. Multinomial tree analyses were also completed to investigate source vs. item memory and revealed a mirror effect in episodic memory experiments (source memory), but a frequency advantage in span tasks (item memory). Interestingly enough, we did not observe an advantage for high working memory span individuals in frequency judgments, even when participants split their attention during the dual task (similar to a complex span task). However, we concluded that both the amount of attentional resources allocated and prior experience with an item affect how it is stored in memory.
ContributorsPeterson, Megan Paige (Author) / Azuma, Tamiko (Thesis advisor) / Gray, Shelley (Committee member) / Liss, Julie (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
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
When a rolling ball exits a spiral tube, it typically maintains its final inertial state and travels along straight line in concordance with Newton's first law of motion. Yet, most people predict that the ball will curve, a "naive physics" misconception called the curvilinear impetus (CI) bias. In the current paper, we explore the ecological hypothesis that the CI bias arises from overgeneralization of correct motion of biological agents. Previous research has established that humans curve when exiting a spiral maze, and college students believe this motion is the same for balls and humans. The current paper consists of two follow up experiments. The first experiment tested the exiting behavior of rodents from a spiral rat maze. Though there were weaknesses in design and procedures of the maze, the findings support that rats do not behave like humans who exhibit the CI bias when exiting a spiral maze. These results are consistent with the CI bias being an overgeneralization of human motion, rather than generic biological motion. The second experiment tested physics teachers on their conception of how a humans and balls behave when exiting a spiral tube. Teachers demonstrated correct knowledge of the straight trajectory of a ball, but generalized the ball's behavior to human motion. Thus physics teachers exhibit the opposite bias from college students and presume that all motion is like inanimate motion. This evidence supports that this type of naive physics inertial bias is at least partly due to participants overgeneralizing both inanimate and animate motion to be the same, perhaps in an effort to minimize cognitive reference memory load. In short, physics training appears not to eliminate the bias, but rather to simply shift it from the presumption of stereotypical animate to stereotypical inanimate behavior.
ContributorsDye, Rosaline (Author) / Mcbeath, Michael K (Thesis advisor) / Sanabria, Federico (Committee member) / Megowan, Colleen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Magicians are informal cognitive scientists who regularly test their hypotheses in the real world. As such, they can provide scientists with novel hypotheses for formal psychological research as well as a real-world context in which to study them. One domain where magic can directly inform science is the deployment of attention in time and across modalities. Both magicians and scientists have an incomplete understanding of how attention operates in time, rather than in space. However, magicians have highlighted a set of variables that can create moments of visual attentional suppression, which they call "off-beats," and these variables can speak to modern models of temporal attention. The current research examines two of these variables under conditions ranging from artificial laboratory tasks to the (almost) natural viewing of magic tricks. Across three experiments, I show that the detection of subtle dot probes in a noisy visual display and pieces of sleight of hand in magic tricks can be influenced by the seemingly irrelevant rhythmic qualities of auditory stimuli (cross-modal attentional entrainment) and processes of working memory updating (akin to the attentional blink).
ContributorsBarnhart, Anthony S (Author) / Goldinger, Stephen D. (Thesis advisor) / Glenberg, Arthur M. (Committee member) / Homa, Donald (Committee member) / Simons, Daniel J. (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