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
This dissertation explores the use of bench-scale batch microcosms in remedial design of contaminated aquifers, presents an alternative methodology for conducting such treatability studies, and - from technical, economical, and social perspectives - examines real-world application of this new technology. In situ bioremediation (ISB) is an effective remedial approach for many contaminated groundwater sites. However, site-specific variability necessitates the performance of small-scale treatability studies prior to full-scale implementation. The most common methodology is the batch microcosm, whose potential limitations and suitable technical alternatives are explored in this thesis. In a critical literature review, I discuss how continuous-flow conditions stimulate microbial attachment and biofilm formation, and identify unique microbiological phenomena largely absent in batch bottles, yet potentially relevant to contaminant fate. Following up on this theoretical evaluation, I experimentally produce pyrosequencing data and perform beta diversity analysis to demonstrate that batch and continuous-flow (column) microcosms foster distinctly different microbial communities. Next, I introduce the In Situ Microcosm Array (ISMA), which took approximately two years to design, develop, build and iteratively improve. The ISMA can be deployed down-hole in groundwater monitoring wells of contaminated aquifers for the purpose of autonomously conducting multiple parallel continuous-flow treatability experiments. The ISMA stores all sample generated in the course of each experiment, thereby preventing the release of chemicals into the environment. Detailed results are presented from an ISMA demonstration evaluating ISB for the treatment of hexavalent chromium and trichloroethene. In a technical and economical comparison to batch microcosms, I demonstrate the ISMA is both effective in informing remedial design decisions and cost-competitive. Finally, I report on a participatory technology assessment (pTA) workshop attended by diverse stakeholders of the Phoenix 52nd Street Superfund Site evaluating the ISMA's ability for addressing a real-world problem. In addition to receiving valuable feedback on perceived ISMA limitations, I conclude from the workshop that pTA can facilitate mutual learning even among entrenched stakeholders. In summary, my doctoral research (i) pinpointed limitations of current remedial design approaches, (ii) produced a novel alternative approach, and (iii) demonstrated the technical, economical and social value of this novel remedial design tool, i.e., the In Situ Microcosm Array technology.
ContributorsKalinowski, Tomasz (Author) / Halden, Rolf U. (Thesis advisor) / Johnson, Paul C (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Bennett, Ira (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study tested the effects of two kinds of cognitive, domain-based preparation tasks on learning outcomes after engaging in a collaborative activity with a partner. The collaborative learning method of interest was termed "preparing-to-interact," and is supported in theory by the Preparation for Future Learning (PFL) paradigm and the Interactive-Constructive-Active-Passive (ICAP) framework. The current work combined these two cognitive-based approaches to design collaborative learning activities that can serve as alternatives to existing methods, which carry limitations and challenges. The "preparing-to-interact" method avoids the need for training students in specific collaboration skills or guiding/scripting their dialogic behaviors, while providing the opportunity for students to acquire the necessary prior knowledge for maximizing their discussions towards learning. The study used a 2x2 experimental design, investigating the factors of Preparation (No Prep and Prep) and Type of Activity (Active and Constructive) on deep and shallow learning. The sample was community college students in introductory psychology classes; the domain tested was "memory," in particular, concepts related to the process of remembering/forgetting information. Results showed that Preparation was a significant factor affecting deep learning, while shallow learning was not affected differently by the interventions. Essentially, equalizing time-on-task and content across all conditions, time spent individually preparing by working on the task alone and then discussing the content with a partner produced deeper learning than engaging in the task jointly for the duration of the learning period. Type of Task was not a significant factor in learning outcomes, however, exploratory analyses showed evidence of Constructive-type behaviors leading to deeper learning of the content. Additionally, a novel method of multilevel analysis (MLA) was used to examine the data to account for the dependency between partners within dyads. This work showed that "preparing-to-interact" is a way to maximize the benefits of collaborative learning. When students are first cognitively prepared, they seem to make the most efficient use of discussion towards learning, engage more deeply in the content during learning, leading to deeper knowledge of the content. Additionally, in using MLA to account for subject nonindependency, this work introduces new questions about the validity of statistical analyses for dyadic data.
ContributorsLam, Rachel Jane (Author) / Nakagawa, Kathryn (Thesis advisor) / Green, Samuel (Committee member) / Stamm, Jill (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
This study examined the relations between cognitive ability, socioemotional competency (SEC), and achievement in gifted children. Data were collected on children between the ages of 8 and 15 years (n = 124). Children were assessed via teacher reports of SEC, standardized cognitive assessment, and standardized achievement assessment. Composite achievement significantly correlated with all areas of SEC on the Devereux Student Strengths Assessment (DESSA). Cognitive ability significantly correlated with all areas of SEC as well. Composite cognitive ability significantly correlated with all composite achievement, as well as with achievement in all subject areas assessed. Achievement scores tended to be higher in older age groups in comparison to younger age groups. When gender differences were found (in some areas of SEC and in language achievement), they tended to be higher in females. Gender moderated the relation between SEC and composite achievement. The areas of SEC that best predicted achievement, over-and-above other SEC scales, were Optimistic Thinking, Self-Awareness, and Relationship Skills. While cognitive scores did not significantly predict achievement when controlling for SEC, SEC did significantly predict achievement over-and-above cognitive ability scores. Overall findings suggest that SEC may be important in children's school achievement; thus it is important for schools and families to promote the development of SEC in gifted children, especially in the areas of optimism and self-awareness.
ContributorsKong, Tiffany (Author) / Caterino, Linda (Thesis advisor) / Naglieri, Jack (Committee member) / Brulles, Dina (Committee member) / Arizona State University (Publisher)
Created2013
Description
Current policies subsidizing or accelerating deployment of photovoltaics (PV) are typically motivated by claims of environmental benefit, such as the reduction of CO2 emissions generated by the fossil-fuel fired power plants that PV is intended to displace. Existing practice is to assess these environmental benefits on a net life-cycle basis, where CO2 benefits occurring during use of the PV panels is found to exceed emissions generated during the PV manufacturing phase including materials extraction and manufacture of the PV panels prior to installation. However, this approach neglects to recognize that the environmental costs of CO2 release during manufacture are incurred early, while environmental benefits accrue later. Thus, where specific policy targets suggest meeting CO2 reduction targets established by a certain date, rapid PV deployment may have counter-intuitive, albeit temporary, undesired consequences. Thus, on a cumulative radiative forcing (CRF) basis, the environmental improvements attributable to PV might be realized much later than is currently understood. This phenomenon is particularly acute when PV manufacture occurs in areas using CO2 intensive energy sources (e.g., coal), but deployment occurs in areas with less CO2 intensive electricity sources (e.g., hydro). This thesis builds a dynamic Cumulative Radiative Forcing (CRF) model to examine the inter-temporal warming impacts of PV deployments in three locations: California, Wyoming and Arizona. The model includes the following factors that impact CRF: PV deployment rate, choice of PV technology, pace of PV technology improvements, and CO2 intensity in the electricity mix at manufacturing and deployment locations. Wyoming and California show the highest and lowest CRF benefits as they have the most and least CO2 intensive grids, respectively. CRF payback times are longer than CO2 payback times in all cases. Thin film, CdTe PV technologies have the lowest manufacturing CO2 emissions and therefore the shortest CRF payback times. This model can inform policies intended to fulfill time-sensitive CO2 mitigation goals while minimizing short term radiative forcing.
ContributorsTriplican Ravikumar, Dwarakanath (Author) / Seager, Thomas P (Thesis advisor) / Fraser, Matthew P (Thesis advisor) / Chester, Mikhail V (Committee member) / Sinha, Parikhit (Committee member) / Arizona State University (Publisher)
Created2013
Description
Current emphasis on adequate academic progress monitored by standardized assessments has increased focus on student acquisition of required skills. Reading ability can be assessed through student achievement on Oral Reading Fluency (ORF) measures. This study investigated the effectiveness of using ORF measures to predict achievement on high stakes tests. Study participants included 312 students across four Title 1 elementary schools in a Southwestern United States school district utilizing the Response to Intervention (RTI) model. Participants' ORF scores from first through third grade years and their third grade standardized achievement test scores were collected. In addition, information regarding reading interventions was obtained. Pearson product-moment correlations were used to determine how ORF scores and specific reading skills were related. Correlations were also used to assess whether the ORF scores from the fall, winter, or spring were most related to high stakes test scores. Additionally, the difference between computer-based versus instructor-led interventions on predicting high stakes test scores was assessed. Results indicated that correlation coefficients were larger between ORF and reading comprehension scores than between ORF and basic reading skills. ORF scores from spring were more highly related to high stakes tests than other times of the year. Students' ORF scores were more strongly related to high stakes tests when in computer-based interventions compared to instructor-led interventions. In predicting third grade high stakes test scores, first grade ORF scores had the most variance for the non-intervention sample, while third grade ORF scores had the most variance for the intervention sample.
ContributorsDevena, Sarah (Author) / Caterino, Linda (Thesis advisor) / Balles, John (Committee member) / Mathur, Sarup (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study examined the effects of an intensive remedial program, Wilson Reading System (WRS), on 43 struggling readers from second to twelfth grade. The students, who attended a large southwestern urban school district, were all at least two grade levels below their peers in reading. Participants received 20 hours of WRS instruction over the course of one month as part of a WRS teacher certification course. Using the Woodcock-Johnson III Tests of Achievement, students were evaluated prior to and following their participation in the intensive summer program using five subtests (Letter-Word Identification, Reading Fluency, Spelling, Word Attack, and Spelling of Sounds) and two clusters (Basic Reading and Phoneme/Grapheme Knowledge) to assess gains in students' reading achievement. Since the intervention was delivered for such a brief period, this study was designed to provide a snapshot measure of initial reading skill gains. While a failure to perform significantly better was observed on the Letter-Word Identification, Reading Fluency, and Spelling subtests, students demonstrated significant improvement on Word Attack and Spelling of Sounds subtests following WRS instruction. Furthermore, students significantly improved on the Basic Reading and Phoneme/Grapheme Knowledge clusters. Study limitations and implications for future research and practice are discussed.
ContributorsAshby, Kristina (Author) / Caterino Kulhavy, Linda (Thesis advisor) / Gatt, Jennifer T (Committee member) / Mathur, Sarup (Committee member) / Arizona State University (Publisher)
Created2013
Description
Many manmade chemicals used in consumer products are ultimately washed down the drain and are collected in municipal sewers. Efficient chemical monitoring at wastewater treatment (WWT) plants thus may provide up-to-date information on chemical usage rates for epidemiological assessments. The objective of the present study was to extrapolate this concept, termed 'sewage epidemiology', to include municipal sewage sludge (MSS) in identifying and prioritizing contaminants of emerging concern (CECs). To test this the following specific aims were defined: i) to screen and identify CECs in nationally representative samples of MSS and to provide nationwide inventories of CECs in U.S. MSS; ii) to investigate the fate and persistence in MSS-amended soils, of sludge-borne hydrophobic CECs; and iii) to develop an analytical tool relying on contaminant levels in MSS as an indicator for identifying and prioritizing hydrophobic CECs. Chemicals that are primarily discharged to the sewage systems (alkylphenol surfactants) and widespread persistent organohalogen pollutants (perfluorochemicals and brominated flame retardants) were analyzed in nationally representative MSS samples. A meta-analysis showed that CECs contribute about 0.04-0.15% to the total dry mass of MSS, a mass equivalent of 2,700-7,900 metric tonnes of chemicals annually. An analysis of archived mesocoms from a sludge weathering study showed that 64 CECs persisted in MSS/soil mixtures over the course of the experiment, with half-lives ranging between 224 and >990 days; these results suggest an inherent persistence of CECs that accumulate in MSS. A comparison of the spectrum of chemicals (n=52) analyzed in nationally representative biological specimens from humans and MSS revealed 70% overlap. This observed co-occurrence of contaminants in both matrices suggests that MSS may serve as an indicator for ongoing human exposures and body burdens of pollutants in humans. In conclusion, I posit that this novel approach in sewage epidemiology may serve to pre-screen and prioritize the several thousands of known or suspected CECs to identify those that are most prone to pose a risk to human health and the environment.
ContributorsVenkatesan, Arjunkrishna (Author) / Halden, Rolf U. (Thesis advisor) / Westerhoff, Paul (Committee member) / Fox, Peter (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study looked at ways of understanding how schoolyards might act as meaningful places in children's developing sense of identity and possibility. Photographs and other images such as historical photographs and maps were used to look at how built environments outside of school reflect demographic and social differences within one southwest city. Intersections of children's worlds with various socio-political communities, woven into and through schooling, were examined for evidence of ways that schools act as the embodiment of a community's values: they are the material and observable effects of resource-allocation decisions. And scholarly materials were consulted to examine relationships in the images to existing theories of place, and its effect on children, as well as to consider theories of the hidden curriculum and its relationship to social reproduction, and the nature of visual representation as a form of data rather than strictly in the service of illustrating other forms of data. The focus of the study was on identifying appropriate research methods for investigating ways to understand the importance of the material worlds of school and childhood. Using a combination of visual and narrative approaches to contribute to our understanding of those material worlds, I sought to expose areas of inequity and class differences in ways that children experience schooling, as evidenced by differences in the material environment. Using a mixed-methods approach, created and found images were coded for categories of material culture, such as the existence of fences, trees, views from the playground or walking in the neighborhood at four Tempe schools. Findings were connected to a rich body of knowledge in areas such as theories of space and place, the nature of the hidden curriculum, visual culture, visual research methods including mapping. Familiar aspects of schooling were exposed in different ways, linking past decisions made by adults to their continuing effects on children today. In this way I arrived at an expanded and enriched understanding of the present worlds of children communicated as through the material environment. Visually examining children's worlds, by looking at the material artifacts of everyday worlds that children experience at school and including the child's-eye view in decision processes, has promise in moving decision makers away from strictly analytical and impersonal approaches to decision making about schooling children of the future. I proposed that by weighting of data points, as used in decision-making processes regarding schooling, differently than is currently done, and by paying closer attention to possible longer-term effects of place for all children, not just a few, there is the potential to improve the quality of life for today's children, and tomorrow's adults.
ContributorsWalsum, Joyce Van (Author) / Margolis, Eric M. (Thesis advisor) / Green, Samuel (Thesis advisor) / Collins, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
Description
Nitrate is the most prevalent water pollutant limiting the use of groundwater as a potable water source. The overarching goal of this dissertation was to leverage advances in nanotechnology to improve nitrate photocatalysis and transition treatment to the full-scale. The research objectives were to (1) examine commercial and synthesized photocatalysts, (2) determine the effect of water quality parameters (e.g., pH), (3) conduct responsible engineering by ensuring detection methods were in place for novel materials, and (4) develop a conceptual framework for designing nitrate-specific photocatalysts. The key issues for implementing photocatalysis for nitrate drinking water treatment were efficient nitrate removal at neutral pH and by-product selectivity toward nitrogen gases, rather than by-products that pose a human health concern (e.g., nitrite). Photocatalytic nitrate reduction was found to follow a series of proton-coupled electron transfers. The nitrate reduction rate was limited by the electron-hole recombination rate, and the addition of an electron donor (e.g., formate) was necessary to reduce the recombination rate and achieve efficient nitrate removal. Nano-sized photocatalysts with high surface areas mitigated the negative effects of competing aqueous anions. The key water quality parameter impacting by-product selectivity was pH. For pH < 4, the by-product selectivity was mostly N-gas with some NH4+, but this shifted to NO2- above pH = 4, which suggests the need for proton localization to move beyond NO2-. Co-catalysts that form a Schottky barrier, allowing for localization of electrons, were best for nitrate reduction. Silver was optimal in heterogeneous systems because of its ability to improve nitrate reduction activity and N-gas by-product selectivity, and graphene was optimal in two-electrode systems because of its ability to shuttle electrons to the working electrode. "Environmentally responsible use of nanomaterials" is to ensure that detection methods are in place for the nanomaterials tested. While methods exist for the metals and metal oxides examined, there are currently none for carbon nanotubes (CNTs) and graphene. Acknowledging that risk assessment encompasses dose-response and exposure, new analytical methods were developed for extracting and detecting CNTs and graphene in complex organic environmental (e.g., urban air) and biological matrices (e.g. rat lungs).
ContributorsDoudrick, Kyle (Author) / Westerhoff, Paul (Thesis advisor) / Halden, Rolf (Committee member) / Hristovski, Kiril (Committee member) / Arizona State University (Publisher)
Created2013