Doctor of Philosophy / Department of Psychology / James C. Shanteau / A training protocol was developed to teach an implicit reasoning strategy to encourage the consideration of alternatives, specifically in behavioral trap decision environments. Engaging the strategy would thereby decrease the effect of focusing on traps, resulting in more rational behavior. In two studies, training was delivered in an instructor-less environment using paper-pencil and multimedia examples. The main training components consisted of analogical problem solving and counterfactual thinking. The potential moderators between training and performance outcomes consisted of an information processing disposition Need for Cognitive Closure, an individualized approach to decisions, Decision-Making Style, and a capacity to process information Working Memory Capacity. Arousal and mood were also measured before, during, and after the training as both have been linked with learning. In Study 1, participants engaged in analogical problem solving, additive counterfactual thinking, subtractive counterfactual thinking, or none of these (i.e., control group). Results revealed that the training was minimally effective, although some comparisons revealed a large shift from pre- to post-training in commitment score away from trap options. Likewise, the Need for Cognitive Closure was the best predictor of decision behavior revealing that a predisposition for amount of information processed during decision making is indicative of behavioral outcomes in this decision environment. Based on results from Study 1, the training was reformatted in Study 2 to obtain the maximum potential benefit. Analogical problem solving was coupled with each form of counterfactual thinking so participants engaged in both critical thinking processes. When training was effective, the two forms were differentially effective as related to behavioral trap problem type. Forward-looking training assisted problem types that force explicit cost recognition and immediate decision outcomes. Past-looking training assisted problem types that force little cost recognition and delayed decision outcomes. Results of this project could be used to enhance the acquisition of critical thinking as well as improve educational practices. Both information processing disposition and decision approach style predicted learning whereas capacity to process information and training manipulations did not. Future projects will examine how long the training effects last and if critical thinking training can be successfully applied to other decision environments.

This study focuses on developing novel modeling techniques for fiber-reinforced composites with polymer and ceramic matrix based on Peridynamic approach. To capture the anisotropic material behaviors of composites under quasi-static and dynamic loading conditions, a new peridynamic model for composite laminate and a modified peridynamic approach for non-uniform discretization are proposed in this study. In order to achieve the numerical implementation of the proposed model and approach, a mixed implicit-explicit solver based on GPU parallel computing is developed as well. The new peridynamic model for composite laminates does not have any limitation in fiber orientation, material properties and stacking sequence. It can capture the expected orthotropic material properties and coupling behaviors in laminates with symmetric and asymmetric layups. Unlike the previous models, the new model enables the evaluation of stress and strain fields in each ply of the laminate. Therefore, it permits the use of existing stress- or strain-based failure criteria for damage prediction. The computation of strain energy stored at material points allows the energy-based failure criteria required for delamination propagation and fatigue crack growth. The capability of this approach is verified against benchmark solutions, and validated by comparison with the available experimental results for three laminate layups with an open hole under tension and compression. The modified peridynamic approach for non-uniform discretization enables computational efficiency and removes the effect of geometric truncations in the simulation. This approach is a modification to the original peridynamic theory by splitting the strain energy associated with an interaction between two material points according to the volumetric ratio arising from the presence of non-uniform discretization and variable horizon. It also removes the requirement for correction of peridynamic material parameters due to surface effects. The accuracy of this approach is verified against the benchmark solutions, and demonstrated by considering cracking in nuclear fuel pellet subjected to a thermal load with non-uniform discretizations. Unlike the previous peridynamic simulations which primarily employs explicit algorithm, this study introduces implicit algorithm to achieve peridynamic simulation under quasi-static loading condition. The Preconditioned Conjugate Gradient (PCG) and Generalized Minimal Residual (GMRES) algorithms are implemented with GPU parallel computing technology. Circulant preconditioner provides significant acceleration in the convergence of peridynamic analyses. To predict damage evolution, the simulation is continued with standard explicit algorithms. The validity and performance of this mixed implicit-explicit solver is established and demonstrated with benchmark tests.

Procedural learning abilities have been shown to be deficient in children who meet criteria for Developmental Dyslexia (DD) and those who meet criteria for Specific Language Impairment (SLI; Lum et al., 2010; Menghini et al., 2006). Further, grammatical understanding has been linked to implicit sequence learning abilities across SLI and typically developing children (Lum, 2012). The present study examined implicit sequence learning, measured by the Serial Reaction Time Task (SRTT), in children who met criteria for DD with or without SLI. Implicit sequence learning was modeled using multi-level growth models of initial reaction time and learning slope across the repeated sequences of the SRTT. We further examined the predictive contributions of grammatical understanding, vocabulary abilities, phonological awareness, and diagnostic groups on implicit learning performance on the SRTT. Results showed language abilities and diagnostic group did not relate strongly to rates of implicit learning.

L’anxiété de reblessure, cette appréhension à l’idée de se reblesser, fait partie des réactions psychologiques survenant suite à une blessure. La littérature scientifique n’a pour le moment fait état de cette dernière uniquement comme un facteur négatif qu’il faut prendre en charge. En effet, étudiée exclusivement chez les sportifs, elle semble être un obstacle lors de la rééducation et du retour au sport. Nous souhaitons adopter un autre point de vue et considérer le caractère adaptatif de cette émotion, en nous basant sur le caractère protecteur que nous connaissons de l’anxiété et ses tendances à l’action (l’évitement et l’inhibition). À travers cet ensemble de recherches, nous avons donc exploré le caractère bénéfique de l’anxiété de reblessure dans une population sportive, mais également non-sportive.Le document se déroule en 5 chapitres. Au cours du premier chapitre, nous faisons état de la littérature sur l’anxiété de reblessure. Puis dans un second chapitre, nous développons une mesure explicite de l’anxiété de reblessure. Un troisième chapitre explore les liens qu’entretiennent l’anxiété de reblessure et la prise de risque alors qu’un quatrième chapitre porte sur la mesure implicite de l’anxiété de reblessure et ses tendances automatiques à l’action. Enfin, un cinquième et dernier chapitre dans lequel nous discutons des résultats et de la prise en charge de l’anxiété de reblessure. / Reinjury anxiety is a psychological reaction arising further to an injury. Currently, the scientific literature considers reinjury anxiety solely as a negativ emotion you have to deal with and make disappear. Fact is, reinjury anxiety seems to be an hindrance to reeducation and a potential trouble when restarting a physical activity. We would like to adopt another point of view and consider the adaptive aspect of this emotion. We know anxiety, as a defensive reaction, makes you prone to action (avoidance and inhibition) and therefore could also be used as a positive incentive. Through our researches, we explored the positive aspects and mechanisms of reinjury anxiety on sportsman and non-sportsman people.The file is divided into 5 chapters. The first chapter is an overview of the academic work concerning reinjury anxiety. In a second chapter, we develop an explicit measure to reinjury anxiety. Chapter three explores the connections between reinjury anxiety and risk taking. The fourth chapter is related to the implicit measure of reinjury anxiety and its action readiness. Finally, in the fifth and last chapter, we discuss the results and the psychological treatment for reinjury anxiety.

The present dissertation explored the acquisition of grammatical knowledge in L2 by adults. The main focus was to investigate the role of type and token frequency in knowledge acquisition under incidental learning conditions. Such impact was studied by using different experimental conditions, in which items were presented with high or low type and token frequency during training. The mediating effect of working memory in such learning conditions was also measured. The material for the study was a natural language (Russian), as opposed to the previous research having used mainly artificial or semi-artificial languages. Within the course of four experiments native speakers of English with no previous knowledge of a Slavic language were exposed to noun-adjective agreement patterns of different complexity. A simple noun-adjective agreement pattern according to gender was used in Experiment 1. A medium-complexity pattern, according to gender and case, was chosen in Experiment 2. And a complex noun-adjective agreement pattern, according to gender, case and number, was used in Experiment 3. Experiment 4 employed the same agreement pattern as in Experiment 2; animacy effects were also studied by selecting animate and inanimate head nouns as stimuli. The knowledge acquired was tested both in comprehension and production domains. Working memory was measured using the Operation and Reading span tests. The results supported a “starting small” approach for production; accuracy was greater in the low type low token frequency and low type high token frequency conditions. For comprehension, high type frequency had shown more effect. Working memory was differentially involved in the production of acquired knowledge in different conditions and not engaged where learning was facilitated by frequency. Levels of knowledge also depended on the complexity of the agreement pattern, frequency effects and the domain of knowledge acquisition: comprehension versus production.

The purpose of this study was to examine the implicit language attitudes of college-level instructors toward accented English and the effect of gender, teaching experience, and home language background on those attitudes. The auditory multifactor Implicit Association Test (IAT) was used to measure the implicit attitudes toward Standard, Chinese, Hispanic, and Korean accented English. For the current study, audio stimuli were embedded into the multifactor IAT, which became available for the first time in 2014. The auditory multifactor IAT generated implicit preference scores of six pairs of accented English: Standard vs. Chinese, Standard vs. Hispanic, Standard vs. Korean, Chinese vs. Hispanic, Chinese vs. Korean, and Hispanic vs. Korean accented English. Participants (N = 93) included college instructors at an urban university in Florida. Statistical analysis results suggested that college instructors in this study exhibited some bias towards speakers of Hispanic-accented English, but no bias toward the other five. However, analysis of the frequency distributions of the responses showed bi-polar accent biases did exist. It was possible that the similar numbers for the polar opposites balanced each other in the statistical results of no bias. Gender and home language background had no effect on implicit preference scores. The years of teaching experience had significant effect in Hispanic- vs. Korean-accented English, but not in the other five accented language pairs. However, close examination of the beta coefficient per year indicated that the relationship was weak even though the effect was significant. Faculty, administrators, and students could use test results as a topic of discussion in faculty development, teaching assistant training, student services, and diversity training in higher education institutions. The discussions might help awareness of hidden-yet-present accent bias and prevent potential prejudice toward other accented English speakers. The administrators need to be aware that preferences do exist toward accented English speakers. These preferences--or biases--toward an accent may be important in selecting instructors.

Florida is the “Fishing Capital of the World”. With 3.1 million recreational anglers and total recreational fishing-related expenditures of $5 billion in 2011, Florida ranked first in the nation. Given the large benefits of recreational fishing in Florida, assessing the preferences of anglers is critical for sustaining the substantial benefits obtained from recreational fishing in Florida. The objective of this study is to estimate the value of fishing attributes using data on recreational fishing services offered by guides and outfitters. Hedonic price models are applied to estimate the implicit prices of fishing trip attributes and features. The estimated total economic impacts suggest that recreational fishing activities have added $151.19 million value to the economy of Florida and generated $69.73 million in total output. The results can be used by state and national policymakers for future policy design and management of this unique ecosystem service to ensure a sustainable economy.

Using an autoethnographic methodology in tandem with a social constructivist lens, the purpose of this study is to critically inquire into the implicit lessons learned by competitive Latin dancers from their participation in the hidden curriculum of DanceSport culture. Additionally, this research looks to outline the intrapersonal and interpersonal development experienced by DanceSport dancers. Doing so, I focus on the voice of the dancers in the exploration of International DanceSport studios and competition floors as sites of informal and non-formal education, particularly in relation to the hidden curriculum of DanceSport. My role as an autoethnographic researcher and participant in this study was to collect data through multimodal expression, as well as ongoing dialogue with participants. As researcher and participant, I completed the same hands-on task and interview questions as participants, and journaled to explore thoughts concerning my DanceSport experience. Information obtained from interview transcripts and journal entries has been organized, coded, and analyzed creating themes. A description and interpretation of the findings uncovers the unifying theme(s) of six narratives. Narrative inquiry reveals that the hidden curriculum of DanceSport is the awakening and development of dormant confidence as dancers acquire implicit lessons pertaining to the development of intra and interpersonal knowledge. A discussion exploring the unique ways this dissertation contributes to the DanceSport community and body of literature concludes this study. This is alongside an assessment as to the culture’s ability to meet current goals of formal education, and the potential Latin DanceSport has to be used as an educational tool in the development of student well-being.

Modelling in cardiac electrophysiology results in a complex system of partial differential equations (PDE) describing the propagation of the electrical wave in the heart muscle coupled with a highly nonlinear system of ordinary differential equations (ODE) describing the ionic activity in the cardiac cells. This system forms the widely accepted bidomain model or its slightly simpler version, the monodomain model. To a large extent, the stiffness of the whole model depends on the choice of the ionic model, which varies in terms of complexity and realism. These simulations require accurate and, depending on the ionic model used, possibly very stable numerical methods. At this time, solving these models numerically requires CPU time of around one day per heartbeat. Therefore, it is necessary to use the most efficient method for these simulations. This research focuses on the comparison and analysis of several time-stepping methods: explicit or semi-implicit, operator splitting, deferred correction and Rush-Larsen methods. The goal is to find the optimal method for the ionic model used. For our analysis, we used the monodomain model but our results apply to the bidomain model as well. We compare the methods for three ionic models of varying complexity and stiffness: the Mitchell-Schaeffer models with only 2 variables, the more realistic Beeler-Reuter model with 8 variables, and the stiff and very complex ten Tuscher-Noble-Noble-Panfilov (TNNP) models with 17 variables. For each method, we derived absolute stability criteria of the spatially discretized monodomain model and verified that the theoretical critical time steps obtained closely match the ones in numerical experiments. Convergence tests were also conducted to verify that the numerical methods achieve an optimal order of convergence on the model variables and derived quantities (such as speed of the wave, depolarization time), and this in spite of the local non-differentiability of some of the ionic models. We looked at the efficiency of the different methods by comparing computational times for similar accuracy. Conclusions are drawn on the methods to be used to solve the monodomain model based on the model stiffness and complexity, measured respectively by the most negative eigenvalue of the model's Jacobian and the number of variables, and based on strict stability and accuracy criteria.

3D geological modelling is becoming an effective tool for communication and development of geological understanding. This is due to increased computer performance and availability of improved geological modelling software. 3D geological modelling technology has reached the stage where it can be implemented in regionally extensive and geologically complex settings, with the ability to achieve geological insight beyond what could otherwise have been gained through 2D investigations alone. Insight includes better constrained fault and horizon topologies, refined fold geometries, improved understanding of tectonic processes, and characterization of deformational events. By integrating field observations, aeromagnetic maps, and 3D modelling techniques in the northern Labrador Trough, a regionally extensive and structurally complex geological environment, regional faults geometries and topological relationships were refined. Additionally, a new fault, the Ujaralialuk Fault, and two shear zones were interpreted. During modelling, several challenges were identified, including higher computational costs for regionally extensive models, sparse 3D constraints, algorithmic limitations related to complex geometries, and the large investment of time and effort required to produce a single model solution. A benefit of this investigation is that new insight was also gained for a greenfields region which may assist future exploration efforts. Developing 3D models in challenging environments allows for better definition of future workflow requirements, algorithm enhancements, and knowledge integration. These are needed to achieve a geologically reasonable modelling standard and gain insight for poorly constrained geological settings.