Browsing by Subject "learning"
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Item A Case Study of Faculty Perceptions of Student Plagiarism(2012-02-14) Schaefer, Candace HastingsThis study examined faculty perceptions of plagiarism in the classroom using a qualitative case study methodology. A single university was used for the case study to locate all data under a single institutional culture. A purposive sample of eleven faculty were interviewed and content analysis was conducted on the data. The data were analyzed using Lave and Wenger?s theory of legitimate peripheral participation, a learning theory which proposes that all learning takes place in a community of practice and that learning takes place as a result of interactions between members of the community of practice. Because the data were analyzed using legitimate peripheral participation, faculty were asked to reflect on how they learned to write in their discipline, how they view their role in working with students as they become proficient in writing in their discipline, and what happens when students violate community practices. This study attempted to reframe scholarship that approaches plagiarism as a right vs. wrong issue and recast scholarship on plagiarism as an issue of students moving toward full participation in the community of practice of academic scholars under the tutelage of faculty members. Research participants saw themselves as mentors to students as they developed their academic writing standards and abilities, a philosophy in keeping with the tenets of legitimate peripheral participation. Research participants attributed violations of community standards to institutional constructs such as grades, social constructs such as culture or generation, or individual constructs such as moral character or upbringing.Item Coding and learning of chemosensor array patterns in a neurodynamic model of the olfactory system(Texas A&M University, 2007-09-17) Gutierrez Galvez, AgustinArrays of broadly-selective chemical sensors, also known as electronic noses, have been developed during the past two decades as a low-cost and high-throughput alternative to analytical instruments for the measurement of odorant chemicals. Signal processing in these gas-sensor arrays has been traditionally performed by means of statistical and neural pattern recognition techniques. The objective of this dissertation is to develop new computational models to process gas sensor array signals inspired by coding and learning mechanisms of the biological olfactory system. We have used a neurodynamic model of the olfactory system, the KIII, to develop and demonstrate four odor processing computational functions: robust recovery of overlapping patterns, contrast enhancement, background suppression, and novelty detection. First, a coding mechanism based on the synchrony of neural oscillations is used to extract information from the associative memory of the KIII model. This temporal code allows the KIII to recall overlapping patterns in a robust manner. Second, a new learning rule that combines Hebbian and anti-Hebbian terms is proposed. This learning rule is shown to achieve contrast enhancement on gas-sensor array patterns. Third, a new local learning mechanism based on habituation is proposed to perform odor background suppression. Combining the Hebbian/anti-Hebbian rule and the local habituation mechanism, the KIII is able to suppress the response to continuously presented odors, facilitating the detection of the new ones. Finally, a new learning mechanism based on anti-Hebbian learning is proposed to perform novelty detection. This learning mechanism allows the KIII to detect the introduction of new odors even in the presence of strong backgrounds. The four computational models are characterized with synthetic data and validated on gas sensor array patterns obtained from an e-nose prototype developed for this purpose.Item Connecting the role of school superintendents to teaching and learning in schools: a research synthesis of three educational administration peer reviewed research journals between 1983-2006(Texas A&M University, 2008-10-10) Shidemantle, Steven PaulThis exploratory synthesis of research was the product of three years of dissertation research efforts that systematically reviewed 23 years of empirical articles between 1983 (or its inception) and 2006 from three of the most highly regarded educational administration journals. Specifically designed to collect investigative data and information from primary research contained within Educational Administration Quarterly, the Journal of School Leadership, and the Journal of Educational Administration; this research synthesis drew upon various research methods to propose pragmatic insights and proffer an empirically founded response to: What has the educational administration profession learned from the research efforts that were independently conducted, presented, and published about the overall connections between school superintendents and education's technical core -teaching and learning in schools? Results from employing meta-analysis, descriptive synthesis, and thematic synthesis techniques to appropriately collect and analyze relevant data indicate that school superintendents remain directly connected to the technical core; however, these connections have evolved from the traditional connections presently maintained by campus administrators and to new connections that meet the increased responsibilities and complexities of the superintendents' role. The thematic synthesis, reinforced by descriptive syntheses, indicated 15 separate superintendent - technical core constructs that promote new areas for investigation; however, the extent and strength of these constructs have yet to be determined. The impact from the next step suggestions for future research indicate that effects could range from educational administration knowledge base contributions to refining in-practice standards and professional development programs. The possible knowledge base contributions, coupled with specific in-practice elements that demonstrate superintendents' direct impact on the technical core, may be the necessary raw materials from which a foundational framework that clearly redefines the superintendent - technical core connections may be forged by scholars and implemented by district leaders to improve teaching and learning in schools.Item Defining and determining the impact of a freshman engineering student's approach to learning (surface versus deep)(Texas A&M University, 2004-11-15) Fowler, Debra AnneWhen an engineering student attends four or five years of college to become a professional engineer one makes the assumption that they approach this learning process in such a way to gain the most knowledge possible. The purpose of this study is to measure the learning approach (deep versus surface) of first-year engineering students, test the impact of two interventions (journaling and learning strategy awareness) on increasing the deep approach to learning, and determine the relationship of the approach to learning on retention within an engineering program. The study was conducted using a quantitative self-reporting instrument to measure surface and deep learning at the beginning and end of the first and second semesters of the freshman year in an engineering program. Retention was measured as the continuous enrollment of a student in the second semester of the first-year engineering program. Results indicate that the first-year engineering students have a slightly higher level of the deep approach to learning than a surface approach to learning when they begin college. However, the results also indicate that the deep approach to learning decreased during the first semester and during the second semester of their freshman year. A student's approach to learning can be impacted by their prior knowledge, the teaching context, the institutional context or the motivation of the student. Results surrounding the learning strategies intervention also indicate that the first-year engineering students do not possess the strong learning strategies that are anticipated from students accepted into an engineering program with stringent application requirements. Finally, results indicate that a deep approach to learning appears to have a positive relationship and a surface approach to learning appears to have a negative relationship to retention in an engineering program. This study illustrates that incorporating learning theory and the use of current learning strategy measurements contributes to the understanding of a freshman engineering student's approach to learning. The understanding of the engineering student's approach to learning benefits faculty in establishing curriculum and pedagogical design. The benefit to the student is in understanding more about themselves as a learner.Item Essays on Network Formation(2012-10-19) Mueller, William GrahamThis dissertation contains two essays which examine the roles that individual incentives, competition, and information play in network formation. In the first essay, I examine a model in which two competing groups offer different allocation rules that may depend on the network of connections among the individuals that make up each group. I assume the existence of a single divisible good, such as a monetary prize, which will be divided amongst the members of the winning network. The probability of winning the prize will depend on the network sizes. I examine two well-known allocation rules: the Myerson value and the egalitarian rule. I prove existence of equilibria and characterize the properties of the two networks. The implications of the equilibria networks for the outcome of the contest are discussed. I find that the winning probability of the network using the Myerson value has an upper bound very close to one half. There is no such upper bound for the network using the egalitarian rule. In my second essay, I examine a dynamic model of network formation in which individuals use reinforcement learning to choose their actions. Typically, economic models of network formation assume the entire network structure to be known to all individuals involved. The introduction of reinforcement learning allows us to relax this assumption. Through the use of a state-dependent reinforcement learning rule, one may allow for varying degrees of information available to the agents. Three informational settings are examined and I determine what networks, if any, each model may converge to in the limit. The long-run behavior of each model is examined through the use of simulations and compared to one another. I find that amount and type of information agents have access plays an important role in which networks emerge when there is no dominant strategy for the agents choosing links. If there is a dominant link choosing strategy, the most efficient network structure quickly emerges in each informational setting. Together, these essays investigate how information, incentives, and competition may affect network formation. Individual incentives in the presence of competition can create tension between an individual's social ties and the overall network size. Information plays a key role in the emergent network topologies when there are no dominate network building strategies.Item Learning and risk aversion(2009-06-02) Oyarzun, CarlosThis dissertation contains three essays on learning and risk aversion. In the first essay we consider how learning may lead to risk averse behavior. A learning rule is said to be risk averse if it is expected to add more probability to an action which provides, with certainty, the expected value of a distribution rather than when it provides a randomly drawn payoff from this distribution, for every distribution. We characterize risk averse learning rules. The result reveals that the analysis of risk averse learning is isomorphic to that of risk averse expected utility maximizers. A learning rule is said to be monotonically risk averse if it is expected to increase the probability of choosing the actions whose distribution second-order stochastically dominates all others in every environment. We characterize monotonically risk averse learning rules. In the second essay we analyze risk attitudes for learning within the mean-variance paradigm. A learning rule is variance-averse if the expected reduced distribution of payoffs in the next period has a smaller variance than that of the current reduced distribution, in every set where all the actions provide the same expected payoff. A learning rule is monotonically variance-averse if it is expected to add probability to the set of actions that have the smallest variance in the set, when all the actions have the same expected payoff. A learning rule is monotonically mean-variance-averse if it is expected to add probability to the set of actions that have the highest expected payoff and smallest variance whenever this set is not empty. We characterize monotonically variance-averse and monotonically mean-variance-averse learning rules. In the last essay we analyze the social learning process of a group of individuals. We say that a learning rule is first-order monotone if the number of individuals that play actions with first-order stochastic dominant payoff distributions is expected to increase. We characterize these learning rules.Item Personal develoment and transformational outcomes for women earning an online degree(2009-05-15) Weatherly, Martha GailThis qualitative study was designed to investigate the changes that occurred in the lives of women as a result of earning a fully online master?s degree. Eighteen women were asked to describe why they chose to earn an online degree, what barriers they faced in trying to gain an education and advance professionally, how their lives changed as a result of earning the degree, and whether the outcomes met or surpassed their expectations. Constant comparative and narrative analysis of interview data revealed that women who overcame barriers and resistance to their pursuit of education experienced a range of benefits from earning the online degree. Benefits encompassed personal gains in self-confidence, respect, the strength to be a role model, and professional gains such as new career opportunities, connectedness in a professional community, and credibility among peers. Participants reported the online environment uniquely connected them to a more diverse group of peers, provided greater access to instructors and peers, offered highly valued anonymity, introduced them to a more engaged form of learning, and created a safe learning environment. Online learning emphasized students? writing, reflection, articulation, timely feedback from the facilitator, caring and respect for students, and effective communication. Participants shared that earning the degree had a ?domino effect? that led others to emulate their behavior, and some experienced relationship changes. Significantly, several of the women had a transformational learning experience that included: (1) an unexpected discovery leading to heightened personal awareness that resulted from the learning experience; (2) an openness to change and the process of becoming; (3) a willingness to overcome internal or external resistance in order to redefine self; and (4) a retrospective affirmation of altered personality and identity. Participants suggested women still face discrimination in their professional lives, making advanced degrees more critical for women. They recommended that institutions of higher education provide more advanced online degree programs for the benefit of women who have a variety of other demands placed on their lives as they strive to attain their personal and professional goals. Implications and recommendations for future research and policy changes are provided.Item Regular treadmill exercise prevents sleep deprivation-induced impairment of hippocampal-dependent memory and synaptic plasticity(2012-04-19) Zagaar, Munder; Alkadhi, Karim; Eriksen, Jason; Salim, Samina; Grill, Raymond; Alcantara, AdrianaABSTRACT Study Objectives: Evidence suggests that regular exercise can protect against learning and memory impairment in the presence of insults such as stroke and neurodegeneration. The purpose of this study was to determine the effect of regular exercise on hippocampus-dependent learning and memory impairment associated with sleep deprivation. Experimental Design: We investigated the effects of 4 weeks of regular treadmill exercise on learning and memory impairment in 24 hour sleep-deprived rats. Sleep deprivation was accomplished using the columns-in-water model. We tested the effects of exercise and/or sleep deprivation using three approaches: the radial arm water maze (RAWM) task to test spatial learning and memory performance; electrophysiological recording in the Cornu Ammonis (CA1) and dentate gyrus (DG) areas of the hippocampus to measure synaptic plasticity; and western blot analysis to quantify the levels of key signaling molecules that are related to memory and synaptic plasticity. Results: In the RAWM, regular exercise prevented the sleep deprivation-induced impairment of spatial learning, short-term memory, and early-phase long-term potentiation (E-LTP) in both CA1 and DG areas. In correlation, exercise prevented the sleep deprivation-associated decrease in basal levels of phosphorylated and total calcium/calmodulin-dependent protein kinase II (P/total-CaMKII) and brain-derived neurotrophic factor (BDNF). High frequency stimulation (HFS), which increased the P-CaMKII and BDNF levels in normal animals, did not change these levels in sleep-deprived rats but did increase levels of the phosphatase calcineurin. In contrast, exercise increased BDNF and P-CaMKII levels in exercised/sleep-deprived rats, probably by preventing increases in calcineurin levels, thus maintaining appropriate P-CaMKII levels. Regular exercise also prevented the sleep deprivation-induced impairment of long-term memory and late-phase LTP. In correlation, exercise increased the basal levels of phosphorylated cAMP response element binding protein (P-CREB) and total-CREB as well as P/total- mitogen activated protein kinase (MAPK/ERK) in CA1 and DG areas of sleep-deprived rats. Also, exercise allowed multiple HFS to increase the levels of BDNF and P/total-CREB during L-LTP expression in sleep-deprived rats. Conclusions: These findings suggest that sleep deprivation impairs both the CA1 and DG areas whereas exercise prevents this impairment. Regular exercise exerts a protective effect against sleep deprivation-induced impairment probably by inducing BDNF expression, which can positively modulate basal and/or stimulated levels of P-CaMKII, P-CREB, P-MAPK/ERK and calcineurin. As a result, exercise-induced BDNF could contribute to the restoration of hippocampus-dependent learning and memory as well as LTP in both CA1 and DG areas.Item The Impact of the Katy Management of Automated Curriculum System on Planning for Learning, Delivery of Instruction and Evaluation of Student Learning as Perceived by Teachers in the Katy Independent School District in Texas(2011-10-21) Hogue, Sharon L.The purpose of this study was to determine teachers? perceptions of the relationship of the Katy Management of Automated Curriculum (KMAC) system developed by Katy ISD in Katy, Texas, on planning for learning, delivery of instruction and evaluation of student learning in the classroom. KMAC is a customized, proprietary networked technology curriculum management system created for online access to curriculum and the creation and sharing of lesson plans. Data was collected from 635 teachers district-wide through an online survey. This data was used to determine whether there were differences between/among teachers and teacher leaders and between/among elementary, junior high and high school teachers in their perceived impact of the KMAC on planning for learning, delivery of instruction and evaluation of student learning. Regarding planning for learning, teachers were found to have a moderately positive perception of KMAC with teacher leaders being slightly more positive. In addition, statistically significant differences were found between grade levels with elementary teachers more positive than secondary teachers. Regarding delivery of instruction, teacher leaders again perceived a more positive relationship with KMAC than the teacher non-leaders. Statistically significant differences were also found between elementary and junior high, elementary and high school and between junior high and high school teachers, with elementary teachers being the most positive. Teachers were the least positive toward KMAC and the evaluation of student learning. While a statistically significant relationship was found in relationship to the grade level taught and evaluation, this area was admittedly weaker than the other two areas in district development and teachers? perceptions. While the position of teacher leader seemed to impact the results in all categories, the grade level taught was found to have the greatest statistical impact on the teacher perceptions.Item The Sign-up Game, Sophisticated Learning and Learning Variable Demand(2009-05-15) Watugala, Megha WeerakooonThis dissertation makes contributions in topics related to mechanism design and learn-ing in game theoretic environments through three essays. The rst essay deals withthe question of mechanism design in the principal-agent model. The main contribu-tion of this essay is in extending the work by Piketty (1993). It prescribes a mechanismin incomplete informational settings where the principal is able to implement rst-best contracts while extracting the entire surplus. Importantly, the mechanism issuch that the desired outcome can be uniquely obtained when agents play the actionthat survives iterative elimination of dominated strategies. Furthermore, given themechanism, the desired outcome is shown to be a truth-revealing Nash equilibriumwhich is also Pareto-ecient. It is shown that the proposed mechanism also has thefeature that none of the agents prefer any of the other possible Nash Equilibria tothe status quo. It thus gives insights into possible mechanisms in nite agent settingsthat could improve upon the traditional second-best results.In the second essay, a model of sophisticated learning is developed where itassumes that a fraction of the population is sophisticated while the rest are adaptive learners. Sophisticated learners in the model try to maximize their cumulative payoin the entire length of the repeated game and are aware of the way adaptive learnerslearn. Sophisticated learning contrasts other models of learning which typically tendto maximize the payo for the next period by extrapolating the history of play.The sophisticated learning model is estimated on data of experiments on repeatedcoordination games where it provides evidence of such learning behavior.The third essay deals with the optimal pricing policy for a rm in an oligopolythat is uncertain about the demand it faces. The demand facing the oligopoly, whichcan be learned through their pricing policy, changes over time in a Markovian fashion.It also deduces the conditions in which learning (experimentation) is not achievableand outlines the dierent learning policies that are possible in other settings. Themodel combines the monopoly learning literature with that of the literature on pric-ing behavior of rms over business cycles. The model has interesting insights onthe pricing behavior over business cycles. It predicts that prices jump as the beliefof a possible future boom rises over a certain threshold. The model also predictscompetition to be quite vigorous following a boom while rms are predicted not toexperiment with their (pricing) policies for many periods following a bust.