Understanding students' technology appropriation and learning perceptions in online learning environments

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file viewed on (May 25, 2006)Includes bibliographical references.Vita.Thesis (Ph. D.) University of Missouri-Columbia 2005.Dissertations, Academic -- University of Missouri--Columbia -- Information science and learning technologies.Distance education has the unique characteristic of using technologies as the primary means of delivery of instruction and interaction. The present study contributes to research dedicated to explaining or predicting phenomena related to distance education, and has four objectives: (1) to identify specific social and technological factors affecting online students' behavior of using technology, (2) to conceptualize a theoretical model to better represent the relationships among the salient factors, (3) to examine how the elements in the theoretical model influence students' learning perceptions and satisfaction in the distance education program, and (4) to compare the proposed model with prior work to model and explain online behavior and satisfaction. For the purpose of advancing understanding of the roles of social and technological factors in a distance learning environment, this study proposed a unified theoretical model based upon four attitude-behavior models, the Theory of Reasoned Action (TRA), the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the decomposed TPB. By reviewing and identifying salient factors in each model, this study attempts to construct a measurable Unified Model of Technology Appropriation (UMTA) integrating the identified factors so as to best overcome the limitations of each model. The study investigated a distance education program providing both a physical and virtual place to support enrolled students in a Midwest state university to learn knowledge and skills by doing. Instructional materials and supports were delivered through a network-based learning system as well as other communication tools. Data collection included self-report questionnaires and computer-recorded system usage data. Among the statistically significant paths found in UMTA, subjective norm (instructor/mentor/peer influence) had the strongest relationship to students' technology appropriation behavior, while perceived behavioral control (self-efficacy and technology/resource facilitating conditions) had the strongest impact on students' satisfaction. These findings have important implications for system designers, online educators, and distance education program managers. In order to reduce students' frustration, not only online instructors but also program managers need to provide and assure the availability of external supports including mentoring and technical supports. System designers, on the other hand, have to enhance the system's ease of use through good design and by providing clear instructions. Results of the present study should help to better manage online courses by focusing attention on social influences and control factors in a distance education program.

A reflective e-learning approach for reading, thinking, and behavioral engagement

One of the main goals of the English as a Foreign Language (EFL) course is to facilitate the development of learners’ reading comprehension and reflective skills in English, which can be developed with appropriate instruction. However, in EFL courses, many students are inactive in reflecting on their reading and are disengaged from learning. To fill this gap, a reflective reading-based e-learning approach was proposed to explore the impact of the suggested approach on reading comprehension, reflective thinking, and behavioral engagement. The study aimed to improve the comprehension of the student’s reading using the proposed reflective e-learning approach. The study employed a quasi-experimental design in which the experimental group used reflective reading-based e-learning (n = 51) and the control group used conventional e-learning (n = 50) for a total of 13 weeks of participation. The experiment was designed to examine reading comprehension, reflective thinking, and behavioral engagement (e.g., reading time, Marker list, Quiz score, Memo list). The results revealed that the reflective reading-based e-learning approach could improve the comprehension and reflective thinking of the learners and promote behavioral engagement. These findings can be valuable for educators designing strategies to improve students’ reading comprehension skills and stimulate behavioral engagement in e-learning systems

Critical Neurons: optimized visual recognition in a neuronal network

In the past few decades, there have been intense debates whether the brain operates at a critical state. To verify the criticality hypothesis in the neuronal networks is challenging and the accumulating experimental and theoretical results remain controversial at this point. Here we simulate how visual information of a nature image is processed by the finite Kinouchi-Copelli neuronal network, extracting the trends of the mutual information (how sensible the neuronal network is), the dynamical range (how sensitive the network responds to external stimuli) and the statistical fluctuations (how criticality is defined in conventional statistical physics). It is rather remarkable that the optimized state for visual recognition, although close to, does not coincide with the critical state where the statistical fluctuations reach the maximum. Different images and/or network sizes of course lead to differences in details but the trend of the information optimization remains the same. Our findings pave the first step to investigate how the information processing is optimized in different neuronal networks and suggest that the criticality hypothesis may not be necessary to explain why a neuronal network can process information smartly.Comment: 11 pages, 4 figures in the main text and 3 figures in the Supplementary Informatio

Classification of multipartite entanglement containing infinitely many kinds of states

We give a further investigation of the range criterion and Low-to-High Rank Generating Mode (LHRGM) introduced in \cite{Chen}, which can be used for the classification of $2\times{M}\times{N}$ states under reversible local filtering operations. By using of these techniques, we entirely classify the family of $2\times4\times4$ states, which actually contains infinitely many kinds of states. The classifications of true entanglement of $2\times(M+3)\times(2M+3)$ and $2\times(M+4)\times(2M+4)$ systems are briefly listed respectively.Comment: 11 pages, revte

Did the S.A.R.S. epidemic weaken the integration of Asian stock markets? Evidence from smooth time-varying cointegration analysis

The purpose of this study is to examine the effect of the Severe Acute Respiratory Syndrome (S.A.R.S.) epidemic on the long-run relationship between China and four Asian stock markets. To this end, we first employ the advanced smooth time-varying cointegration model to investigate the existence of a time-varying cointegration relation among these markets and then employ the difference-indifferences approach to analyse whether or not the S.A.R.S. epidemic impacted the long-run relation between China and these four markets during the period 1998–2008, covering 5 years before and after the S.A.R.S. outbreak. Our results support the existence of a time-varying cointegration relation in the aggregate stock price indices, and that the S.A.R.S. epidemic did weaken the long-run relationship between China and the four markets. Therefore, stockholders and policy makers should be concerned about the influence of catastrophic epidemic diseases on the financial integration of stock market in Asia

Unusual case of spontaneous uterine rupture in a single gestational primipara

AbstractSpontaneous rupture of the primiparous uterus is a rare but catastrophic obstetrical emergency. It is usually associated with prior uterine surgery, trauma, or placental abnormality. To remind physicians to include this condition in their differential diagnosis of acute abdominal pain in pregnant patients, we describe an interesting case of spontaneous uterine rupture that clinically mimicked bowel perforation. A 27-year-old single primiparous pregnant woman presented with sudden onset of severe abdominal pain and peritoneal signs, with absence of vaginal bleeding at 26 weeks’ gestation. The usual risk factors for uterine rupture, such as advanced maternal age, scarred uterus due to mode of previous delivery, or unusual pregnancy, were not present in our patient. Based on clinical examination, abdominal sonography and magnetic resonance imaging, uterine rupture was suspected and eventually confirmed at exploratory laparotomy. No uterine pathological abnormality was noted on the microscopic examination The preterm newborn expired after surgery. Since surgical intervention is the only definitive treatment, emergency physicians should be aware of this rare complication. Emergency physicians should be aware of spontaneous uterine rupture in pregnant patients, even in the absence of risk factors