Evaluation

The purpose of this study was to examine the Computer-Assisted Instructional (CAI) method as an alternative to the Traditional method of instruction for the lowest level of remediation in the content areas of mathematics, reading, and sentence skills, and to specifically determine the comparative effectiveness of these two delivery modes in terms of student success, retention, and costs. The researcher aimed to (a) determine the extent to which ACCUPLACERª mean scores for CAI participants increase based on pre and post measures, (b) investigate the pros and cons fiscally of each method of delivery (CAI vs. Traditional), respectively, (c) examine whether CAI participants are more likely to enroll during the immediately following semester compared to students enrolled in a Traditional course, and (d) investigate the extent to which CAI participants are equally or more likely to complete successfully the course taken during the immediately following semester compared to students enroll ed in a Traditional course. The study consisted of a two-group design (CAI and Traditional), and four dependent variables. All CAI participants (N = 129) were self-selected to participate in the study. A dependent t-test found that CAI participants increased their ACCUPLACER mean scores significantly over time by 22.74 points or 72.6%. A frequency count found that retention rates were slightly higher for the Traditional group (82.3%) in comparison to the CAI group (76.6%), however, chi-square tests did not reveal a statistical significance. Chi-squares found significant increase in success rates for the CAI group as 86% passed their initial course, in comparison to 59.8% of students taught in the Traditional format. CAI participants were found to have greater success (74.1%) in subsequent classes than students taught via the Traditional instructional method (51.9%).

This work presents the development of the Statistical Location-Assisted Broadcast (SLAB) protocol, a multi-hop wireless broadcast protocol designed for vehicular ad-hoc networking (VANET). Vehicular networking is an important emerging application of wireless communications. Data dissemination applications using VANET promote the ability for vehicles to share information with each other and the wide-area network with the goal of improving navigation, fuel consumption, public safety, and entertainment. A critical component of these data dissemination schemes is the multi-hop wireless broadcast protocol. Multi-hop broadcast protocols for these schemes must reliably deliver broadcast packets to vehicles in a geographically bounded region while consuming as little wireless bandwidth as possible. This work contains substantial research results related to development of multi-hop broadcast protocols for VANET, culminating in the design of SLAB. Many preliminary research and development efforts have been required to arrive at SLAB. First, a high-level wireless broadcast simulation tool called WiBDAT is developed. Next, a manual optimization procedure is proposed to create efficient threshold functions for statistical broadcast protocols. This procedure is then employed to design the Distribution-Adaptive Distance with Channel Quality (DADCQ) broadcast protocol, a preliminary cousin of SLAB. DADCQ is highly adaptive to node density, node spatial distribution pattern, and wireless channel quality in realistic VANET scenarios. However, the manual design process used to create DADCQ has a few deficiencies. In response to these problems, an automated design procedure is created that uses a black-box global optimization algorithm to search for efficient threshold functions that are evaluated using WiBDAT. SLAB is finally designed using this procedure.

This study describes analytical model as one innovative way to simulate Light Rail Transit (LRT) operations and calculate vehicular, transit and person delays at LRT crossings through Microsoft Excel. Analytical model emulates LRT trajectories from field and use these trajectories to clearly define train and car phases through Visual Basic for Applications (VBA) logic, which is part of analytical model. Simulation of train trajectories and calculations of delays were done for different LRT strategies and estimated roadway condition, Testing and validation of analytical model were performed in one case study in Salt Lake City (UT). Results show that analytical model is capable of emulating LRT trajectories and estimating delay at isolated LRT crossing. However, analytical model is not capable of simulating different train strategies at two or more LRT crossings, at the same time. Finally, extracted strategy provides savings from $100.000 to $200.000 in study area, on annual basis for projected year.

Standard GPS receivers are unable to provide the rate or precision required when used on a small vessel such as an Unmanned Surface Vehicles (USVs). To overcome this, the thesis presents a low cost high rate motion measurement system for an USV with underwater and oceanographic purposes. The work integrates an Inertial Measurement Unit (IMU), a GPS receiver, a flux-gate compass, a tilt sensor and develops a software package, using real time data fusion methods, for an USV to aid in the navigation and control as well as controlling an onboard Acoustic Doppler Current Profiler (ADCP).While ADCPs non-intrusively measure water flow, they suffer from the inability to discriminate between motions in the water column and self-motion. Thus, the vessel motion contamination needs to be removed to analyze the data and the system developed in this thesis provides the motion measurements and processing to accomplish this task.

The purpose of this study was to investigate the self-directed learning (SDL) readiness of third-year medical students in comparison to previously reported scores for the general population; the relationship between SDL readiness and knowledge-based and performance-based measures of success in a medical school using an integrated medical curriculum; and to determine if knowledge-based and performance-based measures of success are significant in predicting Self-Directed Learning Readiness Survey/Learner Preference Assessment (SDLRS/LPA) and National Board of Medical Examiners Family Medicine Shelf Examination (NBME-FM) scores. This study analyzed SDLRS/LPA scores, knowledge-based scores (NBME-FM), performance-based scores (Objective Structured Clinical Examination [OSCE] and preceptor rating), and a combination of knowledge-based and performance-based scores (final grade). Analyses of 873 students resulted in mean scores of 229.06 + 23.19 for the SDLRS/LPA. Correlations were significant (p < .05) for SDLRS/LPA scores to NBME-FM scores (r = .073, p < .05). OSCE scores (r = .133, p < .01), and final grade (r = .138, p < .01). Regression analysis revealed that the total model of NBME-FM, OSC AVG, and preceptor rating predicted 2.1% of the variation in SDLRS/LPA, which was significant (p < .01). Regression analysis revealed that SDLRS/LPA, OSC AVG and preceptor ratings predicted 9.7% of the variance in NBME-FM, which was significant (p < .001). The results support previous findings that medical students' levels of SDL readiness are higher than the general population mean of 214.0 + 23.49.

The objective of this study was to determine whether 11 independent variables or combinations of variables help to predict a diabetes-related hospital readmission for patients with diabetes within 60 days from discharge. The variables were categorized into four main groups: (a) patient characteristics, (b) lifestyle, (c) biomarkers, and (d) disease management aspects. A convenience sample of 389 historical medical records of patients who were admitted to a rural hospital in northeastern North Carolina with a diagnosis of, or relating to, diabetes was studied. After comparing predictive discriminant analysis (PDA) and logistic regression (LR), PDA performed better and was chosen to analyze a convenience sample of patients admitted to the hospital for a diabetes-related diagnosis from January, 2004 to December, 2006. The best overall subset accurately classified 27 cases with six predictors that included (a) systolic blood pressure, (b) smoking status, (c) blood glucose range, (d) ethnicity, (e) diabetes education, and (f) diastolic blood pressure. In an effort to simplify the prediction process, the subsets of two predictors were examined. The results of the analysis returned four subsets of 2-predictor variable combinations that correctly classified cases for readmission. Each of the four subsets has two predictors that are statistically and practically significant for predicting readmissions for a diabetes-related problem within fewer than 60 days. These combinations are the predictor subsets of (a) smoking status and being treated by a specialist or non-specialist physician, (b) a religious affiliation or a lack thereof and smoking status, (c) gender and smoking status, and (d) smoking status and ethnicity.

The purpose of this study was to examine students' preferred methods of academic advising services and whether they related to their individual learning styles. The first objective of the study was to determine each participant's learning style. The second objective of the study was to determine which method of academic advising each participant preferred. The third objective of the study was to determine whether a relationship existed between the participants' learning styles and preferred methods of academic advising. Additionally, the moderating effect of gender, ethnicity, college major, high school grade point average (GPA), location, and employment on the relationship was considered. Students' learning styles were measured by the Barsch Learning Style Inventory (BLSI). Academic advising preference and demographic information were gathered through a researcher-designed questionnaire. All students (N=1,184) who completed the Online Advising & Registration System (OARS) were cont acted via e-mail and received a web link to the BLSI and student questionnaire. Data from the students (n=172) who completed the BLSI and student questionnaire were analyzed. Correlation and multiple regression analysis were used to analyze the quantitative data. A qualitative analysis of four open-ended survey questions was completed. The results found no relationship between participants' learning styles and their preferred methods of academic advising services. Additionally, gender, ethnicity, college major, high school GPA, location, and employment did not moderate the relationship between participants' learning styles and their preferred methods of academic advising services. The findings suggest that a student's learning style is not associated with his or her preference for type of advising.

This research is concerned with the technoeconomic aspects of modern and next-generation telecommunications including the Internet service. The goal of this study thereof is tailored to address the following: (i) Reviewing the technoeconomic considerations prevailing in telecommunication (telco) systems and their implicating futures; (ii) studying relevant considerations by depicting the modern/next-generation telecommunications as a digital ecosystem viewed in terms of underlying complex system evolution (akin to biological systems); (iii) pursuant to the digital ecosystem concept, co-evolution modeling of competitive business structures in the technoeconomics of telco services using dichotomous (flip-flop) states as seen in prey-predator evolution; (iv) specific to Internet pricing economics, deducing the profile of consumer surplus versus pricing model under DiffServ QoS architecture pertinent to dynamic- , smart- and static-markets; (v) developing and exemplifying decision-making pursuits in telco business under non-competitive and competitive markets (via gametheoretic approach); (vi) and modeling forecasting issues in telco services addressed in terms of a simplified ARIMA-based time-series approach, (which includes seasonal and non-seasonal data plus goodness-fit estimations in time- and frequency-domains). Commensurate with the topics indicated above, necessary analytical derivations/models are proposed and computational exercises are performed (with MatLabTM R2006b and other software as needed). Extensive data gathered from open literature are used thereof and, ad hoc model verifications are performed. Lastly, results are discussed, inferences are made and open-questions for further research are identified.

The goal of this thesis is to develop a test platform for measuring surface effect ship (SES) response to wave loads. The platform is designed and built incorporating a self-propelled vehicle with data acquisition and navigation capabilities. Theoretical analysis is performed, various hardware and electronic parts are designed and built and software applications developed. Wave tank experiments are conducted for test platform evaluation and determination of vehicle response to a range of wave conditions. Furthermore, a three-dimensional model of the AIRCAT scale model SES is created. The theoretical analysis shows that the scale effects in some cases are great, so resonance phenomena cannot be observed. The experimental results clearly show that the heave, pitch and aircushion excess pressure fluctuations increase as the air-blower input level increases. The bow skirt arrangement needs improvements and further experimentation is necessary in order to draw conclusions about the wave loads applied on the skirt.

The Internet has revolutionized the way in which people are entertained, communicate and collect information. As people increase their ability to connect with the outside world from inside their homes, they hold the power to become their own gatekeepers filtering information as they see fit. Many question whether this will weaken the power of the traditional media sources that are often seen as elitist and potentially biased. This researcher hypothesized that people who cite high credibility ratings of news media channels are more likely to use traditional media channels such as television and newspapers and people who cite low credibility ratings of news media channels are more likely to use alternate media channels such as the Internet. While the researcher was unable to reject the null hypothesis, a pattern of general mistrust of traditional news media was revealed when nearly three-fourths of respondents gave traditional media channels a "not-credible" rating.