An Examination of Parental Engagement During the Middle School Years

The purpose of this quantitative study was to explore the previously unexamined phenomenon of middle school parental engagement in a large urban/suburban/rural school district of 209 schools in the mid-Atlantic region of the United States. Across 22 middle schools serving grades six-eight, this study collected and examined perceptions of the three key adult stakeholder groups – administrators, teachers, and parents – most actively involved in middle school parental engagement as described within the theoretical framework of academic socialization. Their reports of observable parental engagement activities were used to document how district stakeholders operationalize behaviors that represent the five actionable constructs and three themes of academic socialization to determine how the district “fares” in employing academic socialization as a middle school parent engagement strategy. The study also applied quantitative descriptive analysis through a one-way ANOVA to determine the significance of observable variations in actionable constructs between the perspectives of the three stakeholder groups. Finally, the study illuminated, through regression modeling, when confounding factors/independent variables such as race, income, school size, administrator and teacher experience, parents’ educational background, etc., impacted operationalization of academic socialization behaviors for middle school parent and family engagement. Rejecting the null hypothesis, the study found that the three stakeholder groups had statistically significant differences in perceptions of their implementation of activities aligned to academic socialization. This study ultimately illuminated ways in which these adult stakeholder groups share similar and varied perceptions about their engagement actions that support the achievement and maturation of middle school students. Significantly, this study provided key findings that illuminated areas that can be systemically addressed to transform middle school parent engagement practices through applied academic socialization theory into consistent and effective collaborative efforts between the home and school. The process of operationalizing academic socialization was outlined in terms that any school or district can follow to improve programs and practices of middle school parental engagement to serve in the best interests of students during this period of great transition for both child/adolescent growth and development and adult navigation of systems to provide support for students in this unique stage of growth and maturation.

SEMIPARAMETRIC METHODS IN THE ESTIMATION OF TAIL PROBABILITIES AND EXTREME QUANTILES

In quantitative risk analysis, the problem of estimating small threshold exceedance probabilities and extreme quantiles arise ubiquitously in bio-surveillance, economics, natural disaster insurance actuary, quality control schemes, etc. A useful way to make an assessment of extreme events is to estimate the probabilities of exceeding large threshold values and extreme quantiles judged by interested authorities. Such information regarding extremes serves as essential guidance to interested authorities in decision making processes. However, in such a context, data are usually skewed in nature, and the rarity of exceedance of large threshold implies large fluctuations in the distribution's upper tail, precisely where the accuracy is desired mostly. Extreme Value Theory (EVT) is a branch of statistics that characterizes the behavior of upper or lower tails of probability distributions. However, existing methods in EVT for the estimation of small threshold exceedance probabilities and extreme quantiles often lead to poor predictive performance in cases where the underlying sample is not large enough or does not contain values in the distribution's tail. In this dissertation, we shall be concerned with an out of sample semiparametric (SP) method for the estimation of small threshold probabilities and extreme quantiles. The proposed SP method for interval estimation calls for the fusion or integration of a given data sample with external computer generated independent samples. Since more data are used, real as well as artificial, under certain conditions the method produces relatively short yet reliable confidence intervals for small exceedance probabilities and extreme quantiles.

Quantitative and Qualitative Trade-Off Analysis of Drowsy Driver Detection Methods: Single Electrode Wearable EEG Device, Multi-Electrode Wearable EEG Device, and Head-Mounted Gyroscope

Drowsy driving impairs motorists’ ability to operate vehicles safely, endangering both the drivers and other people on the road. The purpose of the project is to find the most effective wearable device to detect drowsiness. Existing research has demonstrated several options for drowsiness detection, such as electroencephalogram (EEG) brain wave measurement, eye tracking, head motions, and lane deviations. However, there are no detailed trade-off analyses for the cost, accuracy, detection time, and ergonomics of these methods. We chose to use two different EEG headsets: NeuroSky Mindwave Mobile (single-electrode) and Emotiv EPOC (14- electrode). We also tested a camera and gyroscope-accelerometer device. We can successfully determine drowsiness after five minutes of training using both single and multi-electrode EEGs. Devices were evaluated using the following criteria: time needed to achieve accurate reading, accuracy of prediction, rate of false positives vs. false negatives, and ergonomics and portability. This research will help improve detection devices, and reduce the number of future accidents due to drowsy driving.

MULTI-UNIT ACCIDENT CONTRIBUTIONS TO U.S. NUCLEAR REGULATORY COMMISSION QUANTITATIVE HEALTH OBJECTIVES: A SAFETY GOAL POLICY ANALYSIS USING MODELS FROM STATE-OF-THE-ART REACTOR CONSEQUENCE ANALYSES

The U.S. Nuclear Regulatory Commission implemented a safety goal policy in response to the 1979 Three Mile Island accident. This policy addresses the question “How safe is safe enough?” by specifying quantitative health objectives (QHOs) for comparison with results from nuclear power plant (NPP) probabilistic risk analyses (PRAs) to determine whether proposed regulatory actions are justified based on potential safety benefit. Lessons learned from recent operating experience—including the 2011 Fukushima accident—indicate that accidents involving multiple units at a shared site can occur with non-negligible frequency. Yet risk contributions from such scenarios are excluded by policy from safety goal evaluations—even for the nearly 60% of U.S. NPP sites that include multiple units. This research develops and applies methods for estimating risk metrics for comparison with safety goal QHOs using models from state-of-the-art consequence analyses to evaluate the effect of including multi-unit accident risk contributions in safety goal evaluations.