The purpose of the study was to compare the basic skills achievement scores of mobile and non-mobile students within the Portland Public Schools. The problem was to assess the effect of this mobility on basic skills achievement and the total educational program. The study was designed to test differences in reading, language usage and mathematics achievement test scores between pupils in the third through the eighth grades. The instrument that was used was the Portland Achievement Levels Tests of reading, language usage and math. These tests are administered to students in grades 3 - 8 in the fall and spring of each school year. A questionnaire was also designed to determine the effect of student mobility on instructional programs. This questionnaire was mailed to 81 principals with 56 responding. The Portland Public Schools computer banks were utilized to plot the basic skills test results for two groups of students: 1. The clear and intact group, which was the student who was in the same school from September through June (grades 3 - 8). 2. The mobile student (grades 3 - 8) who had a valid fall and spring test score, but from different schools. Plotting was done for the residual effect of variables in basic skill gains rather than plotting for the effects of regression. Additional analysis took place using multiple regressions by stability index, to determine the relationship between student achievement test scores and the independent variables of mobility and other independent variables (ethnic groups, gender). It was determined that student mobility and the independent variables of gender and ethnicity had no negative effect on basic skills achievement test scores. However, for the stable student, the higher the school stability index, the higher the achievement level for the non-mobile students in that school for the fall testing. The achievement gain was no different for a student in a high stability school versus a low stability school. Additionally, based on the results of the questionnaire used in the study, most principals felt that student mobility had a negative impact on instructional programs. Most of the responding principals, however, were opposed to a more structured district wide basic skills curriculum as a way of moderating the negative effects of student mobility on the educational program. Student mobility is a factor related to the success of a school academic program. It cannot, however, be taken as an answer to the low achievement of mobile students. This study concludes that all students can achieve academically, regardless of their mobility. Recommendations were made to the Portland School District that in order to facilitate and decrease the problem of student mobility, the district might wish to require that each school have a formal plan for integrating new students into the instructional program. Additionally, a more structured district wide basic skills curriculum was recommended. Suggestions for additional in-depth studies were made to determine the kinds of problems that students and school staffs encounter with school mobility. This would include a longitudinal study for students with only one valid test score during an academic year, comparing their fall or spring scores over several years and the frequency of their mobility.

The goal of this study is to investigate the predictive ability of less data intensive but widely accepted methods to estimate mobility and reliability measures. Mobility is a relatively mature concept in the traffic engineering field. Therefore, many mobility measure estimation methods are already available and widely accepted among practitioners and researchers. However, each method has their inherent weakness, particularly when they are applied and compared with real-world data. For instances, Bureau of Public Roads (BPR) Curves are very popular in static route choice assignment, as part of demand forecasting models, but it is often criticized for underperforming in congested traffic conditions where demand exceeds capacity. This study applied five mobility estimation methods (BPR Curve, Akcelic Function, Florida State University (FSU) Regression Model, Queuing Theory, and Highway Capacity Manual (HCM) Facility Procedures) for different facility types (i.e. Freeway and Arterial) and time periods (AM Peak, Mid-Day, PM Peak). The study findings indicate that the methods were able to accurately predict mobility measures (e.g. speed and travel time) on freeways, particularly when there was no congestion and the volume was less than the capacity. In the presence of congestion, none of the mobility estimation methods predicted mobility measures closer to the real-world measure. However, compared with the other prediction models, the HCM procedure method was able to predict mobility measures better. On arterials, the mobility measure predictions were not close to the real-world measurements, not even in the uncongested periods (i.e. AM Peak and Mid-Day). However, the predictions are relatively better in the AM and Mid-Day periods that have lower volume/capacity ration compared to the PM Peak period. To estimate reliability measures, the study applied three products from the Second Strategic Highway Research Program (SHRP2) projects (Project Number L03, L07, and C11) to estimate three reliability measures; the 80th percentile travel time index, 90th percentile travel time index, and 95th percentile travel time index. A major distinction between mobility estimation process and reliability estimation process lies in the fact that mobility can be estimated for any particular day, but reliability estimation requires a full year of data. Inclusion of incident days and weather condition are another important consideration for reliability measurements. The study found that SHRP2 products predicted reliability measures reasonably well for freeways for all time periods (except C11 in the PM Peak). On arterials, the reliability predictions were not close to the real-world measure, although the differences were not as drastic as seen in the case of arterial mobility measures.

Travel has been one of the sectors most severely affected by the COVID-19 pandemic. Countries have taken urgent and aggressive action to contain the spread of the virus by implementing measures such as travel bans, border closures, and lockdowns. This thesis theorizes the relationship between self-making, ethics, and travel at a time when movement has become restricted and morally questionable. It traces important ethical tensions generated by the pandemic and grounds them in different conceptualizations of uncertainty, risk, responsibility, and mobility. Through the examination of the historical and global forces that led to the globalization of movement, capital, bodies, and viruses, this work explores the new parameters of travel as produced by the pandemic and its ensuing restrictions. It argues that COVID-19 blurs the distinctions between local and global infrastructures, bodies, and forms of knowledge, rendering them increasingly difficult to maintain. By examining the unfolding of the global crisis and its effects on the practice of travel, this thesis unravels new and innovative patterns of consumption and envisions alternative futures for the tourism industry.

No description available.

Many research projects have been conducted to compare standing text entry with nomadic text entry. Other research projects have compared the input types of touchscreen and physical keyboards while texting. There is few literature that compares the two inputs types during a standing and nomadic text entry. This research was conducted to investigate the differences in error rate and characters per minute for both input types during both text entry conditions. To investigate these differences two devices were used, the iPhone 4 and the Blackberry Curve 9350, to type a phrase during both a standing and walking condition. Both characters per minute and error rate were analyzed. The investigation showed that there were no significant difference in error rate, but there was a significant difference in characters per minute. The touchscreen keyboard performed better in terms of characters per minutes and arguably performed better in accuracy.

No description available.

No description available.

No description available.

Recent research has focused attention on the concerns of migration in and out of Florida and within the counties themselves. In 1949, Cape Canaveral was established and the boom was on. The character of the state dramatically transformed after 1965, when plans were announced to convert twenty-seven thousand acres of swampland into Walt Disney World. Since then, Orlando's evolution is divided into two eras: before and after Walt Disney World. Orlando has changed from a quiet town whose function was to service the surrounding citrus growing regions in a sparsely populated Orange County to a booming metropolis. Has the growth been for the best? While geographical mobility is frequently analyzed in terms of in-migration, out-migration, and net migration, this thesis will examine the population churn, the sum of in- and out-migration divided by population size. The simple descriptive questions in this thesis are, first, how do Orange County and the Orlando metro area "stack up" against other Florida cities, counties, and metro areas such as: Tampa, Jacksonville, and Miami. Secondly, across 67 Florida counties, what county level characteristics predict the rate of churn? The sample will consist of intra-migration and intermigration movers from a dataset drawn from the 2000 U. S. Census, IRS data, and local data by county, such as, F Cat, Index Crime Rate, and Domestic Violence Rate. The U.S. Census data are compiled from the Census of 2000; most estimates come from data collected by the CPS (Current Population Survey), which the U.S. Census conducts. The Internal Revenue Service migration flow data shows migration patterns by county based on changes in the addresses entered on individual tax returns. Correlation analysis is used to show the strength of association between population churn and the other variables.

Recent literature has emphasized the importance of changes in occupation, i.e. occupational mobility, for both personal and aggregate outcomes. In this study I examine the various causes and consequences of that important decision. I begin by developing a new, generalized, model of measurement error which can fully incorporate changes in discrete classification like occupational mobility. I then use this framework to show that occupational mobility has spuriously risen in the monthly Current Population Survey. I then study the consequences of occupational mobility using a high quality 2% sample of the German Social Security Data to study how wages change around occupation and employer transitions. The results are consistent with idiosyncratic matching at the occupation, but not the employer, level. For men, wages increase by 5.5 percent following a voluntary employer transition that does not involve an occupation transition and 10.1 percent following voluntary employer transition that does involve an occupation transition. I build a model where workers differ in their cognitive, manual, and interactive skills, which creates comparative advantage in certain occupations. I estimate this model and show that most of the wage gains for young workers following an occupational transition are due to improved matching of worker skill with occupation tasks, and not simply movements to higher paying occupations. I then use the estimated model to show that the matching of workers to their comparative advantage has worsened in Germany between 1975-2010. Finally, I examine the testable implications of models of search and models of learning to see if they are consistent with the facts I have developed about occupational mobility. I find that while search models can be consistent with a number of empirical facts they, by themselves, are not able to rationalize "back-and-forth" switching that is observed in the data.