The purpose of this study was to analyze the current and pre-service conditions that can affect student teachers' preparedness to pass the science portion of the EC-6 Texas Examinations for Educator Standards (TExES), one of the mandatory certification exam to become a teacher in Texas. Two types of prediction models were employed in this study: binomial logistic regression and multiple linear regression. The independent variables used in this study were: final grade in BIOL 1082, classification of students, transfer status, taken college biology, taken college chemistry, taken college physics, taken college environmental science, taken college earth science, attending college part-time, number of credits taken during the semester, first-generation college student, relatives with degree in education, and current GPA. The dependent variable of this study was the posttest score on science portion of the EC-6 TExES practice exam. A total of 170 preservice teachers participated this study. This study used students enrolled in BIOL 1082, who volunteered to take a Biology for Educators QualtricsTM survey and the EC-6 TExES practice exam in a pretest (start of semester) and posttest (end of semester) form. The findings of this study revealed that the single best predictor of preservice teachers' performance on the science portion of EC-6 TExES practice certification examination was the Grade in BIOL 1082.

The aim of this paper is to study to what extent socio-economic factors affect the grade in social studies 1b in upper secondary school at municipal level during the period of 2015-2021. The method in this study is a binomial logistic regression and the dependent variable is the grade, and the independent variables are gender, background, parental education level and certified teacher. The data for the dependent and the independent variables are collected from the Swedish National Agency for Education's database Siris at municipal level and for the upper secondary school for the college preparatory programs. Data for 30 municipalities was collected and categorized according to the municipal group division from 2017 of Sweden's Municipalities and Regions. Pierre Bourdieu's capital theory about how education has a social stratification function is used to explain the results from the binomial logistic regression.  The result of this paper indicates that socio-economic factors affect the grade. All the independent variables affect the grade in social studies during the different years. The independent variable parental education level affected the grade in 2015-2017 and 2020/2021. The independent variable gender affected the grade in 2017-2019. Certified teacher ratio affected the grade only in 2018/2019. The independent variable background affected the grade in 2017/2018. The binomial logistic regression indicates that the residual looks similar for all municipal groups A-C for almost all the years apart from in 2017/2018. Thus, the predictive power of the binomial logistic regression model is good for all municipal groups. The results indicate that socio-economic factors affect students' grades in social studies. This is relevant for professional teachers and school principals to be aware of in order to be able to provide all the students with an equal education regardless oft their socio-economic background.

“Vision Zero,” first adopted by Sweden in 1997, is a road safety policy that aims to achieve a transportation system having zero fatalities or serious injuries for all modes of transportation. It takes a proactive approach to road safety system by identifying risk and taking steps to prevent injuries. Historically, traffic related crashes have disproportionately impacted vulnerable communities and system users including people of color, low income individuals, seniors, children, and pedestrians, bicyclists, and transit users (who typically walk to and from public transport). These inequities are addressed in the Vision Zero framework by prioritizing interventions in areas that need safety improvements the most. In 2016, the Alexandria City Council voted unanimously to develop a “Vision Zero” policy and program as a part of its updated transportation master plan. It required an initial equity analysis to assess the impact of traffic crashes on the traditionally underserved communities / groups (groups from at least one of these categories: low-income; minority; elderly; children; limited English proficiency; persons with disabilities; and/or pedestrians/ bicyclists/ transit users). This study combines three different methods to investigate the equity issues regarding traffic safety: 1) descriptive analysis of the spatial pattern of crashes and their relationship with the demographic profiles of neighborhoods at census block group level (for 2010-2014 period); 2) descriptive analysis of the crash trends in Alexandria; and 3) exploratory regression analyses for two different units of analysis (an aggregate regression analysis of crashes at census block group, and a disaggregate regression analysis of the individual level crash reports of traffic crashes). The analysis found that the elderly, school aged children, rail/subway users, and pedestrians had a higher risk of fatalities and severe injuries in traffic crashes. Higher job densities, alcohol impairment, and speeding were significantly related to higher KSI, whereas, smaller block sizes (higher number of street segments per sq. mile area of census block group), higher housing density, and use of safety equipment were related to lower KSI. / Master of Urban and Regional Planning