EXPLORING THE EFFECTS OF THE RELATIONSHIP BETWEEN SCHOOL CHARACTERISTICS, TEACHER CHARACTERISTICS, ADMINISTRATIVE SUPPORT, AND SCHOOL CLIMATE ON VOLUNTARY INTRA-DISTRICT TEACHER MIGRATION

This quantitative research study utilized a binary logistic regression in a block design to investigate exogenous and endogenous factors influencing a teacher’s decision to make an intra-district move. The research focused on the following exogenous factors: classroom characteristics (size of class, percent minority, percent of students with an individualized education plan, and percent of students that are English language learners) and teacher characteristics (experience and gender). The following endogenous factors were examined: direct administrative influence (administrative support, rules enforced, school vision, teacher recognition, and job security) and indirect administrative influence (school climate, student misbehavior, parental support, materials, staff collaboration). The research was conducted by using information available from the National Center for Educational Statistics, the SASS from 2011-2012 and TFS from 2012-2013. The 2012-2013 Teacher Follow-up Survey identified 60 teachers who made a voluntary intra-district move. Results illustrate there is a statistically significant relationship between percentage of English Language Learners and overall job satisfaction and teachers choosing to make an intra-district move.

THE EFFECT OF SCHOOL CLIMATE (STUDENT AND TEACHER ENGAGEMENT) ON STUDENT PERFORMANCE

Title of Dissertation: THE EFFECT OF SCHOOL CLIMATE (STUDENT AND TEACHER ENGAGEMENT) ON STUDENT PERFORMANCE Kenneth L. Marcus, Doctor of Education, 2016 Directed By: Dr. Thomas Davis, Assistant Professor, Education Policy and Leadership, Department of Teaching and Learning, Policy and Leadership This quantitative research study was designed to compute correlations/relationships of student engagement and student achievement of fifth grade students. Secondary information was collected on the relationship of FARMS, type of school, hope, and well-being on student achievement. School leaders are charged with ensuring that students achieve academically and demonstrate their ability by meeting identified targets on state and district mandated assessments. Due to increased pressure to meet targets, principals implement academic interventions to improve student learning and overlook the benefits of a positive school climate. This study has provided information on the impact of school climate on student achievement. To conduct this study, the researcher collected two sets of public fifth grade data (Gallup Survey student engagement scores and DSA reading, mathematics, and science scores) to determine the relationship of student performance and school climate. Secondary data were also collected on teacher engagement and the percentage of students receiving FARMS to determine the effect on students. The findings from this study reinforced the belief that school climate can have a positive effect on student achievement. This study contributed quantitative data about the relationship between school climate and school achievement.

Developing Quantitative Methodologies for the Digital Humanities: A Case Study of 20th Century American Commentary on Russian Literature

Using scientific methods in the humanities is at the forefront of objective literary analysis. However, processing big data is particularly complex when the subject matter is qualitative rather than numerical. Large volumes of text require specialized tools to produce quantifiable data from ideas and sentiments. Our team researched the extent to which tools such as Weka and MALLET can test hypotheses about qualitative information. We examined the claim that literary commentary exists within political environments and used US periodical articles concerning Russian literature in the early twentieth century as a case study. These tools generated useful quantitative data that allowed us to run stepwise binary logistic regressions. These statistical tests allowed for time series experiments using sea change and emergency models of history, as well as classification experiments with regard to author characteristics, social issues, and sentiment expressed. Both types of experiments supported our claim with varying degrees, but more importantly served as a definitive demonstration that digitally enhanced quantitative forms of analysis can apply to qualitative data. Our findings set the foundation for further experiments in the emerging field of digital humanities.