English Language Learners: A Correlational Study of the Relationship Between A Proficiency Level Assessment and End of Course Test Scores at one Georgia High School

Understanding the language of one’s cultural environment is important for effective communication and function. As such, students entering U.S. schools from foreign countries are given access to English to Speakers of Other Languages (ESOL) programs and they are referred to as English Language Learner (ELL) students. This dissertation examined the correlation of ELL ACCESS Composite Performance Level (CPL) score to the End of Course tests (EOCTs) and the Georgia High School Graduation Tests (GHSGTs) in the four content courses (language arts, mathematics, science, and social studies). A premise of this study was that English language proficiency is critical in meeting or exceeding state and county assessment standards. A quantitative descriptive research design was conducted using Cross-sectional archival data from a secondary source. There were 148 participants from school years 2011-2012 to 2013- 2014 from Grades 9-12. A Pearson product moment correlation was run to assess the relationship between the ACCESS CPL (independent variable) and the EOCT scores and the GHSGT scores (dependent variables). The findings showed that there was a positive correlation between ACCESS CPL scores and the EOCT scores where language arts showed a strong positive correlation and mathematics showed a positive weak correlation. Also, there was a positive correlation between ACCESS CPL scores and GHSGT scores where language arts showed a weak positive correlation. The results of this study indicated that that there is a relationship between the stated variables, ACCESS CPL, EOCT and GHSGT. Also, the results of this study showed that there were positive correlations at varying degrees for each grade levels. While the null hypothesis for Research Question 1 and Research Question 2 were rejected, there was a slight relationship between the variables.

The Effects of the Use of Technology In Mathematics Instruction on Student Achievement

The purpose of this study was to examine the effects of the use of technology on students’ mathematics achievement, particularly the Florida Comprehensive Assessment Test (FCAT) mathematics results. Eleven schools within the Miami-Dade County Public School System participated in a pilot program on the use of Geometers Sketchpad (GSP). Three of these schools were randomly selected for this study. Each school sent a teacher to a summer in-service training program on how to use GSP to teach geometry. In each school, the GSP class and a traditional geometry class taught by the same teacher were the study participants. Students’ mathematics FCAT results were examined to determine if the GSP produced any effects. Students’ scores were compared based on assignment to the control or experimental group as well as gender and SES. SES measurements were based on whether students qualified for free lunch. The findings of the study revealed a significant difference in the FCAT mathematics scores of students who were taught geometry using GSP compared to those who used the traditional method. No significant differences existed between the FCAT mathematics scores of the students based on SES. Similarly, no significant differences existed between the FCAT scores based on gender. In conclusion, the use of technology (particularly GSP) is likely to boost students’ FCAT mathematics test scores. The findings also show that the use of GSP may be able to close known gender and SES related achievement gaps. The results of this study promote policy changes in the way geometry is taught to 10th grade students in Florida’s public schools.

Utilizing Traditional Cognitive Measures of Academic Preparation to Predict First-Year Science, Technology, Engineering, and Mathematics (STEM) Majors' Success in Math and Science Courses

For the past several years, U.S. colleges and universities have faced increased pressure to improve retention and graduation rates. At the same time, educational institutions have placed a greater emphasis on the importance of enrolling more students in STEM (science, technology, engineering and mathematics) programs and producing more STEM graduates. The resulting problem faced by educators involves finding new ways to support the success of STEM majors, regardless of their pre-college academic preparation. The purpose of my research study involved utilizing first-year STEM majors’ math SAT scores, unweighted high school GPA, math placement test scores, and the highest level of math taken in high school to develop models for predicting those who were likely to pass their first math and science courses. In doing so, the study aimed to provide a strategy to address the challenge of improving the passing rates of those first-year students attempting STEM-related courses. The study sample included 1018 first-year STEM majors who had entered the same large, public, urban, Hispanic-serving, research university in the Southeastern U.S. between 2010 and 2012. The research design involved the use of hierarchical logistic regression to determine the significance of utilizing the four independent variables to develop models for predicting success in math and science. The resulting data indicated that the overall model of predictors (which included all four predictor variables) was statistically significant for predicting those students who passed their first math course and for predicting those students who passed their first science course. Individually, all four predictor variables were found to be statistically significant for predicting those who had passed math, with the unweighted high school GPA and the highest math taken in high school accounting for the largest amount of unique variance. Those two variables also improved the regression model’s percentage of correctly predicting that dependent variable. The only variable that was found to be statistically significant for predicting those who had passed science was the students’ unweighted high school GPA. Overall, the results of my study have been offered as my contribution to the literature on predicting first-year student success, especially within the STEM disciplines.