Matching Items (4)
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- All Subjects: Education Policy
- Creators: Garcia, David
Description
Lead is a neurotoxin that has been shown to have a long and lasting impact on the brains, bodies, and behaviors of those who are poisoned. It also has a greater presence in communities with high levels of poverty and minority populations. Compounded over time, the effects of lead poisoning, even at low levels of exposure, impact a child's readiness and ability to learn. To investigate the relationship between the risk of lead poisoning, school level academic achievement, and community demographics, three sets of data were combined. The Lead Poisoning Risk Index (LPRI), used to quantify the risk in each census tract of being poisoned by lead, standardized state assessment data for third grade reading and eighth grade math, and census 2000 demographic data were combined to provide information for all Arizona schools and census tracts. When achievement was analyzed at the school level using descriptive, bivariate correlation, and multivariate regression analyses, lead's impact practically disappeared, exposing the powerful effect of poverty and race on achievement. At a school in Arizona, the higher the percentage of students who are poor or Hispanic, African American or Native American, these analyses' predictive models suggest there will be a greater percentage of students who fail the third grade AIMS reading and eighth grade AIMS math tests. If better achievement results are to be realized, work must be done to mitigate the effects of poverty on the lives of students. In order to improve schools, there needs to be an accounting for the context within which schools operate and a focus on improving the neighborhoods and the quality of life for the families of students.
ContributorsGehrman, Matthew Paul (Author) / Berliner, David C. (Thesis advisor) / Garcia, David (Committee member) / Danzig, Arnold (Committee member) / Arizona State University (Publisher)
Created2011
Description
Teacher mobility is a policy issue that affects students and school across the country. Despite a long-standing body of research related to teacher mobility, relatively little is known about how teacher-school pairings affect teachers’ decisions to stay at or leave their schools. Therefore, this study tested a model of teacher-school fit with a focus on the value that teachers and principals place on standardized test scores. Survey responses were collected from 382 K-8th grade public school teachers from 22 schools in two school districts. The results show that teachers who placed higher values on standardized test scores reported slightly higher levels of teacher-school fit and were slightly less likely to leave their schools within five years. Additionally, teachers’ self-assessed teacher-school fit showed a strong, positive relationship with teacher retention. These findings suggest that a better understanding of the factors that affect teachers’ sense of teacher-school fit may help reduce teacher mobility.
ContributorsVagi, Robert (Author) / Garcia, David (Thesis advisor) / Hermanns, Carl (Committee member) / Ida, Masumi (Committee member) / West, Stephen (Committee member) / Arizona State University (Publisher)
Created2017
Description
Peer coaching is an emerging approach higher education institutions are using to increase student success outcomes for first-year students. This study examined how peer coaches use their community cultural wealth with the students they coach and how coaching encouraged first-generation students to access the community cultural wealth they bring with them to college. The theoretical framework guiding this study was Yosso’s theory of community cultural wealth. I used a qualitative approach and interviewed five peer coaches and conducted focus groups with 15 first-generation, first-year students who had received coaching. Findings indicate peer coaches used the six dimensions of community cultural wealth with students they coach, including aspirational, familial, linguistic, navigational, resistant, and social capital. Students also reported peer coaching helped them access their community cultural wealth, especially as compared to advising and faculty interactions. Three key differentiators emerged when comparing coaching to other forms of support: relatability, sense of belonging, and self-confidence.
ContributorsSymonds, Sylvia (Author) / Garcia, David (Thesis advisor) / Rund, James (Committee member) / Ott, Molly (Committee member) / Arizona State University (Publisher)
Created2020
Description
Since the No Child Left Behind (NCLB) Act required classifications of students’ performance levels, test scores have been used to measure students’ achievement; in particular, test scores are used to determine whether students reach a proficiency level in the state assessment. Accordingly, school districts have started using benchmark assessments to complement the state assessment. Unlike state assessments administered at the end of the school year, benchmark assessments, administered multiple times during the school year, measures students’ learning progress toward reaching the proficiency level. Thus, the results of the benchmark assessments can help districts and schools prepare their students for the subsequent state assessments so that their students can reach the proficiency level in the state assessment. If benchmark assessments can predict students’ future performance measured in the state assessments accurately, the assessments can be more useful to facilitate classroom instructions to support students’ improvements. Thus, this study focuses on the predictive accuracy of a proficiency cut score in the benchmark assessment. Specifically, using an econometric research technique, Regression Discontinuity Design, this study assesses whether reaching a proficiency level in the benchmark assessment had a causal impact on increasing the probability of reaching a proficiency level in the state assessment. Finding no causal impact of the cut score, this study alternatively applies a Precision-Recall curve - a useful measure for evaluating predictive performance of binary classification. By using this technique, this study calculates an optimal proficiency cut score in the benchmark assessment that maximizes the accuracy and minimizes the inaccuracy in predicting the proficiency level in the state assessment. Based on the results, this study discusses issues regarding the conventional approaches of establishing cut scores in large-scale assessments and suggests some potential approaches to increase the predictive accuracy of the cut score in benchmark assessments.
ContributorsTerada, Takeshi (Author) / Chen, Ying-Chih (Thesis advisor) / Edwards, Michael (Thesis advisor) / Garcia, David (Committee member) / Arizona State University (Publisher)
Created2021