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Reading Achievement of Third-Grade English Learners and Low-Socioeconomic Students in Title I and Non-Title I Schools.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Reading Achievement of Third-Grade English Learners and Low-Socioeconomic Students in Title I and Non-Title I Schools./
作者:
Saenz, Claudia V.
面頁冊數:
1 online resource (136 pages)
附註:
Source: Dissertations Abstracts International, Volume: 83-11, Section: A.
Contained By:
Dissertations Abstracts International83-11A.
標題:
Educational leadership. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28967823click for full text (PQDT)
ISBN:
9798438754992
Reading Achievement of Third-Grade English Learners and Low-Socioeconomic Students in Title I and Non-Title I Schools.
Saenz, Claudia V.
Reading Achievement of Third-Grade English Learners and Low-Socioeconomic Students in Title I and Non-Title I Schools.
- 1 online resource (136 pages)
Source: Dissertations Abstracts International, Volume: 83-11, Section: A.
Thesis (Ed.D.)--Texas A&M University - Commerce, 2022.
Includes bibliographical references
The purpose of this quantitative study was to determine whether school type (Title I versus non-Title I), English learner (EL) student percentage, and low-socioeconomic status (low-SES) student percentage could statistically predict the percentage of third-grade students who perform at the Meets Grade Level (MGL) performance on the State of Texas Assessments of Academic Readiness (STAAR) Reading exam in the 2018-2019 school year on the campus level. This quantitative study used a multiple linear regression model to examine the predictive relationship between these variables. Multiple linear regression was used to determine whether these three predictor variables had a statistically significant predictive relationship with the third-grade STAAR Reading MGL percentage of the campus. Additionally, correlation tests were another statistical method used. The correlations were used to measure the strength of the linear relationship between each of the independent variables and the dependent variable. The data used in this study were derived from a requested Texas Education Agency (TEA) report and the TEA public website. The sample size was calculated through statistical power analysis using G*Power analysis and other recommendations. Campuses were identified using stratified sampling and the findings from this study provide a better understanding as to whether school type, EL percentage, and low-SES percentage in third grade can predict the student MGL performance on the STAAR Reading exam of third-grade students on a campus. The results of this study may start a conversation about the possibility of socioeconomic and EL integration in Texas public schools. Socioeconomic and EL integration refers to low-SES students and ELs being combined with non-ELs and higher SES students in a higher-average SES school. Another implication of this study suggests that the use of culturally responsive teaching is a pedagogy that academically supports ELs and low-SES students, as well as other minorities and students of color. Further, the findings illuminate how the leadership role of the administrator can help them improve student achievement. Stakeholders can utilize these findings and implications for immediate insight and decision-making to support an equitable education for EL and low-SES students.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023
Mode of access: World Wide Web
ISBN: 9798438754992Subjects--Topical Terms:
529436
Educational leadership.
Subjects--Index Terms:
Achievement gapIndex Terms--Genre/Form:
542853
Electronic books.
Reading Achievement of Third-Grade English Learners and Low-Socioeconomic Students in Title I and Non-Title I Schools.
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Source: Dissertations Abstracts International, Volume: 83-11, Section: A.
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The purpose of this quantitative study was to determine whether school type (Title I versus non-Title I), English learner (EL) student percentage, and low-socioeconomic status (low-SES) student percentage could statistically predict the percentage of third-grade students who perform at the Meets Grade Level (MGL) performance on the State of Texas Assessments of Academic Readiness (STAAR) Reading exam in the 2018-2019 school year on the campus level. This quantitative study used a multiple linear regression model to examine the predictive relationship between these variables. Multiple linear regression was used to determine whether these three predictor variables had a statistically significant predictive relationship with the third-grade STAAR Reading MGL percentage of the campus. Additionally, correlation tests were another statistical method used. The correlations were used to measure the strength of the linear relationship between each of the independent variables and the dependent variable. The data used in this study were derived from a requested Texas Education Agency (TEA) report and the TEA public website. The sample size was calculated through statistical power analysis using G*Power analysis and other recommendations. Campuses were identified using stratified sampling and the findings from this study provide a better understanding as to whether school type, EL percentage, and low-SES percentage in third grade can predict the student MGL performance on the STAAR Reading exam of third-grade students on a campus. The results of this study may start a conversation about the possibility of socioeconomic and EL integration in Texas public schools. Socioeconomic and EL integration refers to low-SES students and ELs being combined with non-ELs and higher SES students in a higher-average SES school. Another implication of this study suggests that the use of culturally responsive teaching is a pedagogy that academically supports ELs and low-SES students, as well as other minorities and students of color. Further, the findings illuminate how the leadership role of the administrator can help them improve student achievement. Stakeholders can utilize these findings and implications for immediate insight and decision-making to support an equitable education for EL and low-SES students.
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