Page 121 |
Save page Remove page | Previous | 121 of 194 | Next |
|
small (250x250 max)
medium (500x500 max)
Large (1000x1000 max)
Extra Large
large ( > 500x500)
Full Resolution
All (PDF)
|
This page
All
|
115 the data published by government agencies and higher education institutions report on progress made in college access, and not necessarily on student transfer success rates. Budgetary constraints and general resource issues has made it even more difficult for community colleges to have institutional researchers who can gather and analyze the effects of their programs and their policies. The only data community colleges have available to them are those collected from K-12 institutions or from neighboring four-year institutions (Venezia, Kirst and Antonio, 1997). A recent publication by the Institute for High Education Leadership and Policy exhorted the State of California to adopt data systems as a means to understand student success/failure rates at the community college level and application of that knowledge towards institutional change and responsiveness (Moore and Shulock, 2010). To that end, data systems that will track graduates’ progress in transferring to four-year universities, and assess current and future institutional practice need to be created so that information is available to make strategic decisions that will produce positive results for students. Of course, data use needs to be grounded in institutional learning that effectively frames diversity and equity outcomes. Despite increased focus on educational accountability and diversity, there has historically been a lack of attention on procuring equitable outcomes for traditionally underrepresented students of color. The University of Southern California’s Center for Urban Education (CUE) has focused on shaping institutional learning and data systems to confront and change the “educational outcomes for students with a history of exclusion, discrimination, and disenfranchisement (i.e.
Object Description
Title | Improving college participation success in Glendale Unified School District: An application of the gap analysis model |
Author | Cassady, Dawn Marie |
Author email | Kedwyn@aol.com; cassady@usc.edu |
Degree | Doctor of Education |
Document type | Dissertation |
Degree program | Education (Leadership) |
School | Rossier School of Education |
Date defended/completed | 2011-01-22 |
Date submitted | 2011 |
Restricted until | Unrestricted |
Date published | 2011-04-29 |
Advisor (committee chair) | Marsh, David D. |
Advisor (committee member) |
Rueda, Robert S. Arias, Robert J. |
Abstract | From the time of Brown v. Board of Education, the role of education has been on the forefront of our social, political and economic landscape. Legislation such as the Elementary and Secondary Education Act and No Child Left Behind as well as publications like A Nation at Risk have all illustrated the lack of access, equity and achievement in American schools for the last fifty years. Currently, the United States has a 69% average high school graduation rate, which varies between subgroups and of those students only 57% continue their education in college.; Glendale Unified School District (GUSD) is a high-performing, large, urban school district that serves an economically and culturally diverse population. This project examined the root causes of the gaps in college going rates for all students as well as those of the underrepresented subgroups by applying the Clark and Estes (2005) gap analysis model. Gaps between goal achievement (college participation) and actual student performance were examined and then research-based solutions for closing the achievement gap and recommendations based on those solutions were recommended to the school district administrative team. |
Keyword | secondary education; school reform; college access |
Geographic subject | school districts: Glendale Unified School District |
Geographic subject (county) | Los Angeles |
Geographic subject (state) | California |
Geographic subject (country) | USA |
Coverage date | 1954/2010 |
Language | English |
Part of collection | University of Southern California dissertations and theses |
Publisher (of the original version) | University of Southern California |
Place of publication (of the original version) | Los Angeles, California |
Publisher (of the digital version) | University of Southern California. Libraries |
Provenance | Electronically uploaded by the author |
Type | texts |
Legacy record ID | usctheses-m3806 |
Contributing entity | University of Southern California |
Rights | Cassady, Dawn Marie |
Repository name | Libraries, University of Southern California |
Repository address | Los Angeles, California |
Repository email | cisadmin@lib.usc.edu |
Filename | etd-Cassady-4360 |
Archival file | uscthesesreloadpub_Volume14/etd-Cassady-4360.pdf |
Description
Title | Page 121 |
Contributing entity | University of Southern California |
Repository email | cisadmin@lib.usc.edu |
Full text | 115 the data published by government agencies and higher education institutions report on progress made in college access, and not necessarily on student transfer success rates. Budgetary constraints and general resource issues has made it even more difficult for community colleges to have institutional researchers who can gather and analyze the effects of their programs and their policies. The only data community colleges have available to them are those collected from K-12 institutions or from neighboring four-year institutions (Venezia, Kirst and Antonio, 1997). A recent publication by the Institute for High Education Leadership and Policy exhorted the State of California to adopt data systems as a means to understand student success/failure rates at the community college level and application of that knowledge towards institutional change and responsiveness (Moore and Shulock, 2010). To that end, data systems that will track graduates’ progress in transferring to four-year universities, and assess current and future institutional practice need to be created so that information is available to make strategic decisions that will produce positive results for students. Of course, data use needs to be grounded in institutional learning that effectively frames diversity and equity outcomes. Despite increased focus on educational accountability and diversity, there has historically been a lack of attention on procuring equitable outcomes for traditionally underrepresented students of color. The University of Southern California’s Center for Urban Education (CUE) has focused on shaping institutional learning and data systems to confront and change the “educational outcomes for students with a history of exclusion, discrimination, and disenfranchisement (i.e. |