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45
of setting high expectations, it is not readily implemented (Mac Iver & Farley, 2003,
Datnow, 2005). In order for this approach to be engrained in the school community, it
must be a part of a greater effort of improving student performance. Data-based decision
making is a critical component to helping schools reach the high expectations they have
set for their students.
Data-Based Decision Making. After high expectations are solidified and goals
are set, data-based decision making becomes a key lever to meeting hose high
expectations. Johnson (2002), Weiss (2007), Boudett & Steele (2007), Datnow, Park, and
Wohlstetter (2006), and EdSource (2006) state that when teachers use data to inform
instruction, considerable improvements in student results are evident. Weiss (2007) and
Datnow, et. al., (2006) state that before data can be utilized, a foundation for effective use
must be established which includes a culture of open data use and continuous
improvement, investment in data storage systems, utilizing the correct data, building the
ability and capacity for data to be used at the school site, and finally acting upon and
driving instruction based on the data. Fisher & Frey (2007) stress the importance of
systematic formative assessments to collect data on student achievement and to guide
instruction. These authors contend that using data goes beyond state standardized test
results, and that teachers must continually check for understanding during the school
year. Johnson (2002) recommends having leadership and data teams to lead a school-wide
effort in using data in every aspect of instructional practice—this can be data from
formative and summative classroom assessments to state-wide standardized assessments.
Object Description
| Title | Allocation of educational resources to improve student achievement: Case studies of four California charter schools |
| Author | Patrick, Ramona Kay |
| Author email | rpatrick@usc.edu; ramonakaypatrick@gmail.com |
| Degree | Doctor of Education |
| Document type | Dissertation |
| Degree program | Education (Leadership) |
| School | Rossier School of Education |
| Date defended/completed | 2011-03-28 |
| Date submitted | 2011 |
| Restricted until | Unrestricted |
| Date published | 2011-05-04 |
| Advisor (committee chair) | Picus, Lawrence O. |
| Advisor (committee member) |
Hentschke, Guilbert C. Nelson, John L. |
| Abstract | Charter schools are growing at a rapid pace have significantly more flexibility in their allocation of resources in comparison to their traditional public school counterparts in California. Because of this, it is important to study how successful charter schools, with this increased flexibility, are utilizing their resources to achieve high results with their students in a time of fiscal constraint. There is a plethora of data and research on effective school practices to improve student achievement, but a dearth of research on the effective allocation of resources at charter schools. The purpose of this study is to analyze how four high performing charter schools, with high percentages of socioeconomically disadvantaged students in Los Angeles, California, are implementing school improvement strategies and utilizing resources at their school site to impact student achievement. The Evidenced-Based Model, (Odden & Picus, 2008) along with Odden and Archibald’s (2009) Ten Strategies for Doubling Student Performance were used as a lens in this study to compare resource allocation as well as school improvement strategies to best support student achievement at the schools. This study will describe each schools’ instructional vision and improvement strategy, how resources are utilized to implement their instructional improvement plan, how the current fiscal crisis is affecting their allocation of resources, and how actual resource patterns are aligned with the Evidence Based Model (Odden & Picus, 2008). |
| Keyword | charter schools; resource allocation; evidenced-based model |
| Geographic subject (state) | California |
| Geographic subject (country) | USA |
| Coverage date | 2000/2010 |
| 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-m3815 |
| Contributing entity | University of Southern California |
| Rights | Patrick, Ramona Kay |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Patrick-4438 |
| Archival file | uscthesesreloadpub_Volume51/etd-Patrick-4438.pdf |
Description
| Title | Page 53 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 45 of setting high expectations, it is not readily implemented (Mac Iver & Farley, 2003, Datnow, 2005). In order for this approach to be engrained in the school community, it must be a part of a greater effort of improving student performance. Data-based decision making is a critical component to helping schools reach the high expectations they have set for their students. Data-Based Decision Making. After high expectations are solidified and goals are set, data-based decision making becomes a key lever to meeting hose high expectations. Johnson (2002), Weiss (2007), Boudett & Steele (2007), Datnow, Park, and Wohlstetter (2006), and EdSource (2006) state that when teachers use data to inform instruction, considerable improvements in student results are evident. Weiss (2007) and Datnow, et. al., (2006) state that before data can be utilized, a foundation for effective use must be established which includes a culture of open data use and continuous improvement, investment in data storage systems, utilizing the correct data, building the ability and capacity for data to be used at the school site, and finally acting upon and driving instruction based on the data. Fisher & Frey (2007) stress the importance of systematic formative assessments to collect data on student achievement and to guide instruction. These authors contend that using data goes beyond state standardized test results, and that teachers must continually check for understanding during the school year. Johnson (2002) recommends having leadership and data teams to lead a school-wide effort in using data in every aspect of instructional practice—this can be data from formative and summative classroom assessments to state-wide standardized assessments. |
