2016 Texas Public School Rankings Methodology

Children and Youth;Education and Literacy

2016 Texas Public School Rankings Methodology

Each year, CHILDREN AT RISK reexamines its methodology of ranking schools to ensure that the rankings most accurately reflects school performance, utilizes the most appropriate data available, and incorporates feedback from educators, researchers, and service providers.

CHILDREN AT RISK is pleased to have completed the 2016 Annual School Rankings.

  • Student Achievement Index – Performance on STAAR Reading and Math tests
  • Campus Performance Index – An adjustment of achievement indicators to eliminate bias toward campuses with low percentages of economically disadvantaged students
  • Growth Index – The improvement over time on standardized test scores in Reading, English, and Math
  • College Readiness Index - graduation rates, SAT/ACT participation rate and scores, and AP/IB participation rate and scores

August 1970

Geographic Focus: North America / United States (Southwestern) / Texas

2016 Texas Public School Rankings Methodology

Children and Youth;Education and Literacy

2016 Texas Public School Rankings Methodology

Each year, CHILDREN AT RISK reexamines its methodology of ranking schools to ensure that the rankings most accurately reflects school performance, utilizes the most appropriate data available, and incorporates feedback from educators, researchers, and service providers.

CHILDREN AT RISK is pleased to have completed the 2016 Annual School Rankings.

  • Student Achievement Index – Performance on STAAR Reading and Math tests
  • Campus Performance Index – An adjustment of achievement indicators to eliminate bias toward campuses with low percentages of economically disadvantaged students
  • Growth Index – The improvement over time on standardized test scores in Reading, English, and Math
  • College Readiness Index - graduation rates, SAT/ACT participation rate and scores, and AP/IB participation rate and scores

August 1970

Geographic Focus: North America / United States (Southwestern) / Texas

2016 Texas Public School Rankings Methodology

Children and Youth;Education and Literacy

2016 Texas Public School Rankings Methodology

Each year, CHILDREN AT RISK reexamines its methodology of ranking schools to ensure that the rankings most accurately reflects school performance, utilizes the most appropriate data available, and incorporates feedback from educators, researchers, and service providers.

CHILDREN AT RISK is pleased to have completed the 2016 Annual School Rankings.

  • Student Achievement Index – Performance on STAAR Reading and Math tests
  • Campus Performance Index – An adjustment of achievement indicators to eliminate bias toward campuses with low percentages of economically disadvantaged students
  • Growth Index – The improvement over time on standardized test scores in Reading, English, and Math
  • College Readiness Index - graduation rates, SAT/ACT participation rate and scores, and AP/IB participation rate and scores

August 1970

Geographic Focus: North America / United States (Southwestern) / Texas

Connecting the Dots: Data Use in Afterschool Systems

Children and Youth;Education and Literacy

Connecting the Dots: Data Use in Afterschool Systems

Afterschool programs are seen as a way to keep low-income children safe and to foster the skills needed to succeed in school and life. Many cities are creating afterschool systems to ensure that such programs are high-quality and widely available. One way to do so is to ensure afterschool systems develop and maintain a data system.This interim report presents early findings from a study of how afterschool systems build their capacity to understand and improve their practices through their data systems. It examines afterschool data systems in nine cities that are part of The Wallace Foundation’s Next Generation Afterschool System-Building initiative, a multi-year effort to strengthen systems that support access to and participation in high-quality afterschool programs for low-income youth. The cities are Baltimore, Md., Denver, Colo., Fort Worth, Texas, Grand Rapids, Mich., Jacksonville, Fla.,Louisville, Ky., Nashville, Tenn., Philadelphia, Pa., and Saint Paul, Minn.To date, research on data use in afterschool systems has focused more on the implementation of technology than on what it takes to develop and sustain effective data use. This study found that the factors that either enabled or hampered the use of data in afterschool systems—such as norms and routines, partner relationships, leadership and coordination, and technical knowledge—had as much to do with the people and process components of the systems as with the technology.Strategies that appear to contribute to success include:

  •     Starting small. A number of cities intentionally started with a limited set of goals for data collection and use, and/or a limited set of providers piloting a new data system, with plans to scale up gradually.
  •     Ongoing training. Stakeholders learned that high staff turnover required ongoing introductory trainings to help new hires use management information systems and data. Providing coaching and developing manuals also helped to mitigate the effects of turnover and to further the development of more experienced and engaged staff.
  •     Outside help. Systems varied in how they used the expertise of outside research partners. Some cities identified a research partner who participated in all phases of the development of their data systems. Others used the relationship primarily to help analyze and report data collected by providers. Still others did not engage external research partner, but identified internal staff to support the system. In any of these scenarios, dedicated staffers with skills in data analytics were key.

 

August 1970

Geographic Focus: North America / United States (Midwestern) / Minnesota / Ramsey County / St. Paul;North America / United States (Southern) / Florida / Duval County / Jacksonville;North America / United States (Southern) / Maryland / Baltimore;North America / United States (Southwestern) / Texas / Tarrant County / Fort Worth;North America / United States (Western) / Colorado / Denver County;North America / United States (Northeastern) / Pennsylvania / Philadelphia County / Philadelphia;North America / United States (Southern) / Tennessee / Davidson County / Nashville;North America / United States (Midwestern) / Michigan / (Western) / Kent County / Grand Rapids;North America / United States (Southern) / Kentucky / Jefferson County / Louisville

Connecting the Dots: Data Use in Afterschool Systems

Children and Youth;Education and Literacy

Connecting the Dots: Data Use in Afterschool Systems

Afterschool programs are seen as a way to keep low-income children safe and to foster the skills needed to succeed in school and life. Many cities are creating afterschool systems to ensure that such programs are high-quality and widely available. One way to do so is to ensure afterschool systems develop and maintain a data system.This interim report presents early findings from a study of how afterschool systems build their capacity to understand and improve their practices through their data systems. It examines afterschool data systems in nine cities that are part of The Wallace Foundation's Next Generation Afterschool System-Building initiative, a multi-year effort to strengthen systems that support access to and participation in high-quality afterschool programs for low-income youth. The cities are Baltimore, Md., Denver, Colo., Fort Worth, Texas, Grand Rapids, Mich., Jacksonville, Fla.,Louisville, Ky., Nashville, Tenn., Philadelphia, Pa., and Saint Paul, Minn.To date, research on data use in afterschool systems has focused more on the implementation of technology than on what it takes to develop and sustain effective data use. This study found that the factors that either enabled or hampered the use of data in afterschool systems—such as norms and routines, partner relationships, leadership and coordination, and technical knowledge—had as much to do with the people and process components of the systems as with the technology.Strategies that appear to contribute to success include:

  •     Starting small. A number of cities intentionally started with a limited set of goals for data collection and use, and/or a limited set of providers piloting a new data system, with plans to scale up gradually.
  •     Ongoing training. Stakeholders learned that high staff turnover required ongoing introductory trainings to help new hires use management information systems and data. Providing coaching and developing manuals also helped to mitigate the effects of turnover and to further the development of more experienced and engaged staff.
  •     Outside help. Systems varied in how they used the expertise of outside research partners. Some cities identified a research partner who participated in all phases of the development of their data systems. Others used the relationship primarily to help analyze and report data collected by providers. Still others did not engage external research partner, but identified internal staff to support the system. In any of these scenarios, dedicated staffers with skills in data analytics were key.

 

August 1970

Geographic Focus: North America / United States (Midwestern) / Minnesota / Ramsey County / St. Paul;North America / United States (Southern) / Florida / Duval County / Jacksonville;North America / United States (Southern) / Maryland / Baltimore;North America / United States (Southwestern) / Texas / Tarrant County / Fort Worth;North America / United States (Western) / Colorado / Denver County;North America / United States (Northeastern) / Pennsylvania / Philadelphia County / Philadelphia;North America / United States (Southern) / Tennessee / Davidson County / Nashville;North America / United States (Midwestern) / Michigan / (Western) / Kent County / Grand Rapids;North America / United States (Southern) / Kentucky / Jefferson County / Louisville

Connecting the Dots: Data Use in Afterschool Systems

Children and Youth;Education and Literacy

Connecting the Dots: Data Use in Afterschool Systems

Afterschool programs are seen as a way to keep low-income children safe and to foster the skills needed to succeed in school and life. Many cities are creating afterschool systems to ensure that such programs are high-quality and widely available. One way to do so is to ensure afterschool systems develop and maintain a data system.This interim report presents early findings from a study of how afterschool systems build their capacity to understand and improve their practices through their data systems. It examines afterschool data systems in nine cities that are part of The Wallace Foundation’s Next Generation Afterschool System-Building initiative, a multi-year effort to strengthen systems that support access to and participation in high-quality afterschool programs for low-income youth. The cities are Baltimore, Md., Denver, Colo., Fort Worth, Texas, Grand Rapids, Mich., Jacksonville, Fla.,Louisville, Ky., Nashville, Tenn., Philadelphia, Pa., and Saint Paul, Minn.To date, research on data use in afterschool systems has focused more on the implementation of technology than on what it takes to develop and sustain effective data use. This study found that the factors that either enabled or hampered the use of data in afterschool systems—such as norms and routines, partner relationships, leadership and coordination, and technical knowledge—had as much to do with the people and process components of the systems as with the technology.Strategies that appear to contribute to success include:

  •     Starting small. A number of cities intentionally started with a limited set of goals for data collection and use, and/or a limited set of providers piloting a new data system, with plans to scale up gradually.
  •     Ongoing training. Stakeholders learned that high staff turnover required ongoing introductory trainings to help new hires use management information systems and data. Providing coaching and developing manuals also helped to mitigate the effects of turnover and to further the development of more experienced and engaged staff.
  •     Outside help. Systems varied in how they used the expertise of outside research partners. Some cities identified a research partner who participated in all phases of the development of their data systems. Others used the relationship primarily to help analyze and report data collected by providers. Still others did not engage external research partner, but identified internal staff to support the system. In any of these scenarios, dedicated staffers with skills in data analytics were key.

 

August 1970

Geographic Focus: North America / United States (Midwestern) / Minnesota / Ramsey County / St. Paul;North America / United States (Southern) / Florida / Duval County / Jacksonville;North America / United States (Southern) / Maryland / Baltimore;North America / United States (Southwestern) / Texas / Tarrant County / Fort Worth;North America / United States (Western) / Colorado / Denver County;North America / United States (Northeastern) / Pennsylvania / Philadelphia County / Philadelphia;North America / United States (Southern) / Tennessee / Davidson County / Nashville;North America / United States (Midwestern) / Michigan / (Western) / Kent County / Grand Rapids;North America / United States (Southern) / Kentucky / Jefferson County / Louisville

Lessons From the Local Level: DACA's Implementation and Impact on Education and Training Success

Education and Literacy;Immigration

Lessons From the Local Level: DACA's Implementation and Impact on Education and Training Success

This report examines the ways in which local educational institutions, legal service providers, and immigrant youth advocates have responded to the first phase of Deferred Action for Childhood Arrivals (DACA). Based on extensive interviews with stakeholders in seven states -- California, Florida, Georgia, Illinois, Maryland, New York, and Texas -- the report identifies initiatives undertaken by educational institutions and other community stakeholders to support DACA youth's education and training success, and examine the impact of deferred action on grantees' academic and career pursuits. It provides examples of promising practices, additional challenges, and key takeaways at the high school, postsecondary, and adult education levels, as well as an exploration of the nature and scope of DACA legal outreach initiatives.

August 1970

Geographic Focus: North America / United States (Midwestern) / Illinois;North America / United States (Northeastern) / New York;North America / United States (Southern) / Florida;North America / United States (Southern) / Georgia;North America / United States (Southern) / Maryland;North America / United States (Southwestern) / Texas;North America / United States (Western) / California

Building Community Partnerships in Support of a Postsecondary Completion Agenda

Education and Literacy

Building Community Partnerships in Support of a Postsecondary Completion Agenda

This report highlights key lessons from the Bill & Melinda Gates Foundation's Community Partnerships portfolio evaluation. It assesses the communities' progress over the course of the investment, and describes their work in the areas of building public commitment, using data, building and sustaining partnerships, and aligning policies and practices. The OMG Center served as the national evaluator of this initiative and the report also discusses the steps these communities can take to sustain their programs.

August 1970

Geographic Focus: North America / United States (Midwestern) / Ohio / Montgomery County / Dayton;North America / United States (Northeastern) / Massachusetts / Suffolk County / Boston;North America / United States (Southern) / Florida / Duval County / Jacksonville;North America / United States (Southern) / North Carolina / Mecklenburg County / Charlotte;North America / United States (Southwestern) / Arizona / Maricopa County / Phoenix;North America / United States (Western) / California / San Francisco County / San Francisco;North America / United States (Northwestern) / Oregon / Multnomah County / Portland;North America / United States (Northeastern) / New York / New York County / New York City;North America / United States (Northeastern) / Pennsylvania / Philadelphia County / Philadelphia;North America / United States (Southern) / North Carolina / Wake County / Raleigh;North America / United States (Southern) / Kentucky / Jefferson County / Louisville;North America / United States (Southwestern) / Arizona / Maricopa County / Mesa;North America / United States (Southwestern) / Texas / Cameron County / Brownsville;North America / United States (Southwestern) / Texas / Potter County / Amarillo;North America / United States (Western) / California / Riverside County / Riverside

See More Reports

Go to IssueLab