This document provides a technical guide for common college completion metrics adopted by Complete College America. It outlines outcome, progress, and context metrics for measuring degree production, graduation rates, transfer rates, remedial education, credit accumulation, retention, and enrollment at the state level. The purpose is to inform the public and policymakers about college completion, identify areas for improvement, show progress over time, and ensure accountability. Data will be collected uniformly to allow for comparisons across states and institutions.
USDOL IMPAQ International Capstone Report (Final Client Version) (2)Stephanie Koo
This document provides a summary and analysis of performance measurement tools used in U.S. workforce development programs. It evaluates the effectiveness, efficiency, and equity of key elements of the Workforce Investment Act (WIA) performance management system, including performance measurement, data collection, and incentives. The analysis draws on literature review, application of a principal-agent framework, and quantitative analysis of performance data from several states. It identifies several issues with the current system, such as an exclusive focus on effectiveness that may preclude other goals, data lags that limit accountability, and inconsistencies in reported data. The document concludes with seven recommendations for improving performance management under the new Workforce Innovation and Opportunity Act.
- North Carolina currently has 47 Educator Preparation Programs that provide students with the knowledge and skills to become licensed teachers. These programs collect and report data to state oversight bodies for approval and accountability purposes.
- The state produces almost 100 annual Educator Preparation Program Performance Reports and Report Cards using the reported data. However, the dispersion of data across these reports and lack of uniform metrics makes comparative assessment difficult.
- New legislation strengthened accountability but also introduced challenges, such as sanctioning programs based on small, disaggregated student subgroups. The state has an opportunity to adopt a streamlined, performance-based reporting model to better reflect priorities and assess programs.
Information and-communications-technologies-ict-strategic2439Munir ZD
This document provides a strategic plan for Information and Communications Technologies (ICT) at Monash University from 2006-2010. It outlines the university's ICT planning pyramid which aligns the ICT plan with the university's overall strategic planning process. The plan identifies critical strategic initiatives in research, education, administration, and core ICT infrastructure to support the university's academic directions. These initiatives include e-research programs, learning management systems, enterprise resource planning, and improvements to data centers, networking, security and other foundational technologies. The plan is intended to guide investment and leadership in ICT over the next five years to enable the university's teaching, research and operations.
Developmental Education in Kansas and the Nationjwillia8
This document provides an overview of developmental metrics in Kansas. It summarizes data on college readiness, remediation rates, completion of remediation courses, and graduation rates. Some key points are:
- Kansas scores above the national average on the ACT and in all college readiness subject areas.
- About 40% of students entering 2-year colleges and 18% entering 4-year colleges in Kansas require remediation.
- African American, Hispanic, and low-income students are more likely to require remediation.
- Less than 60% of students complete remediation courses, and only about 20% and 35% of students at 2- and 4-year colleges complete associated college courses within two
This document provides a summary and draft recommendations from Florida's Blue Ribbon Task Force on State Higher Education Reform. It catalogs previous recommendations from other reports and outlines draft recommendations in the areas of accountability, funding, and governance. The key recommendations include:
1. Enhancing the Board of Governor's accountability framework to focus on outcome-based metrics like employment rates, degrees in strategic areas, cost per graduate, and graduate salaries.
2. Differentiating tuition rates between universities and programs, with no tuition increases for 3 years for high-skill, high-wage degrees that are important to the state economy.
3. Rewarding "Preeminent Universities" that meet specific metrics with more flexibility in
This document provides guidance for states on implementing performance funding for higher education institutions. It outlines 11 principles for designing an effective performance funding system, including getting agreement on clear state goals, using metrics that are difficult to manipulate, and ensuring incentives align with goals. The principles are meant to help states avoid pitfalls of prior performance funding attempts and focus institutions on key priorities like increasing degrees and certificates awarded. The document also provides examples from states that have implemented performance funding successfully.
The document outlines essential steps for states to measure progress and success in college completion. It recommends that states uniformly collect and publicly report data using key metrics like graduation rates, remediation rates, credit accumulation, and time to degree. This will allow states to diagnose challenges, identify opportunities for improvement, and be accountable for students' success. The document suggests states measure interim milestones and outcomes to drive completion, and disaggregate data by student demographics to close achievement gaps.
The document is a draft report from the Florida Blue Ribbon Task Force on State Higher Education Reform. It contains an introduction outlining the task force's focus on accountability, funding, and governance of the state university system. It also includes a summary of the strengths and weaknesses of the current state university system governance structure centered around the Board of Governors. The task force aims to provide recommendations to improve performance and innovation within the university system.
USDOL IMPAQ International Capstone Report (Final Client Version) (2)Stephanie Koo
This document provides a summary and analysis of performance measurement tools used in U.S. workforce development programs. It evaluates the effectiveness, efficiency, and equity of key elements of the Workforce Investment Act (WIA) performance management system, including performance measurement, data collection, and incentives. The analysis draws on literature review, application of a principal-agent framework, and quantitative analysis of performance data from several states. It identifies several issues with the current system, such as an exclusive focus on effectiveness that may preclude other goals, data lags that limit accountability, and inconsistencies in reported data. The document concludes with seven recommendations for improving performance management under the new Workforce Innovation and Opportunity Act.
- North Carolina currently has 47 Educator Preparation Programs that provide students with the knowledge and skills to become licensed teachers. These programs collect and report data to state oversight bodies for approval and accountability purposes.
- The state produces almost 100 annual Educator Preparation Program Performance Reports and Report Cards using the reported data. However, the dispersion of data across these reports and lack of uniform metrics makes comparative assessment difficult.
- New legislation strengthened accountability but also introduced challenges, such as sanctioning programs based on small, disaggregated student subgroups. The state has an opportunity to adopt a streamlined, performance-based reporting model to better reflect priorities and assess programs.
Information and-communications-technologies-ict-strategic2439Munir ZD
This document provides a strategic plan for Information and Communications Technologies (ICT) at Monash University from 2006-2010. It outlines the university's ICT planning pyramid which aligns the ICT plan with the university's overall strategic planning process. The plan identifies critical strategic initiatives in research, education, administration, and core ICT infrastructure to support the university's academic directions. These initiatives include e-research programs, learning management systems, enterprise resource planning, and improvements to data centers, networking, security and other foundational technologies. The plan is intended to guide investment and leadership in ICT over the next five years to enable the university's teaching, research and operations.
Developmental Education in Kansas and the Nationjwillia8
This document provides an overview of developmental metrics in Kansas. It summarizes data on college readiness, remediation rates, completion of remediation courses, and graduation rates. Some key points are:
- Kansas scores above the national average on the ACT and in all college readiness subject areas.
- About 40% of students entering 2-year colleges and 18% entering 4-year colleges in Kansas require remediation.
- African American, Hispanic, and low-income students are more likely to require remediation.
- Less than 60% of students complete remediation courses, and only about 20% and 35% of students at 2- and 4-year colleges complete associated college courses within two
This document provides a summary and draft recommendations from Florida's Blue Ribbon Task Force on State Higher Education Reform. It catalogs previous recommendations from other reports and outlines draft recommendations in the areas of accountability, funding, and governance. The key recommendations include:
1. Enhancing the Board of Governor's accountability framework to focus on outcome-based metrics like employment rates, degrees in strategic areas, cost per graduate, and graduate salaries.
2. Differentiating tuition rates between universities and programs, with no tuition increases for 3 years for high-skill, high-wage degrees that are important to the state economy.
3. Rewarding "Preeminent Universities" that meet specific metrics with more flexibility in
This document provides guidance for states on implementing performance funding for higher education institutions. It outlines 11 principles for designing an effective performance funding system, including getting agreement on clear state goals, using metrics that are difficult to manipulate, and ensuring incentives align with goals. The principles are meant to help states avoid pitfalls of prior performance funding attempts and focus institutions on key priorities like increasing degrees and certificates awarded. The document also provides examples from states that have implemented performance funding successfully.
The document outlines essential steps for states to measure progress and success in college completion. It recommends that states uniformly collect and publicly report data using key metrics like graduation rates, remediation rates, credit accumulation, and time to degree. This will allow states to diagnose challenges, identify opportunities for improvement, and be accountable for students' success. The document suggests states measure interim milestones and outcomes to drive completion, and disaggregate data by student demographics to close achievement gaps.
The document is a draft report from the Florida Blue Ribbon Task Force on State Higher Education Reform. It contains an introduction outlining the task force's focus on accountability, funding, and governance of the state university system. It also includes a summary of the strengths and weaknesses of the current state university system governance structure centered around the Board of Governors. The task force aims to provide recommendations to improve performance and innovation within the university system.
This document discusses using data to drive instruction and student learning. It emphasizes using multiple sources of student data, including standardized tests, observations, conversations and student work, to identify learning goals and diagnose student strengths and needs. The document also discusses tools like data disaggregation and student work analysis protocols to help teachers understand what students know and still need to learn in order to improve instruction. Finally, it provides information on the Common Core State Standards and 21st century skills emphasized by the Partnership for 21st Century Skills.
This document discusses the creation of a system-wide data warehouse called the Common Data Repository and Electronic Data Warehouse (CDR/EDW) by the Tennessee Board of Regents (TBR) to facilitate data-driven decision making. It aims to organize student data from all TBR institutions to allow for data mining and analytics at the system level. The document outlines some challenges to implementing such a data warehouse, presents case studies of similar projects, and provides recommendations for effective use of the CDR/EDW, including potential questions it could help answer across multiple institutions.
North Carolina has made progress implementing its Race to the Top education reforms over four years, including adopting more rigorous academic standards, increasing teacher and principal professional development, and establishing a statewide technology system called Home Base. While the full effects on student achievement may not be seen for years, reforms have impacted classrooms, schools, and the state education agency. Next steps include sustaining reforms and using lessons learned to better support districts and schools.
The document discusses developing a growth model and data visualization system for a school district. It proposes a three-phase approach: 1) Discovering growth model requirements through interviews and observations, 2) Developing technical and design specifications for data visualization, and 3) Implementing and documenting the system. The methodology for phase 1 involves on-site interviews with district and school leaders, teachers, and parents to understand their needs. Phases 2 and 3 involve designing the data warehouse, dashboards, and visualizations to analyze student performance data and factors affecting learning based on requirements. Training and support will be provided to help users understand and utilize the system.
Police and Fire On-Line Courseware Training Trends and Evaluation StudyInteract Business Group
This document provides an overview and summary of a study on online courseware trends and evaluation for fire service training. It finds that while online learning has grown for fire departments, there is a lack of standardized quality evaluation of courses. The study analyzed 12 common courses from multiple vendors using a scoring system. It found wide variation in course quality and costs. Key conclusions are that a centralized evaluation system and online library is needed to help departments identify high-quality, cost-effective courseware.
Dr. Fred C. Lunenburg - measurement and assessment in schools schooling v1 n1...William Kritsonis
Dr. Fred C. Lunenburg, www.nationalforum, NATIONAL FORUM JOURNALS, Houston, Texas, Dr. William Allan Kritsonis, Editor-in-Chief,
www.nationalforum.com
National Refereed Journals
Major Activities Performed regarding Planning.pdfDrHafizKosar
A planning framework serves as the fundamental structure guiding the process of planning. This framework encompasses various key components, each with its own distinctive role in the planning process. Let's delve into each of these components in more detail, accompanied by illustrative examples:
1. Principles: Principles are fundamental rules or concepts that guide decision-making. For instance, a company may have a principle of sustainability that influences all its planning decisions, ensuring a commitment to environmental responsibility.
2. Vision: The vision is a broad and aspirational description of the desired outcome of the planning process. An example could be a city's vision to become a "green and sustainable metropolis" in the next decade, setting the tone for urban planning and development.
3. Problem: Problems represent undesirable conditions that planning aims to address, whether by solving, reducing, or compensating for them. In the context of public health, a problem might be the high prevalence of a specific disease, prompting a planning effort to mitigate its impact.
4. Goals: Goals are overarching, often abstract conditions that planning aims to achieve, such as wealth, health, equity, or freedom. For a non-profit organization, a goal might be to improve community well-being, which then informs more specific planning efforts.
5. Objectives: Objectives are specific and potentially quantifiable ways to attain broader goals. For instance, if the goal is to enhance educational equity, an objective could be to increase the number of scholarships awarded to underprivileged students.
6. Targets or standards: These are quantitative levels that objectives should reach. In the case of reducing carbon emissions, a target could be to achieve a 20% reduction by 2030.
7. Performance Indicators: These are practical metrics used to measure progress toward objectives. If the objective is to improve public transportation, performance indicators might include on-time arrival rates, passenger satisfaction surveys, and ridership numbers.
8. Plans: Plans outline a scheme or a set of actions to achieve specific objectives. For instance, a business might create a strategic plan for expanding into new markets or an action plan for launching a new product line.
9. Options: Options are various possible ways to achieve an objective or solve a problem. In urban planning, options might include increasing public transportation, promoting cycling infrastructure, or implementing congestion pricing to reduce traffic.
10. Policies or Strategies: These are courses of action implemented by jurisdictions or organizations. A government might adopt a policy of tax incentives to promote renewable energy as part of its environmental strategy.
11. Programs: Programs are specific sets of objectives, responsibilities, and tasks within an organization. An educational institution might establish a program to improve literacy, which includes curriculum development, teacher
States are increasingly using early warning systems to identify students at risk of falling off track to graduation. These systems analyze data like attendance, behavior, and course performance to predict which students may need additional support. States provide this early warning data to districts, schools, teachers, counselors, and parents to help guide intervention efforts. While more states are developing early warning systems, most only provide the data periodically or upon request. Going forward, states aim to better support stakeholders in using predictive analytics to keep students on a path to both high school graduation and future career or college readiness.
Using Data to Improve Minority-Serving Institution SuccessDawn Follin
This document discusses how Minority-Serving Institutions (MSIs) can better use data to improve student and institutional success and meet national college completion goals. It outlines that MSIs have traditionally educated underserved student populations but some are not fully utilizing data to assess areas for improvement. The document recommends that MSIs adopt interim measures to track student progress and success at multiple points along their educational pathway, such as placement upon entry, persistence in continuous enrollment, progression toward earning a credential, and ultimate completion. These interim measures can provide a more comprehensive view of student outcomes than traditional metrics like graduation rates alone.
Kindergarten Entry Assessments and Early Learning Challenge Grantselccollaboration
This document summarizes key aspects of developing Kindergarten Entry Assessments (KEAs) and their role in Early Learning Challenge Grants. It outlines the definition and purposes of KEAs, scoring criteria, types of assessment instruments, examples, and components of an effective KEA system. It also discusses developing a high quality plan and budget for implementing KEAs that can be used to inform instruction and close readiness gaps while meeting grant requirements.
ow-a-days data volumes are growing rapidly in several domains. Many factors have contributed to this growth, including inter alia proliferation of observational devices, miniaturization of various sensors ,improved logging and tracking of systems, and improvements in the quality and capacity of both disk storage and networks .Analyzing such data provides insights that can be used to guide decision making. To be effective, analysis must be timely and cope with data scales. The scale of the data and the rates at which they arrive make manual inspection infeasible. As an educational management tool, predictive analytics can help and improve the quality of education by letting decision makers address critical issues such as enrollment management and curriculum Development. This paper presents an analytical study of this approach’s prospects for education planning. The goals of predictive analytics are to produce relevant information, actionable insight, better outcomes, and smarter decisions, and to predict future events by analyzing the volume, veracity, velocity, variety, value of large amounts of data and interactive exploration.
The document provides instructions for educators on how to create custom reports in DataDirector to analyze classroom data. It outlines how to select relevant data points, build a custom report with multiple columns of data, and download the report into Excel. Educators can then use conditional formatting in Excel to identify the bottom 30% of students in a particular subject area based on assessment results. The final customized report allows educators to make informed instructional decisions and determine necessary student interventions.
192020 Capella University Scoring Guide Toolhttpsscor.docxaulasnilda
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 1/7
MHA-FP5064
u03a1 - Health Information System Implementation
Learner: Monna , Joseph
OVERALL COMMENTS
Mona
This paper is not very clear and specific. You have very genialized explanations of data and are not discussing
data requirements from meaningful use and merit-based incentives. Also you are not supporting the data needs
with CURRENT academic sources. You only have 2 references both from well over 10 years ago. You need
research current trends and best practices from recent sources.
See the rubric below for more specifics.
RUBRICS
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 2/7
CRITERIA 1
Outline a plan for collecting and analyzing data.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not outline a plan for collecting and analyzing data.
BASIC:
Outlines a plan for collecting and analyzing data that is impracticable or unlikely to yield limited data for
analysis.
PROFICIENT: Outlines a plan for collecting and analyzing data.
DISTINGUISHED:
Outlines a plan for collecting and analyzing data. Provides a concise and well-articulated outline that
identifies specific data needs and a clear approach to analysis.
Comments:
I am not see a plan that alignes with current trends in health care. Plan needs to address specific data that
would common in an EHR and meet current legislative requirments.
(20%)
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 3/7
CRITERIA 2
Propose criteria for evaluating organizational needs.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not propose criteria for evaluating organizational needs.
BASIC:
Proposes criteria for evaluating organizational needs that may lead to erroneous conclusions.
PROFICIENT: Proposes criteria for evaluating organizational needs.
DISTINGUISHED:
Proposes criteria for evaluating organizational needs, and provides relevant, credible evidence that
clearly validates the proposed criteria.
Comments:
Very unclear and is not alinging with best practices from AHIMA, HIMSS or Health IT,gov. Research
current oversight organizations
(16%)
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 4/7
CRITERIA 3
Outline a plan for generating reports.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not outline a plan for generating reports.
BASIC:
Outlines a plan for generating reports that is impracticable or unlikely to provide all of the information
necessary to support sound decision making.
PROFICIENT: Outlines a ...
The document summarizes the Common Core State Standards Initiative, which aims to establish consistent K-12 standards in English and math that can be adopted by states. It discusses the importance of common standards, the momentum behind the initiative with 48 states and territories signed on, and outlines the process used to develop the standards with input from states and educators. It also emphasizes that fully implementing the standards will require changes to classroom instruction, materials, assessments, and policies to support student achievement.
Data Driven Instructional Decision MakingA framework.docxwhittemorelucilla
Data Driven
Instructional Decision Making
A framework
Data –Driven Instruction
Data-driven instruction is characterized by cycles
that provide a feedback loop
in which teachers plan and deliver instruction, assess student
understanding through the collection of data, analyze the data, and
then pivot instruction based on insights from their analysis.
From: Teachers know best: Making Data Work For Teachers and Students
Bill & Melinda Gates Foundation
https://s3.amazonaws.com/edtech-production/reports/Gates-TeachersKnowBest-MakingDataWork.pdf
Data-Driven Decision Making Process Cycle
Data Planning
and
Production
Data Analysis
Developing
an Action
Plan
Monitoring
progress
Measuring
Success
Implementing
the Action
Plan
Data is used
From : Teachers know best: Making Data Work For Teachers and Students
Bill & Melinda Gates Foundation
https://s3.amazonaws.com/edtech-production/reports/Gates-
TeachersKnowBest-MakingDataWork.pdf
Data –Driven Instruction Feedback Loop
Data Planning
and
Production
Data Analysis
Developing an
Action Plan
Monitoring
progress
Measuring
Success
Implementing
the Action
Plan
Data –Driven Instruction Feedback Loop
Data Planning
and
Production
Data Analysis
Developing an
Action Plan
Monitoring
progress
Measuring
Success
Implementing
the Action
Plan
Instructors need to
facilitate this data –driven
instruction decision loop
in a timely and smooth
fashion
…and on an ongoing basis
• Per student
• Per class
• Per group
Data –Driven Instruction Feedback Loop
Roles Inherent in the Data-Driven Instruction
Decision Making Loop
• Planner
• Data Producer
• Data Analyst
• Monitor
• Reporter
• Data End User
• IT
• Operations and Logistics
Data Planning and Production Questions
• What questions are to be addressed in future data-informed
conversations? Which questions are more important?
• What information (metrics) are needed to answer these question?
• Is the information available and feasibly attainable?
• Are the necessary technology and resources available?
• How can current non-data based instructional decision making be
mapped to data-based instructional decision making process?
• What are the costs associated with this endeavor?
• What are the timelines ?
• How and when will the data be collected and stored?
Data Analysis Questions
• What relations exists between the metrics? What patterns do
the data reveal?
• How many levels of the metric are needed to answer the
questions?
• Do the original questions need to be revised or expanded?
• Do the original metrics need to be redefined or expanded?
• What analytical tools are currently available? What tools
need to be designed to support the analysis?
• What method of analysis or evaluation will be used?
• What are the data limitations, strengths, challenges, context?
Monitor Questions
• How are the metrics evolving as the learning and instructional
processes evolve.
This document provides an overview of the Common Core State Standards and the transition to Common Core-aligned assessments. It discusses how the Common Core requires higher standards that focus on deeper learning rather than superficial coverage of many topics. It also explains how assessments will change from primarily multiple choice to include more innovative item types like performance tasks and technology-enhanced questions to better measure skills like writing, problem-solving, and analytical thinking. The document provides resources and timelines to help educators understand what is required and plan their transition to meet Common Core requirements by the 2014-2015 deadline.
This document provides guidance on developing a School Improvement Plan (SIP). It explains that a SIP is a formal, structured approach to managing school resources to achieve optimal performance. A SIP committee of 7-10 individuals oversees the process. Key steps in developing a SIP include conducting a self-evaluation, identifying priorities, preparing draft and final plans through consultation, implementation, monitoring and evaluation on an annual basis. The SIP should be aligned with national priorities and the school's annual self-evaluation.
The document provides an overview of online learning for secondary education, noting that an estimated 1.5 million secondary students participated in some form of online learning in 2010, with opportunities available in 48 states and Washington D.C. through various providers. While online learning has become popular due to its potential to provide more flexible access and assemble instructional content more efficiently, the document also notes some proponents see technology as having potential to expand communities of learners and support models of participatory education.
Recent trends and issues in assessment and evaluationROOHASHAHID1
1. The document discusses recent trends and issues in educational assessment and evaluation. It covers topics such as putting students at the center, building capacity at all levels of education systems, managing local needs, greater use of technology, and shifts towards more holistic and demonstration-based forms of assessment.
2. Key trends discussed include expanding the scope of evaluation beyond just student assessment, increasing use of data and technology to enhance assessment, and growing internationalization and standardization of assessment.
3. Issues addressed involve ensuring appropriate and valid assessment methods that align with learning objectives, evaluating new skills developed through technology, and considering the policy impacts of assessment.
The document is the final report of the Florida Blue Ribbon Task Force on State Higher Education Reform from November 2012. It provides recommendations on accountability, funding, and governance for the Florida State University System. The task force organized their work around these three areas and provided a strengths/weaknesses analysis of the system. They recommend a set of linked accountability, funding, and governance changes intended to improve understanding between universities and funding stakeholders and help the system better demonstrate its value and operational innovation.
The document is a draft report from the Florida Blue Ribbon Task Force on State Higher Education Reform. It includes a letter from the chair introducing the task force's work over 6 months to assess the state university system. The draft report contains sections on strengths and weaknesses of the system, and recommendations related to accountability, funding, and governance. It emphasizes the complexity of higher education issues and the need for the university system to improve its standing and contributions to the state.
This document discusses using data to drive instruction and student learning. It emphasizes using multiple sources of student data, including standardized tests, observations, conversations and student work, to identify learning goals and diagnose student strengths and needs. The document also discusses tools like data disaggregation and student work analysis protocols to help teachers understand what students know and still need to learn in order to improve instruction. Finally, it provides information on the Common Core State Standards and 21st century skills emphasized by the Partnership for 21st Century Skills.
This document discusses the creation of a system-wide data warehouse called the Common Data Repository and Electronic Data Warehouse (CDR/EDW) by the Tennessee Board of Regents (TBR) to facilitate data-driven decision making. It aims to organize student data from all TBR institutions to allow for data mining and analytics at the system level. The document outlines some challenges to implementing such a data warehouse, presents case studies of similar projects, and provides recommendations for effective use of the CDR/EDW, including potential questions it could help answer across multiple institutions.
North Carolina has made progress implementing its Race to the Top education reforms over four years, including adopting more rigorous academic standards, increasing teacher and principal professional development, and establishing a statewide technology system called Home Base. While the full effects on student achievement may not be seen for years, reforms have impacted classrooms, schools, and the state education agency. Next steps include sustaining reforms and using lessons learned to better support districts and schools.
The document discusses developing a growth model and data visualization system for a school district. It proposes a three-phase approach: 1) Discovering growth model requirements through interviews and observations, 2) Developing technical and design specifications for data visualization, and 3) Implementing and documenting the system. The methodology for phase 1 involves on-site interviews with district and school leaders, teachers, and parents to understand their needs. Phases 2 and 3 involve designing the data warehouse, dashboards, and visualizations to analyze student performance data and factors affecting learning based on requirements. Training and support will be provided to help users understand and utilize the system.
Police and Fire On-Line Courseware Training Trends and Evaluation StudyInteract Business Group
This document provides an overview and summary of a study on online courseware trends and evaluation for fire service training. It finds that while online learning has grown for fire departments, there is a lack of standardized quality evaluation of courses. The study analyzed 12 common courses from multiple vendors using a scoring system. It found wide variation in course quality and costs. Key conclusions are that a centralized evaluation system and online library is needed to help departments identify high-quality, cost-effective courseware.
Dr. Fred C. Lunenburg - measurement and assessment in schools schooling v1 n1...William Kritsonis
Dr. Fred C. Lunenburg, www.nationalforum, NATIONAL FORUM JOURNALS, Houston, Texas, Dr. William Allan Kritsonis, Editor-in-Chief,
www.nationalforum.com
National Refereed Journals
Major Activities Performed regarding Planning.pdfDrHafizKosar
A planning framework serves as the fundamental structure guiding the process of planning. This framework encompasses various key components, each with its own distinctive role in the planning process. Let's delve into each of these components in more detail, accompanied by illustrative examples:
1. Principles: Principles are fundamental rules or concepts that guide decision-making. For instance, a company may have a principle of sustainability that influences all its planning decisions, ensuring a commitment to environmental responsibility.
2. Vision: The vision is a broad and aspirational description of the desired outcome of the planning process. An example could be a city's vision to become a "green and sustainable metropolis" in the next decade, setting the tone for urban planning and development.
3. Problem: Problems represent undesirable conditions that planning aims to address, whether by solving, reducing, or compensating for them. In the context of public health, a problem might be the high prevalence of a specific disease, prompting a planning effort to mitigate its impact.
4. Goals: Goals are overarching, often abstract conditions that planning aims to achieve, such as wealth, health, equity, or freedom. For a non-profit organization, a goal might be to improve community well-being, which then informs more specific planning efforts.
5. Objectives: Objectives are specific and potentially quantifiable ways to attain broader goals. For instance, if the goal is to enhance educational equity, an objective could be to increase the number of scholarships awarded to underprivileged students.
6. Targets or standards: These are quantitative levels that objectives should reach. In the case of reducing carbon emissions, a target could be to achieve a 20% reduction by 2030.
7. Performance Indicators: These are practical metrics used to measure progress toward objectives. If the objective is to improve public transportation, performance indicators might include on-time arrival rates, passenger satisfaction surveys, and ridership numbers.
8. Plans: Plans outline a scheme or a set of actions to achieve specific objectives. For instance, a business might create a strategic plan for expanding into new markets or an action plan for launching a new product line.
9. Options: Options are various possible ways to achieve an objective or solve a problem. In urban planning, options might include increasing public transportation, promoting cycling infrastructure, or implementing congestion pricing to reduce traffic.
10. Policies or Strategies: These are courses of action implemented by jurisdictions or organizations. A government might adopt a policy of tax incentives to promote renewable energy as part of its environmental strategy.
11. Programs: Programs are specific sets of objectives, responsibilities, and tasks within an organization. An educational institution might establish a program to improve literacy, which includes curriculum development, teacher
States are increasingly using early warning systems to identify students at risk of falling off track to graduation. These systems analyze data like attendance, behavior, and course performance to predict which students may need additional support. States provide this early warning data to districts, schools, teachers, counselors, and parents to help guide intervention efforts. While more states are developing early warning systems, most only provide the data periodically or upon request. Going forward, states aim to better support stakeholders in using predictive analytics to keep students on a path to both high school graduation and future career or college readiness.
Using Data to Improve Minority-Serving Institution SuccessDawn Follin
This document discusses how Minority-Serving Institutions (MSIs) can better use data to improve student and institutional success and meet national college completion goals. It outlines that MSIs have traditionally educated underserved student populations but some are not fully utilizing data to assess areas for improvement. The document recommends that MSIs adopt interim measures to track student progress and success at multiple points along their educational pathway, such as placement upon entry, persistence in continuous enrollment, progression toward earning a credential, and ultimate completion. These interim measures can provide a more comprehensive view of student outcomes than traditional metrics like graduation rates alone.
Kindergarten Entry Assessments and Early Learning Challenge Grantselccollaboration
This document summarizes key aspects of developing Kindergarten Entry Assessments (KEAs) and their role in Early Learning Challenge Grants. It outlines the definition and purposes of KEAs, scoring criteria, types of assessment instruments, examples, and components of an effective KEA system. It also discusses developing a high quality plan and budget for implementing KEAs that can be used to inform instruction and close readiness gaps while meeting grant requirements.
ow-a-days data volumes are growing rapidly in several domains. Many factors have contributed to this growth, including inter alia proliferation of observational devices, miniaturization of various sensors ,improved logging and tracking of systems, and improvements in the quality and capacity of both disk storage and networks .Analyzing such data provides insights that can be used to guide decision making. To be effective, analysis must be timely and cope with data scales. The scale of the data and the rates at which they arrive make manual inspection infeasible. As an educational management tool, predictive analytics can help and improve the quality of education by letting decision makers address critical issues such as enrollment management and curriculum Development. This paper presents an analytical study of this approach’s prospects for education planning. The goals of predictive analytics are to produce relevant information, actionable insight, better outcomes, and smarter decisions, and to predict future events by analyzing the volume, veracity, velocity, variety, value of large amounts of data and interactive exploration.
The document provides instructions for educators on how to create custom reports in DataDirector to analyze classroom data. It outlines how to select relevant data points, build a custom report with multiple columns of data, and download the report into Excel. Educators can then use conditional formatting in Excel to identify the bottom 30% of students in a particular subject area based on assessment results. The final customized report allows educators to make informed instructional decisions and determine necessary student interventions.
192020 Capella University Scoring Guide Toolhttpsscor.docxaulasnilda
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 1/7
MHA-FP5064
u03a1 - Health Information System Implementation
Learner: Monna , Joseph
OVERALL COMMENTS
Mona
This paper is not very clear and specific. You have very genialized explanations of data and are not discussing
data requirements from meaningful use and merit-based incentives. Also you are not supporting the data needs
with CURRENT academic sources. You only have 2 references both from well over 10 years ago. You need
research current trends and best practices from recent sources.
See the rubric below for more specifics.
RUBRICS
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 2/7
CRITERIA 1
Outline a plan for collecting and analyzing data.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not outline a plan for collecting and analyzing data.
BASIC:
Outlines a plan for collecting and analyzing data that is impracticable or unlikely to yield limited data for
analysis.
PROFICIENT: Outlines a plan for collecting and analyzing data.
DISTINGUISHED:
Outlines a plan for collecting and analyzing data. Provides a concise and well-articulated outline that
identifies specific data needs and a clear approach to analysis.
Comments:
I am not see a plan that alignes with current trends in health care. Plan needs to address specific data that
would common in an EHR and meet current legislative requirments.
(20%)
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 3/7
CRITERIA 2
Propose criteria for evaluating organizational needs.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not propose criteria for evaluating organizational needs.
BASIC:
Proposes criteria for evaluating organizational needs that may lead to erroneous conclusions.
PROFICIENT: Proposes criteria for evaluating organizational needs.
DISTINGUISHED:
Proposes criteria for evaluating organizational needs, and provides relevant, credible evidence that
clearly validates the proposed criteria.
Comments:
Very unclear and is not alinging with best practices from AHIMA, HIMSS or Health IT,gov. Research
current oversight organizations
(16%)
1/9/2020 Capella University Scoring Guide Tool
https://scoringguide.capella.edu/grading-web/gradingdetails 4/7
CRITERIA 3
Outline a plan for generating reports.
COMPETENCY
Incorporate project management principles into health care administration management and leadership.
NON_PERFORMANCE: Does not outline a plan for generating reports.
BASIC:
Outlines a plan for generating reports that is impracticable or unlikely to provide all of the information
necessary to support sound decision making.
PROFICIENT: Outlines a ...
The document summarizes the Common Core State Standards Initiative, which aims to establish consistent K-12 standards in English and math that can be adopted by states. It discusses the importance of common standards, the momentum behind the initiative with 48 states and territories signed on, and outlines the process used to develop the standards with input from states and educators. It also emphasizes that fully implementing the standards will require changes to classroom instruction, materials, assessments, and policies to support student achievement.
Data Driven Instructional Decision MakingA framework.docxwhittemorelucilla
Data Driven
Instructional Decision Making
A framework
Data –Driven Instruction
Data-driven instruction is characterized by cycles
that provide a feedback loop
in which teachers plan and deliver instruction, assess student
understanding through the collection of data, analyze the data, and
then pivot instruction based on insights from their analysis.
From: Teachers know best: Making Data Work For Teachers and Students
Bill & Melinda Gates Foundation
https://s3.amazonaws.com/edtech-production/reports/Gates-TeachersKnowBest-MakingDataWork.pdf
Data-Driven Decision Making Process Cycle
Data Planning
and
Production
Data Analysis
Developing
an Action
Plan
Monitoring
progress
Measuring
Success
Implementing
the Action
Plan
Data is used
From : Teachers know best: Making Data Work For Teachers and Students
Bill & Melinda Gates Foundation
https://s3.amazonaws.com/edtech-production/reports/Gates-
TeachersKnowBest-MakingDataWork.pdf
Data –Driven Instruction Feedback Loop
Data Planning
and
Production
Data Analysis
Developing an
Action Plan
Monitoring
progress
Measuring
Success
Implementing
the Action
Plan
Data –Driven Instruction Feedback Loop
Data Planning
and
Production
Data Analysis
Developing an
Action Plan
Monitoring
progress
Measuring
Success
Implementing
the Action
Plan
Instructors need to
facilitate this data –driven
instruction decision loop
in a timely and smooth
fashion
…and on an ongoing basis
• Per student
• Per class
• Per group
Data –Driven Instruction Feedback Loop
Roles Inherent in the Data-Driven Instruction
Decision Making Loop
• Planner
• Data Producer
• Data Analyst
• Monitor
• Reporter
• Data End User
• IT
• Operations and Logistics
Data Planning and Production Questions
• What questions are to be addressed in future data-informed
conversations? Which questions are more important?
• What information (metrics) are needed to answer these question?
• Is the information available and feasibly attainable?
• Are the necessary technology and resources available?
• How can current non-data based instructional decision making be
mapped to data-based instructional decision making process?
• What are the costs associated with this endeavor?
• What are the timelines ?
• How and when will the data be collected and stored?
Data Analysis Questions
• What relations exists between the metrics? What patterns do
the data reveal?
• How many levels of the metric are needed to answer the
questions?
• Do the original questions need to be revised or expanded?
• Do the original metrics need to be redefined or expanded?
• What analytical tools are currently available? What tools
need to be designed to support the analysis?
• What method of analysis or evaluation will be used?
• What are the data limitations, strengths, challenges, context?
Monitor Questions
• How are the metrics evolving as the learning and instructional
processes evolve.
This document provides an overview of the Common Core State Standards and the transition to Common Core-aligned assessments. It discusses how the Common Core requires higher standards that focus on deeper learning rather than superficial coverage of many topics. It also explains how assessments will change from primarily multiple choice to include more innovative item types like performance tasks and technology-enhanced questions to better measure skills like writing, problem-solving, and analytical thinking. The document provides resources and timelines to help educators understand what is required and plan their transition to meet Common Core requirements by the 2014-2015 deadline.
This document provides guidance on developing a School Improvement Plan (SIP). It explains that a SIP is a formal, structured approach to managing school resources to achieve optimal performance. A SIP committee of 7-10 individuals oversees the process. Key steps in developing a SIP include conducting a self-evaluation, identifying priorities, preparing draft and final plans through consultation, implementation, monitoring and evaluation on an annual basis. The SIP should be aligned with national priorities and the school's annual self-evaluation.
The document provides an overview of online learning for secondary education, noting that an estimated 1.5 million secondary students participated in some form of online learning in 2010, with opportunities available in 48 states and Washington D.C. through various providers. While online learning has become popular due to its potential to provide more flexible access and assemble instructional content more efficiently, the document also notes some proponents see technology as having potential to expand communities of learners and support models of participatory education.
Recent trends and issues in assessment and evaluationROOHASHAHID1
1. The document discusses recent trends and issues in educational assessment and evaluation. It covers topics such as putting students at the center, building capacity at all levels of education systems, managing local needs, greater use of technology, and shifts towards more holistic and demonstration-based forms of assessment.
2. Key trends discussed include expanding the scope of evaluation beyond just student assessment, increasing use of data and technology to enhance assessment, and growing internationalization and standardization of assessment.
3. Issues addressed involve ensuring appropriate and valid assessment methods that align with learning objectives, evaluating new skills developed through technology, and considering the policy impacts of assessment.
Similar to CCA metrics technical-guide-2-3-2012 (20)
The document is the final report of the Florida Blue Ribbon Task Force on State Higher Education Reform from November 2012. It provides recommendations on accountability, funding, and governance for the Florida State University System. The task force organized their work around these three areas and provided a strengths/weaknesses analysis of the system. They recommend a set of linked accountability, funding, and governance changes intended to improve understanding between universities and funding stakeholders and help the system better demonstrate its value and operational innovation.
The document is a draft report from the Florida Blue Ribbon Task Force on State Higher Education Reform. It includes a letter from the chair introducing the task force's work over 6 months to assess the state university system. The draft report contains sections on strengths and weaknesses of the system, and recommendations related to accountability, funding, and governance. It emphasizes the complexity of higher education issues and the need for the university system to improve its standing and contributions to the state.
The document proposes refinements to the "System Strengths and Weaknesses" section of a report. It lists three strengths: 1) an effective professional staff supports the Board of Governors, 2) local control enables excellent learning environments, and 3) comprehensive coordination allows the Board to manage higher education goals. It also lists three weaknesses: 1) limitations in data analysis inhibit decision making, 2) over-centralization may hinder innovation, and 3) insufficient data assessment of university performance.
The document is a draft report from the Florida Blue Ribbon Task Force on State Higher Education Reform. It contains recommendations on accountability, funding, and governance of the state university system. The task force analyzed strengths and weaknesses of the current system and sought to address the complexity of issues facing higher education in Florida. The recommendations are presented as an interconnected whole and are intended to close the gap in understanding between universities and those who appropriate resources by linking accountability, funding, and governance.
The Florida Blue Ribbon Task Force on State Higher Education Reform drafted recommendations to improve accountability and transparency in the state university system. The recommendations included enhancing the Board of Governors' metrics-based accountability framework to focus on outcome-based performance metrics aligned with the governor's strategic goals. These goals include increasing degrees in strategic areas, employment rates and salaries of graduates, and lowering costs. The recommendations also suggested the Board of Governors articulate goals for each university's contributions to the overall system goals, and that universities align their plans with the Board's strategic plan and report progress annually.
This document provides a draft summary of recommendations from various efforts addressing reform of Florida's higher education system. It catalogs recommendations in the areas of accountability, funding, and governance. For accountability, it recommends enhancing metrics around outcomes like employment and enhancing alignment between university and state strategic plans. For funding, it discusses balancing access with excellence and tying funding to performance metrics. For governance, it recommends tying decreased regulation and flexibility to achieving strategic plan outcomes.
The document provides notes from a Governor's Blue Ribbon Task Force conference call discussing strategies to address tensions between increasing and decreasing university tuition in Florida. It recommends increasing state funding toward the national average per student and allowing differentiated tuition rates between degree programs. Specific degree programs in strategic state emphasis areas could qualify for lower tuition rates if universities meet metrics agreed upon by the state Legislature and Board of Governors. Universities meeting additional metrics could be designated "Preeminent" with more tuition flexibility and reduced regulation.
This document provides draft talking points to guide a teleconference discussion about implementing a differentiated tuition model. It outlines a three-step plan where universities could gradually increase tuition rates for degrees up to 6 times the Consumer Price Index annual increase. Degrees classified as "eminent," such as those leading to high employment, could have lower tuition increases. The program would be reevaluated after 4 years based on economic factors. If a university's student quality or graduation rates dropped for two years in a row, tuition increases would be capped at the CPI increase until improvements are made.
This document summarizes a journal article about the relationship between public university research and state economic development. It describes potential virtuous and vicious cycles in this relationship. The virtuous cycle involves increased federal research funding leading to more university discoveries, job growth, and increased state tax revenues that fund universities. However, a vicious cycle can also occur if states do not adequately fund universities. This can weaken universities' research competitiveness and the state's long-term economy. It can also exacerbate disparities between states with strong vs. weak university systems.
The Blue Ribbon Task Force on State Higher Education Reform held a webinar to discuss recommendations on funding, accountability, and governance for state universities. They aimed to refine, improve, accept, table or reject proposed recommendations and identify areas needing further work. Next meeting dates were established to continue discussions and finalize recommendations by October 30th.
The document contains recommendations from working groups on university funding, accountability, and governance. It recommends giving universities more autonomy over tuition rates while tying funding to performance metrics. It also suggests establishing flagship research universities and rewarding programs with high employment outcomes. Additional meetings are scheduled to further refine recommendations for submission to the governor.
This document provides a draft recommendation from a task force on tuition rates at public universities in Florida. It summarizes research showing that state funding for public higher education has declined significantly in recent decades while tuition rates have risen sharply. For Florida universities in particular, state funding has dropped by 25% in four years while tuition rates have remained capped below rates charged by peer institutions in other states. The recommendation suggests removing Florida's system-wide tuition cap and allowing individual universities to set tuition appropriate to their missions and programs.
This document contains draft recommendations from a task force regarding tuition and governance at public universities in Florida. It provides background information on declining state support for higher education and restrictions on tuition increases in Florida. The task force recommends abandoning the tuition policy that locks universities into a narrow tuition range. It also recommends giving university boards of trustees more authority over tuition rates and allowing differentiated rates by program. The recommendations aim to provide universities more flexibility to deal with state funding cuts while maintaining affordability.
The document discusses reforms needed for Florida higher education. It argues that (1) Florida already has an effective structure in place and does not need reorganization, (2) restoring state funds cut in recent years is essential to improve student/faculty ratios and access to courses, and (3) additional new funding is needed to address salary compression and retain faculty talent, in order to build a strong knowledge-based economy.
This document discusses occupational projections in Florida from 2011 to 2019. It includes two tables showing employment counts by education level for 2003, 2011, and 2019. The tables assign educational codes to occupations based on Florida codes and U.S. Bureau of Labor Statistics codes. The document also compares projected bachelor's degree production in Florida to projected job openings requiring a bachelor's degree over that period.
The chair of the Blue Ribbon Task Force on State Higher Education Reform provides guidance to task force members on next steps. Members are to meet in subcommittees between now and September 17 to develop initial reform options, which will be discussed at a September 21 webinar. The chair outlines a timeline of subsequent meetings and deliverables, culminating in a final set of recommendations voted on at an October 12 webinar. Task force members are instructed to provide data and logic to build a business case for each reform option.
The group discussed strengths within the current system, and worked to define what successful state higher education would look like in 3-5 years. They focused on issues of governance, accountability, funding and the system as a whole, with the goal of developing recommendations to advance the governor's vision.
The three sentence summary is:
The document provides final attachments and a website link for participants of a July 26 workshop to aid in their preparation, noting they should resist arguing for or against the ideas presented and instead focus on innovative solutions; it also looks forward to hearing the participants' own analysis and contributions; and includes three attached files and the name and title of the sender.
This document outlines 10 principles for reforming higher education in the United States. The first principle is to reduce third-party payments and end government subsidies and tax breaks that subsidize higher education costs. This would better align costs with the direct benefits received by students and encourage colleges to reduce costs. Currently, third-party payments have led to soaring costs without improving access or outcomes.
More from Florida Blue Ribbon Task Force on State Higher Education Reform (20)
1. Complete College America
Common College Completion Metrics Technical Guide
Updated February 3, 2012 for the 2011-12 Data Collection Managed by SHEEO
Note: Technical guide may be periodically updated to reflect improvements to the instructions as states
collect data and work through the metrics
2. Updated February 3, 2012
Contents
Introduction .................................................................................................................................................. 2
Data Collection and Common Metrics Reporting ......................................................................................... 2
Origination, Purpose, and Guiding Principles ............................................................................................... 2
Outcomes, Progress, and Context ................................................................................................................ 4
OUTCOME METRICS ...................................................................................................................................... 5
Outcome Metric 1: Degree Production .................................................................................................... 5
Outcome Metric 2: Graduation Rates ....................................................................................................... 5
Outcome Metric 3: Transfer Out (for Two-Year colleges only) .............................................................. 10
Outcomes Metric 4: Credits and Time to Degree ................................................................................... 11
PROGRESS METRICS .................................................................................................................................... 12
Progress Metric 1: Enrollment in Remedial Education ........................................................................... 12
Progress Metric 2: Success in Remedial Education................................................................................. 13
Progress Metric 3: Success in Gateway (First-Year) College Courses ..................................................... 15
Progress Metric 4: Credit Accumulation ................................................................................................. 16
Progress Metric 5: Retention Rates ........................................................................................................ 17
Progress Metric 6: Course Completion ................................................................................................... 18
CONTEXT METRICS ...................................................................................................................................... 19
Context Metric 1: Enrollment ................................................................................................................. 19
Context Metric 2: Completion Ratio ....................................................................................................... 20
Definitions of Data Elements and Disaggregation Categories .................................................................... 21
1
3. Updated February 3, 2012
Introduction
This Technical Guide describes the concepts, data elements and definitions supporting the Common
College Completion Metrics adopted by Complete College America (CCA). The goal of this guide is to
increase consistency and commonality across states in reporting benchmark data and measuring future
progress. These metrics are intended to be publicly reported by the state with data collected from all
public postsecondary institutions in the state. Beginning with the 2011-12 data collection, the State
Higher Education Executive Officers (SHEEO) will perform data collection and warehousing operations
on behalf of Complete College America.
Data Collection and Common Metrics Reporting
States with unit record systems may use their system- or state-level data to construct the metrics for
reporting purposes.
States without complete or any unit record systems may collect these data by requesting them from the
colleges and universities in a way that allows for aggregation at the state level and used in constructing
the metrics. These states should begin the process of adding the additional data elements to their unit
record systems as soon as possible.
All states are encouraged to supplement their data through the National Student Clearinghouse (to
provide more accuracy in respect to transfer students within the state).
Origination, Purpose, and Guiding Principles
On July 27-28, 2009, Complete College America, the National Center for Higher Education Management
Systems (NCHEMS), and the State Higher Education Executive Officers (SHEEO) hosted a Data/Metrics
Convening in Denver, Colorado to discuss a common core set of metrics in the area of college
completion. In May 2010, the National Governors Association convened a group of state and national
experts to further refine the metrics. The metrics contained within this Technical Guide reflect the major
conclusions reached at these two convenings.
As a basis for the collective work, individuals involved in the development of the common completion
metrics strongly endorsed the following statement of purpose. The purpose of the metrics is to:
Inform - help policymakers and the general public understand how students (particularly
historically underserved, low-income, and minority young adults), institutions of higher
education, and the state are doing on college completion;
Analyze - help policymakers and institutions of higher education identify specific challenges and
opportunities for improvement;
Show Progress - establish a fair baseline and show progress over time; and
Hold Accountable - hold students, institutions of higher education, and the state accountable to
the general public and to policymakers investing taxpayer dollars in higher education.
2
4. Updated February 3, 2012
Additionally, the initial working group identified a set of guiding principles to contextualize, prioritize,
and guide the implementation of the metrics. These principles are:
1. The data on which the metrics are based must be collected uniformly, allowing for comparisons
across states and, whenever possible, across institutions of higher education.
2. The metrics should be capable of being disaggregated by subpopulations (by age, race, gender,
income) and by the value or type of degree or credential, in order to continuously assess the
equity of postsecondary opportunity.
3. The initial set of metrics should be capable of being constructed from readily available data.
While data systems should improve over time, the urgent need to improve college completion
necessitates utilizing currently available data to measure progress.
4. The quantity of metrics implemented should be carefully balanced to reflect a focus on data that
connect most clearly to completion rates.
5. The metrics should help to identify barriers to student achievement and provide guidance as to
actions that might be taken to improve student success. This means that progression
(intermediate) as well as outcome (completion) metrics should be included. It also means that
metrics should be disaggregated by and allow for comparison among institutions of higher
education.
6. Priority should be placed on measuring improvement over time.
7. The metrics should be transparent and publicly reported.
8. The metrics should be constructed in a manner that minimizes the potential for unintended
negative consequences.
3
5. Updated February 3, 2012
Outcomes, Progress, and Context
The common metrics are organized in three categories:
1. Outcome Metrics;
2. Progress Metrics; and
3. Context Metrics.
The Outcome Metrics quantify the end product of the educational process, mainly the completion of an
undergraduate academic program, and additionally for community colleges, the successful transfer of
students to a baccalaureate campus.
The Progress Metrics measure student progress from semester-to-semester or year-to-year toward the
completion of an undergraduate academic program. Such metrics allow institutions of higher education
the ability to track student progression in a way that allows for early intervention and support to
increase the likelihood of a successful completion or transfer outcome.
The Context Metrics tell the broader story of how the state is doing on college completion. These
metrics allow state policymakers to understand both college completion outcomes relative to growth in
enrollment and the overall effectiveness of their higher education system in increasing educational
attainment of the state’s citizens.
Significantly increasing college completion will require closing the gaps in success rates for low-income
and minority students and ensuring the success of targeted sub-groups such as adults, transfer students,
part-time students, and students who required remedial education. The metrics also should facilitate
measuring progress on a state’s specific postsecondary goals, such as increasing the number of
graduates in STEM or health fields. To understand and track improvement, outcome and progression
metrics must be disaggregated by race/ethnicity, gender, income (Pell Grant recipients), age group,
student attendance status, transfer versus native-to-the-institution students, degree type, and
discipline. States also may wish to flag within their data systems those students who graduated from
high schools within the state (“in-state” students).
For all of these metrics, the standard rule of non-disclosure of personally identifiable information
applies. States and institutions should not publicly report disaggregated data that pertain to a sample
size (N) of 10 or fewer students.
4
6. Updated February 3, 2012
OUTCOME METRICS
Outcome Metric 1: Degree Production
Purpose: To determine how many undergraduate degrees and certificates the state's system of
postsecondary education and its public colleges and universities are awarding annually,
and to measure change over time.
Definition: Annual number of certificates or diplomas of less than 1 academic year (of economic
value, with industry certification or licensure), at least 1 academic year but less than 2
academic years, and at least 2 academic years but less than 4 academic years in length,
associate’s degrees, and bachelor's degrees awarded; disaggregated by age group,
gender, race/ethnicity, Pell status (at any time), remedial status (at any time), and
discipline.
See definitions of Data Elements and Disaggregation Categories on page 20 for more information on the
disaggregation specified throughout this guide
Notes on Collection and Reporting:
For the 2011-12 data collection, data collected are from 2004-05 and 2008-09.
Degree production should be reported for the state and for each public institution of higher education
within the state as appropriate. Each type of award should be reported and displayed individually.
Data should be unduplicated at the institution or state level to show only the highest degree earned
by a student in a given year. This metric is not a calculation of cohort survival rate.
Outcome Metric 2: Graduation Rates
Purpose: To determine the rate at which students graduate from a public institution of higher
education.
Definition: Number and percentage of entering undergraduate students who graduate from a
degree or certificate program within 100%, 150%, and 200% of normal program time.
Disaggregated by degree/credential type, institution type (two-year; four-year research,
very high activity; all other four-year), and by race/ethnicity, gender, age group, Pell
status (at time of entry), and remedial status (at time of entry).
1. Certificates (of at least 1 but less than 2 academic years in program length):
a. First-time, full-time certificate-seeking students
Numerator: Number of students in cohort (denominator) who earn an award
in 100%, 150%, and 200% of the expected (full-time) program
length (each timeframe should be reported cumulatively).
5
7. Updated February 3, 2012
Denominator: Number of first-time, full-time certificate-seeking students
entering in the fall semester of a given year and whose
attendance status at entry is full-time.
b. First-time, part-time certificate-seeking students
Numerator: Number of students in cohort (denominator) who earn an award
in 100%, 150%, and 200% of the expected (full-time) program
length (each timeframe should be reported cumulatively).
Denominator: Number of first-time, part-time certificate-seeking students
entering in the fall semester of a given year and whose
attendance status at entry is part-time.
c. Transfer at entry certificate-seeking students (includes both part-time and full-
time students who were transfer students at time of entry)
Numerator: Number of students in cohort (denominator) who earn an award
in 100%, 150%, and 200% of the expected (full-time) program
length (each timeframe should be reported cumulatively)
Denominator: Number of certificate-seeking students entering in the fall
semester of a given year who enter with or without credits after
attending another institution of higher education (exclude
students entering with only AP or dual enrollment credits here
and include them as first-time student).
2. Associate Degrees:
a. First-time, full-time associate degree-seeking students
Numerator: Number of students in cohort (denominator) who earn an award
in 2 years for 100% time, in 3 years for 150% time, and in 4 years
for 200% (each timeframe should be reported cumulatively).
Denominator: Number of first-time associate degree-seeking students entering
in the fall semester of the given year and whose attendance
status at entry is full-time.
b. First-time, part-time associate degree-seeking students
Numerator: Number of students in cohort (denominator) who earn an award
in 2 years for 100% time, in 3 years for 150% time, and in 4 years
for 200% (each timeframe should be reported cumulatively).
Denominator: Number of first-time associate degree-seeking students entering
in the fall semester of a given year and whose attendance status
at entry is part-time.
6
8. Updated February 3, 2012
c. Transfer at entry associate degree-seeking students (includes both part-time
and full-time students who were transfer students at time of entry)
Numerator: Number of students in cohort (denominator) who earn an award
in 2 years for 100% time, in 3 years for 150% time, and in 4 years
for 200% (each timeframe should be reported cumulatively).
Denominator: Number of associate degree-seeking students entering in the fall
semester of a given year who enter with or without some college
credits after attending another institution of higher education
(exclude students entering with only AP or dual enrollment
credits here and include them as first-time students).
3. Bachelor’s Degree – Four-Year Institutions – Research Universities, Very High
Activity:
a. First-time, full-time bachelor’s degree-seeking students
Numerator: Number of students in cohort (denominator) who earn an award
in 4 years for 100% time, in 6 years for 150% time, and in 8 years
for 200% (each timeframe should be reported cumulatively).
Denominator: Number of first-time bachelor’s degree-seeking students
entering in the fall semester of a given year and whose
attendance status at entry is full-time.
b. First-time, part-time bachelor’s degree-seeking students
Numerator: Number of students in cohort (denominator) who earn an award
in 4 years for 100% time, in 6 years for 150% time, and in 8 years
for 200% time (each timeframe should be reported cumulatively.
Denominator: Number of first-time bachelor’s degree-seeking students
entering in the fall semester of a given year and whose
attendance status at entry is part-time.
c. Transfer at entry bachelor's degree-seeking students (includes both part-time
and full-time students who were transfer students at time of entry)
Numerator: Number of students in cohort (denominator) who earn an award
in 4 years for 100% time, in 6 years for 150% time, and in 8 years
for 200% (each timeframe should be reported cumulatively).
7
9. Updated February 3, 2012
Denominator: Number of bachelor’s degree-seeking students entering in the
fall semester of a given year who enter, with or without credits,
after attending another institution of higher education (exclude
students entering with only AP or dual enrollment credits here
and include them as first-time students).
4. Bachelor’s Degree – All Other Four-Year Institutions
a. First-time, full-time bachelor’s degree-seeking students
Numerator: Number of students in cohort (denominator) who earn an award
in 4 years for 100% time, in 6 years for 150% time, and in 8 years
for 200% (each timeframe should be reported cumulatively).
Denominator: Number of first-time bachelor’s degree-seeking students
entering in the fall semester of a given year and whose
attendance status at entry is full-time.
b. First-time, part-time bachelor’s degree-seeking students
Numerator: Number of students in cohort (denominator) who earn an award
in 4 years for 100% time, in 6 years for 150% time, and in 8 years
for 200% time (each timeframe should be reported
cumulatively).
Denominator: Number of first-time bachelor’s degree-seeking students
entering in the fall semester of a given year and whose
attendance status at entry is part-time.
c. Transfer at entry bachelor's degree-seeking students (includes both part-time
and full-time students who were transfer students at time of entry)
Numerator: Number of students in cohort (denominator) who earn an award
in 4 years for 100% time, in 6 years for 150% time, and in 8 years
for 200% (each timeframe should be reported cumulatively).
Denominator: Number of bachelor’s degree-seeking students entering in the
fall semester of a given year who enter, with or without credits,
after attending another institution of higher education (exclude
students entering with only AP or dual enrollment credits here
and include them as first-time students).
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Notes on Collection and Reporting:
For 2011-12data collection, entering cohorts are as follows:
1. Certificate of at least 1 but less than 2 academic years -Seeking Cohorts
First-time, full-time cohort ; first-time, part-time cohort; and transfer at entry cohort identified
in the fall semester 2006; 100% time by August 31, 2008; 150% time by August 31, 2009; 200%
time by August 31, 2010. 1
2. Associate Degree-Seeking Cohorts
First-time, full-time cohort ; first-time, part-time cohort; and transfer at entry cohort identified
in fall semester 2005; 100% time by August 31, 2007; 150% time by August 31, 2008; and 200%
time by August 31, 2009.
3. Bachelor's Degree-Seeking Cohorts
First-time, full-time cohort ; first-time, part-time cohort; and transfer at entry cohort identified
in fall semester 2003; 100% time by August 31, 2007; 150% time by August 31, 2009; 200% time
by August 31, 2011.
Graduation rates should be produced for the state and for each public institution of higher education
within the state as appropriate. Institutions that award both associate and bachelor’s degrees can report
graduation rates for each cohort separately. For a public institution of higher education graduation rate,
the award must have been completed at that specific institution to be counted in the numerator. For
graduation rates at the state level, the award can be counted in the numerator regardless of where that
student started and completed as long as it was an in-state institution (for states with longitudinal
databases that allow for such tracking of students and/or states that use the National Student
Clearinghouse).
Each timeframe (100%, 150%, and 200%) should be reported and displayed individually for each
respective student type (first-time full-time, first-time part-time, and transfer at time of entry) for each
type of award (Associate degree, Bachelor's degree, and Certificate). The timeframes (100%, 150%, and
200%) are defined by program length.
For the certificate-seeking cohort, the cohort includes students seeking a certificate that is at least one
year but less than two years in program length. As such, the timeframes (100%, 150%, and 200%) are
based on completion of a certificate that is two years program length.
Attendance status of student (full-time, part-time, transfer) is defined at time of entry. "Transfer at
entry" is defined as a student who previously attended a postsecondary institution (with or without
1
Please note that the 100%, 150%, and 200% dates for certificates greater than one year but less than
two years were selected to ensure that completion times for longer certificate programs were not
unreasonably brief. The dates do, however, give additional time to one-year certificates beyond what
one would report to IPEDS.
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credit and who may or may not have a degree award). Undergraduate students entering the institution
directly from high school who earned dual credit or Advanced Placement credit or any other type of
college credit while enrolled in high school should not be considered transfer students at entry, but
rather “first-time” students at entry.
Students identified as "transfer at entry" include both part-time and full-time students.
Data should be unduplicated at the state level. States unable to unduplicate at the state level should
note that fact in the comment box.
Optional Methods to Supplement the Graduation Rate Metrics
1) Attendance Status: Recognizing that many institutions serve large numbers of students whose
attendance status may change over the course of their enrollment, an additional graduation rate
calculation (following the same calculation methodology and baseline cohort years) that includes all
students regardless of full or part-time enrollment may be useful to supplement the above graduation
rate metrics. Please note, however, that the reporting template does not accommodate this option.
2) 12-Month Enrollment vs. Fall Semester Entry (Program vs. Academic Year): Recognizing that many
colleges, especially community colleges, increasingly enroll students throughout the year or have non-
traditional academic calendars, states may wish to make a provision for institutions to adopt a 12-month
enrollment method of identifying graduation rate cohorts. Institutions currently have this option for
identifying their Graduation Rate Survey (GRS) cohorts for reporting IPEDS (referred to as “program
year” reporting as opposed to “academic year” reporting). States or institutions choosing this option
should note this in the comment box.
Outcome Metric 3: Transfer Out (for Two-Year colleges only)
Purpose: To determine the proportion of students successfully transferring from two-year
institution of higher education to four-year institutions of higher education.
Definition: Annual number and percentage of students who transfer from a two-year campus to a
four-year campus by enrollment status at entry, number of credits or credential
completed prior to transfer, race/ethnicity, gender, age group, Pell status (at time of
entry), and remedial status (at time of entry).
Numerator: Number of students from the cohort (denominator) who enroll at a four-
year public institution of higher education or received a degree.
Denominator: Number of entering students in two-year public institutions of higher
education in the fall semester of a specified year.
Notes on Collection and Reporting:
For the 2011-12 data collection, data collected are as follows:
First-time, full-time cohort; first-time, part-time cohort; and transfer at entry cohort are
identified in fall semester 2005 and followed annually until August 31, 2009.
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12. Updated February 3, 2012
The transfer-out metric should be produced for the state and for each public two-year institution of
higher education in the state. Many institutions do not have the ability to determine what type of
institution (if any) students enroll in after transferring out of their institution. Therefore, in most states
this metric will need to be supplied by systems or by the state for institutions using either a student-unit
record system or the National Student Clearinghouse.
Students that transfer should be categorized by the number of credits they receive at the 2-year
institution before they enroll in a four-year institution. They should be reported in the following
categories:
Completed 12 or Fewer Credit Hours
Completed 13 to 30 Credit Hours
Completed More than 30 Credit Hours but Not an Associate’s
Completed an Associate’s Degree
Outcomes Metric 4: Credits and Time to Degree
Purpose: To determine the average length of time in years and number of credits to complete a
certificate or undergraduate degree by student entry status, number of credits
transferred in for transfer students at entry, institutional classification for four-year
institutions, race/ethnicity, gender, age groups, Pell status (at any time), and remedial
status (at any time).
Definitions: Time to degree. Average length of time in years a student takes to complete an
associate’s degree, a bachelor's degree, or a certificate of greater than 1 year but less
than 2 academic years. Start with the degrees/ certificates awarded in a specified year
and determine how many total years and months elapsed from the first date of entry to
the date of completion. Partial years should be expressed as a decimal. Average the
number of years across students and report by degree type.
Credits to degree. Average number of semester credits a student has accumulated when
they earn an associate’s degree, a bachelor's degree, or a certificate of 1 but less than 2
academic years. Start with the degrees/certificates awarded in a specified year and
determine the total number of semester credit hours each student completed since first
enrolling. Average the number of semester credit hours across students and report by
degree type.
Years to Collect/Report: Certificates and degrees awarded in Academic Year 2008-09.
Notes on Collection and Reporting:
The metric should be produced for the state and each public institution of higher education within the
state. For calculating the metrics for each institution, only include elapsed time and accumulated credits
that the student was enrolled in/completed at that specific institution. At the state-level, include all time
and credits accrued beginning with the student’s initial post-high school enrollment in a postsecondary
education institution.
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13. Updated February 3, 2012
Some states may not have the ability to track students’ total length of time to degree or total number of
credits to degree. If available, please instead provide average length of time or number of credits after
transfer, but indicate in an explanatory note that this is what was done. For Transfer Student cohort,
please calculate years and credits consistently. If average years are calculated after transfer, then
average total credits should be calculated after transfer as well, if possible. Please note with an
explanatory note if this is not the manner in which the data is presented.
Student status (full-time, part-time, transfer) is identified at time of entry to the public institution of
higher education. Transfer-in students at 4-year public universities should be classified by the number of
credit hours they earned at previously attended institutions regardless of how the credit hours are
accepted toward a degree at the reporting institution. Based on these criteria transfer students should
be classified into the following categories:
Transfer in 30 or Fewer Credits
Transfer in 31 to 59 Credits
Transfer in 60 or More Credits
For this metric, student race/ethnicity should be based upon data reported at the time of completion
(as opposed to at entry) to conform to the new IPEDS race/ethnicity codes.
Conversion of Quarter Credit Hours to Semester Credit Hours
Credits should be reported as semester credit hours. States and institutions using the quarter system
should divide quarter hours by 1.5 to convert to semester hours prior to reporting.
PROGRESS METRICS
Progress Metric 1: Enrollment in Remedial Education
Purpose: To determine the proportion of undergraduate students who enroll in remedial
coursework at public institutions of higher education.
Definition: Annual number and percentage of entering first-time undergraduate students who
enroll in remedial math, English/reading, or both math and English/reading courses; by
institution type (two-year; four-year research, very high activity; all other four-year),
race/ethnicity, gender, age groups, and Pell status (at time of entry).
1. Remedial Math Only:
Numerator: Number and percent of students from the cohort (denominator) who
enrolled in a remedial math course (but not a remedial
English/reading course) during the first academic year.
Denominator: All first-time degree or certificate-seeking students entering in the
fall semester of the specified year.
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14. Updated February 3, 2012
2. Remedial English/Reading Only:
Numerator: Number and percent of students from the cohort (denominator) who
enrolled in a remedial English/reading course (but not a remedial
math course) during the first academic year.
Denominator: All first-time degree or certificate-seeking students entering in the
fall semester of the specified year.
3. Both Remedial Math and English:
Numerator: Number and percent of students from the cohort (denominator) who
enrolled in a remedial English/reading and a remedial math course
during the first academic year.
Denominator: All first-time degree or certificate-seeking students entering in the
fall semester of the specified year.
Progress Metric 2: Success in Remedial Education
Purpose: To determine the proportion of undergraduate students who enroll in remedial
education, complete remedial education, and go on to complete college-level
coursework in the same subject within two academic years.
Definition: Annual number of entering first-time undergraduate students enrolled in remedial
education courses who complete2 remedial education courses in math, English/reading,
or both and complete a college-level course in the same subject; by institution type
(two-year; four-year research, very high activity; all other four-year), by race/ethnicity,
gender, age groups, and Pell status (at time of entry).
1. Remedial Math Only:
Numerator: Number of students enrolled in a remedial math course during their
first academic year (denominator) who complete all required courses
in remedial math and the first college-level math course within two
academic years.
Denominator: All first-time degree or certificate-seeking students enrolled in a
remedial math course (but not a remedial English/reading course)
during the first academic year.
2
“Complete” means passing or earning a credit for the course. Institutions should determine what counts as
successful completion of a course (i.e., a mark of “pass” for a pass/fail course; a grade of C or better, etc.).
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15. Updated February 3, 2012
2. Remedial English/Reading Only:
Numerator: Number of students enrolled in a remedial English/reading course
during their first academic year (denominator) who complete all
required courses in remedial English/reading and the first college-
level English/reading course within two academic years.
Denominator: All first-time degree or certificate-seeking students enrolled in
remedial English/reading course (but not a remedial Math course)
during the first academic year.
3. Both Remedial Math and English:
Numerator: Number of students enrolled in a remedial English/reading and a
remedial math course during the first academic year (denominator)
who complete all required courses in remedial English/reading and
math and the first college-level English/reading and math courses
within two academic years.
Denominator: All first-time degree or certificate-seeking students enrolled in both
remedial English/reading and math course(s) during the first
academic year.
Years to Collect/Report:
For 2011-2012 data collection, both Progress Metric 1 and Progress Metric 2 use the same
cohort. For both two-year institutions of higher education and four-year institutions of higher
education, the cohort is established with the first-time entry students in the fall semester 2007.
These students are followed through August 31, 2009 to determine the numerator.
A new cohort is established in each subsequent year (the next one is identified in the fall
semester 2008) with the timeframe for completing the remedial course and the college-level
course(s) in the same subject area(s) being within two academic years.
Notes on Collection and Reporting:
The metric should be produced for each public institution of higher education within the state, and
aggregated at the state level for each sector (two-year institutions and four-year institutions).
Both full-time and part-time students should be included.
Data should be unduplicated at the state level. States unable to unduplicate at the state level should
note that in the comment box.
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Disaggregation of Other Metrics by Remedial Status: Remedial course-taking functions both as a metric
in itself and as a disaggregation category (see Definitions of Data Elements and Disaggregation
Categories for more information). The remedial education metrics refer to enrollment in remedial
courses during the period being reported on (i.e., 2008-09 academic year), while the remedial status
disaggregation category refers to whether students took a least one remedial course at time of entry or
at any time during their postsecondary enrollment depending upon the specific metric.
Progress Metric 3: Success in Gateway (First-Year) College Courses
Purpose: To determine the proportion of undergraduate students completing entry, college-level
math courses, English courses, and both math and English courses within the first two
academic years at public institutions of higher education.
Definition: Annual number and percentage of entering first-time degree or certificate-seeking
undergraduate students who complete entry college-level math and English courses
within the first two consecutive academic years; by institution type ((two-year; four-
year research, very high activity; all other four-year), race/ethnicity, gender, age groups,
Pell status (at time of entry), and remedial status (at time of entry).
Numerator(s): Number of students from cohort (denominator) who complete at least
one entry college-level (non-remedial or developmental course) math
course but not an entry-level English course within the first two
consecutive academic years.
OR
Number of students from cohort (denominator) who complete at least
one entry college-level (non-remedial or developmental course) English
course but not an entry-level math course within the first two
consecutive academic years.
OR
Number of students from cohort (denominator) who complete at least
one entry college-level (non-remedial or developmental course) English
course and at least one entry-level math course within the first two
consecutive academic years.
Denominator: For each of the above numerators, the number of first-time degree or
certificate-seeking undergraduate students enrolling in the fall semester
of a specified year.
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17. Updated February 3, 2012
Years to Collect/Report:
For data collection in 2011-12, for both two-year institutions of higher education and four-year
institutions of higher education, the cohort is established with the first-time entry students in
the fall semester 2007. These students are followed through August 31, 2009 to determine the
numerator.
A new cohort is established in each subsequent year (the next one is identified in the fall
semester 2008) with the timeframe for completing college-level course(s) being within two
academic years.
Notes on Collection and Reporting:
The metric should be produced for each public institution of higher education within the state and at the
state level.
First-time students who are exempt from taking entry college-level courses in math or English or both
math and English as a result of AP credit, dual credit earned while enrolled in high school, or CLEP credit
should be included as completers in the numerators.
Both full-time and part-time students should be included.
Data should be unduplicated at the state level. States unable to unduplicate at the state level should
note that fact in the comment box.
Progress Metric 4: Credit Accumulation
Purpose: To determine the proportion of undergraduate students making steady academic
progress during one academic year at public institutions of higher education.
Definition: Number and percentage of first-time degree or certificate-seeking undergraduate
students completing 24 semester credit hours (for full-time students) or 12 semester
credit hours (for part-time students) within their first academic year by institution type
(two-year; four-year research, very high activity; all other four-year), student entry
status, race/ethnicity, gender, age groups, Pell status (at entry), and remedial status (at
time of entry).
1. Full-time Students:
Numerator: Number of students from cohort (denominator) completing 24
semester credit hours within one academic year after entry.
Denominator: Number of first-time, full-time degree or certificate-seeking
undergraduate students entering in the fall semester of the specified
year.
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2. Part-time Students
Numerator: Number of students from cohort (denominator) completing 12
semester credit hours within one academic year of entry.
Denominator: Number of first-time, part-time degree or certificate-seeking
undergraduate students entering in the fall semester of the specified
year.
Years to Collect/Report: For 2011-12 data collection, please report first-time entering students in
the fall semester 2007.
Notes on Collection and Reporting:
The metric should be produced for each public institution of higher education within the state and at the
state level.
Student status (full-time, part-time) is identified at time of entry to the institution of higher education.
Data should be unduplicated at the state level. States unable to unduplicate at the state level should
note that fact in the comment box.
Conversion of Quarter Credit Hours to Semester Credit Hours
Credits should be reported as semester credit hours. States and institutions using the quarter system
should divide quarter hours by 1.5 to convert to semester hours prior to reporting.
Progress Metric 5: Retention Rates
Purpose: To determine the rate at which undergraduate students return to a public institution of
higher education from fall-to-spring and fall-to-fall adjusted for transfers out and
graduates.
Definition: Number and percentage of entering degree or certificate-seeking undergraduate
students enrolling from fall-to-spring and fall-to-fall at an institution of higher education
by institution type (two-year; four-year research, very high activity; all other four-year),
student entry status, race/ethnicity, gender, age groups, Pell status (at time of entry),
and remedial status (at time of entry).
Numerator: Number of students in cohort (denominator) enrolling in the next
consecutive spring and the next consecutive fall semester, or who have
been identified as transferring to another institution or graduating from
the institution.
Denominator: Number of entering first-time degree or certificate-seeking
undergraduate students enrolling in the fall semester of a specified
academic year.
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Years to Collect/Report:
1. Two-Year Public Institutions
For two-year public institutions of higher education, the cohorts for first-time, full-time; first-
time, part-time; and transfer students at entry are established with the students entering in the
fall semester 2005. These students are followed and reported on annually for four years.
2. Four-Year Public Institutions
For four-year public institutions of higher education, the cohorts for first-time, full-time; first-
time, part-time; and transfer students at entry are established with entering students in the fall
semester 2003. These students are followed for six years.
Notes on Collection and Reporting:
The metric should be produced for the state and each public institution of higher education within the
state. For a public institution of higher education retention rate, the student must be retained at that
specific institution to be counted in the numerator. For retention rates at the state level, the student can
be counted in the numerator regardless of where that student started (for states with longitudinal
databases that allow for such tracking of students and/or states that use the National Student
Clearinghouse).
For institutions using a quarterly academic calendar, the fall-to-spring semester retention rate should be
operationalized as fall quarter to following spring quarter (skipping the winter quarter).
Student status (full-time, part-time, transfer) is identified at time of entry to the public institution of
higher education.
Data should be unduplicated at state level. States unable to unduplicate at the state level should note
that fact in the comment box.
Progress Metric 6: Course Completion
Purpose: To determine the proportion of attempted credit hours being completed by entering
undergraduate students at public institutions of higher education.
Definition: Percentage of credit hours completed out of those attempted by entering degree or
certificate-seeking undergraduate students annually and disaggregated by student entry
status.
Numerator: Number of credit hours awarded to entering undergraduate students at
the end of a specified academic year.
Denominator: Number of credit hours degree or certificate-seeking entering
undergraduate students enrolled in during the same academic year.
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Years to Collect/Report: Students entering in the fall semester 2008.
Notes on Collection and Reporting:
The metric should be produced for the state and each public institution of higher education within the
state.
Student status (full-time, part-time, transfer) is identified at time of entry to the institution of higher
education.
Conversion of Quarter Credit Hours to Semester Credit Hours
Credits should be reported as semester credit hours. States and institutions using the quarter system
should divide quarter hours by 1.5 to convert to semester hours prior to reporting.
CONTEXT METRICS
These metrics are calculated at the state and institutional levels from annual degree production
and overall enrollment or state population data. These metrics help to inform state
policymakers of the overall effectiveness of the state’s higher education system, and help to
place the outcome and progress measures in context.
Context Metric 1: Enrollment
Purpose: To determine the number of undergraduate students enrolling at institutions of public
higher education and to measure changes in enrollment over time, overall, and for
specific subgroups.
Definition: Annual unduplicated number of undergraduate students enrolled over a 12-month
period at public institutions of higher education, disaggregated by entry and attendance
status during the 12-month period (first-time or continuing full-time, first-time or
continuing part-time, full-time transfer, or part-time transfer), race/ethnicity, gender,
age, Pell recipient status during enrollment period, and remedial status. Enrollment
should be reported for each public institution and aggregated by sector.
Years to Collect/Report: Academic Years 2003-04 and 2008-09.
Notes on Collection and Reporting:
The metric should be produced for the state and for each institution of higher education in the state.
High school students enrolled in postsecondary courses for credit should not be included.
Students should not be included in both the transfer category and the first-time and continuing
category. See additional clarification on the categories below:
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21. Updated February 3, 2012
Full-time transfers (entered as a transfer student during the 12-month period, status at entry
was full-time)
Part-time transfers (entered as a transfer student during the 12-month period, status at entry
was part-time)
Full-time First-time and Full-time Continuing (not included as a full-time transfer above)
Part-Time First-time and Part-time Continuing (not included as a part-time transfer above)
Context Metric 2: Completion Ratio
Purpose: To determine the proportion of certificates (of at least 1 and less than 2 academic years
in length) and undergraduate degrees awarded relative to undergraduate student
enrollment at public institutions of higher education.
Definition: Annual ratio of undergraduate degrees and certificates (of at least 1 and less than 2
years in length) awarded per 100 full-time equivalent (FTE) undergraduate students
(disaggregated by institution type (two-year; four-year research, very high activity; all
other four-year).
Numerator: Number of undergraduate degrees and certificates (of at least 1 and less
than 2 years in length) awarded in a specified year. (This is a duplicated
count)
Denominator: Number of full-time equivalent (FTE) undergraduate students in the
same year.
Years to Collect/Report: Academic Year 2008-09 (for both the numerator and denominator).
Notes on Collection and Reporting:
The metric should be produced for the state and for each institution of higher education in the state.
Full-time, part-time, and transfer students should be included.
This metric is not a calculation of cohort survival rate.
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22. Updated February 3, 2012
Definitions of Data Elements and Disaggregation Categories
(Special note on disaggregation: For all metrics, the standard rule of non-disclosure of personally
identifiable information applies. States and institutions should not publicly report disaggregated data
that pertain to a sample size (N) of 10 or fewer students.)
Academic year
An academic year includes a summer, fall, winter, and spring term but not necessarily in that order.
Age groups
Date of birth as reported by student in the following age bands:
17-19 years old
20-24 years old
25 and older
Unknown
As with age of majority, age is not rounded up: a student is 19 years old until his/her 20th birthday, and a
student is 24 years old until his/her 25th birthday.
Awards
Associate degree
An award (associate of arts or associate of science) that normally requires at least 2 but less than 4 years
of full-time equivalent college work.
Bachelor's degree
An award (baccalaureate or equivalent degree, as determined by the Secretary, U.S. Department of
Education) that normally requires at least 4 but not more than 5 years of full-time equivalent college-
level work. This includes all bachelor's degrees conferred in a 5-year cooperative (work-study) program.
A cooperative plan provides for alternate class attendance and employment in business, industry, or
government; thus, it allows students to combine actual work experience with their college studies. Also
includes bachelor's degrees in which the normal 4 years of work are completed in 3 years.
Certificate/Diploma (less than one academic year) of Economic Value with Industry Certification or
Licensure
An award that requires completion of an organized program of study at the postsecondary level (below
the baccalaureate degree) of less than one full-time equivalent academic year in program length, and
leading to an industry-recognized credential or certification of proven economic value.
Certificate/Diploma (at least one but less than two academic years in program length)
An award that requires completion of an organized program of study at the postsecondary level (below
the baccalaureate degree) in at least one full-time equivalent academic year but fewer than two full-
time equivalent academic years, or designed for completion in at least 30 semester or trimester credit
hours, or in at least 45 quarter credit hours, or in at least 900 contact or clock hours, by a student
enrolled full time.
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Certificate/Diploma (at least two but less than 4 academic years)
An award that requires completion of an organized program of study at the postsecondary level (below
the baccalaureate degree) in at least two full-time equivalent academic years but fewer than four full-
time equivalent academic years.
Credit
Credit hour
A unit of measure representing the equivalent of an hour (50 minutes) of instruction per week over the
entire term. It is applied toward the total number of credit hours needed for completing the
requirements of a degree, diploma, certificate, or other formal award.
Credit hour (attempted)
The total number of student credit hours attempted in a specified academic term.
Credit hour (completed)
The total number of credits earned in a specified academic term.
For the CCA/NGA metrics, all quarter system credit hours should be converted to semester credit hours
by dividing quarter credit hours by 1.5 prior to reporting.
Degree/certificate-seeking students
Students enrolled in courses for credit and recognized by the institution as seeking a degree, certificate,
or other formal award. High school students enrolled in postsecondary courses for credit are not
considered degree/certificate-seeking.
Discipline
The following degree categories are based on the two-digit Classification of Instruction Programs (CIP)
codes defined by the National Center for Education Statistics. When providing data by discipline,
aggregate up to the subcategory and report by subcategory (i.e., Education, Arts & Humanities, etc) as
follows:
Education
13 Education
Arts and Humanities
5 Area, ethnic, cultural, and gender studies
16 Foreign languages, literatures, and linguistics
23 English language and literature/letters
24 Liberal arts and sciences, general studies and humanities
30 Multi/interdisciplinary studies
38 Philosophy and religious studies
39 Theology and religious vocations
50 Visual and performing arts
54 History
Social and Behavioral Sciences and Human Services
19 Family and consumer sciences/human sciences
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25 Library science
31 Parks, recreation, leisure, and fitness studies
42 Psychology
44 Public administration and social service professions
45 Social sciences
Science, Technology, Engineering, and Math (STEM)
1 Agriculture, agriculture operations, and related sciences.
3 Natural resources and conservation
4 Architecture and related services
11 Computer and information sciences and support services.
14 Engineering
15 Engineering technologies/technicians
26 Biological and biomedical sciences
27 Mathematics and statistics
29 Military technologies
40 Physical sciences
41 Science technologies/technicians
Business and Communication
9 Communication, journalism, and related programs
10 Communications technologies/technicians and support services
52 Business, management, marketing, and related support services
Health
51 Health professions and related clinical sciences
Trades
12 Personal and culinary services
22 Legal Professions and Studies
43 Security and protective services
46 Construction trades
47 Mechanic and repair technologies/technicians
48 Precision production
49 Transportation and materials moving
First-time student (undergraduate)
A student who has no prior postsecondary experience (except as noted below) attending any institution
for the first time at the undergraduate level. This includes students enrolled in academic or occupational
programs. It also includes students enrolled in the fall term who attended college for the first time in the
prior summer term, and students who entered with advanced standing (college credits earned before
graduation from high school).
First-year college course (also referred to as college-level or gateway college course)
The first credit-bearing college course in English or math that applies to course requirements for a
certificate or degree.
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Full-time equivalent student (FTE)
The preferred FTE calculation is the IPEDS definition based on instructional activity. The number of FTE
students is calculated based on the credit and/or contact hours reported by the institution on the IPEDS
12-month enrollment (E12) component and the institution's calendar system, as reported on the
Institutional Characteristics (IC) component. For institutions with continuous enrollment programs, FTE
is determined by dividing the number of contact hours attempted by 900.
For institutions that do not have credit or contact hour information from which to generate the
instructional-based FTE, the default FTE calculation should be as follows:
Part-time annual unduplicated headcount
Full-time annual unduplicated headcount +
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Gender
Sex (male or female or unknown) reported by the student.
Graduation rate
This rate follows closely the rate required of institutions for disclosure and/or reporting purposes under
Student Right-to-Know Act. This rate is calculated as the total number of completers within 100%, 150%,
and 200% of normal time divided by the cohort.
Institution of higher education
Two-year institution (also referred to as community college)
A postsecondary institution that offers programs of at least 2 but less than 4 years’ duration. Those
institutions that historically have offered and awarded programs of at least 2 years, but recently have
added programs of 4 years should be included as long as the majority of degrees awarded still are for
programs of at least two years but less than four years duration. Includes occupational and vocational
schools with programs of at least 1800 hours and academic institutions with programs of less than 4
years. Does not include bachelor’s degree-granting institutions where the baccalaureate program can be
completed in 3 years.
Four-year institution
A postsecondary institution that offers programs of at least 4 years duration or one that offers programs
at or above the baccalaureate level. Does not include institutions that historically have offered and
awarded programs of 2 years or less, but now offer programs of 4 years, if the majority of the degrees
awarded still are for programs of at least two years but less than four years duration.
Four-year Institution—Research University, Very High Activity
A postsecondary institution that offers programs of at least 4 years duration or one that offers programs
at or above the baccalaureate level and is classified by the Carnegie Foundation classification system as
RU/VH or Research University, Very High Activity.
All Other Four-Year Institutions
A postsecondary institution that offers programs of at least 4 years duration or one that offers programs
at or above the baccalaureate level and NOT classified by the Carnegie Foundation classification system
as RU/VH or Research University, Very High Activity.
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26. Updated February 3, 2012
Pell recipient
Undergraduate postsecondary student who qualifies and receives grant assistance through the Higher
Education Act of 1965, Title IV, Part A, Subpart I, as amended.
Pell recipient at entry
An undergraduate student is considered a Pell recipient at entry if the student received a Pell grant
within the first year of entry at a given institution of higher education.
Pell recipient at any time
An undergraduate student is considered a Pell recipient at any time if the student received a Pell grant
at any time during the student's undergraduate tenure.
Race/ethnicity
Categories used to describe groups to which individuals belong, identify with, or belong in the eyes of
the community. The categories do not denote scientific definitions of anthropological origins. They are
used to categorize U.S. citizens, resident aliens, and other eligible non-citizens.
Note about race/ethnicity data codes: For all categories the template collects based on the new IPEDS
categories. In areas such as graduation rate, retention, and other metrics that track a cohort of
students, states may have to map the old race/ethnicity codes to the new ones. The Association For
Institutional Research provides guidance on how to map these categories here:
http://airweb.org/page.asp?page=1502
In general the biggest change is that states should crosswalk Asian/Pacific Islander to the new
categories should select Asian or Native Hawaiian or Other Pacific Islander based on the majority of
students in the Asian/Pacific Islander category, if known.
New Categories (1997 OMB)
A new methodology was developed in 1997 by OMB to be used in reporting race/ethnicity. Individuals
are asked to first designate ethnicity as:
Hispanic or Latino or
Not Hispanic or Latino
Second, individuals are asked to indicate one or more races that apply among the following:
American Indian or Alaska Native
Asian
Black or African American
Native Hawaiian or Other Pacific Islander
White
Two or more races
Hispanic or Latino (new definition)
A person of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin,
regardless of race.
American Indian or Alaska Native (new definition)
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27. Updated February 3, 2012
A person having origins in any of the original peoples of North and South America (including Central
America) who maintains cultural identification through tribal affiliation or community attachment.
Asian (new definition)
A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian
Subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the
Philippine Islands, Thailand, and Vietnam.
Black or African American (new definition)
A person having origins in any of the black racial groups of Africa.
Native Hawaiian or Other Pacific Islander (new definition)
A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.
White (new definition)
A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.
Two or More Races
A person who is not of Hispanic origin and who indicates having origins in two or more races.
Other descriptive categories
Nonresident alien
A person who is not a citizen or national of the United States and who is in this country on a visa or
temporary basis and does not have the right to remain indefinitely. NOTE - Nonresident aliens are to be
reported separately, in the boxes provided, rather than included in any of the seven racial/ethnic
categories. Resident aliens and other eligible (for financial aid purposes) noncitizens who are not citizens
or nationals of the United States and who have been admitted as legal immigrants for the purpose of
obtaining permanent resident alien status (and who hold either an alien registration card (Form I-551 or
I-151), a Temporary Resident Card (Form I-688), or an Arrival/Departure Record (Form I-94) with a
notation that conveys legal immigrant status such as Section 207 Refugee, Section 208 Asylee,
Conditional Entrant Parolee or Cuban-Haitian) are to be reported in the appropriate racial/ethnic
categories along with United States citizens.
Race and ethnicity unknown
This category is used only if the person did not select EITHER a racial or ethnic designation.
Remedial courses
Instructional courses (also called developmental education) designed for students deficient in the
general competencies necessary for a regular postsecondary curriculum and educational setting.
Remedial status (at time of entry)
Remedial status at time of entry as a disaggregation category is determined by whether the student
enrolled in a remedial course within the first year of entry at a given institution of higher education
Remedial status (at any time)
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28. Updated February 3, 2012
Remedial status at any time as a disaggregation category is determined by whether a student enrolled in
a remedial course in any subject at any time during their enrollment in postsecondary institutions.
Retention rate
(Fall-to-spring)
A measure of the rate at which students persist in their educational program at an institution, expressed
as a percentage. For four-year institutions, this is the percentage of first-time bachelors (or equivalent)
degree-seeking undergraduates from the previous fall who are again enrolled in the consecutive spring
semester (or, for institutions on a quarter-based academic calendar, the following spring quarter). For all
other institutions this is the percentage of first-time degree/certificate-seeking students from the
previous fall who either re-enrolled or successfully completed their program by the following spring
term.
(Fall-to-fall)
A measure of the rate at which students persist in their educational program at an institution, expressed
as a percentage. For four-year institutions, this is the percentage of first-time bachelors (or equivalent)
degree-seeking undergraduates from the previous fall who are again enrolled in the current fall. For all
other institutions this is the percentage of first-time degree/certificate-seeking students from the
previous fall who either re-enrolled or successfully completed their program by the current fall.
Student Status
Full-time student
Undergraduate—A student enrolled for 12 or more semester credits, or 12 or more quarter credits, or
24 or more contact hours a week each term.
Part-time student
Undergraduate—A student enrolled for either less than 12 semester or quarter credits, or less than 24
contact hours a week each term.
Transfer at entry
A student entering the reporting institution for the first time but known to have previously attended a
postsecondary institution. The student may transfer in with or without credit and/or a degree award.
Students entering the institution directly from high school who earned dual credit or Advanced
Placement credit or any other type of college credit while enrolled in high school should not be
considered transfer students at entry. Instead, they should be included as “first-time” students.
Undergraduate
A student enrolled in a 4- or 5-year bachelor's degree program, an associate degree program, a
vocational or technical program, or a certificate program below the baccalaureate.
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