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Workforce Data Quality Initiative – WDQI Round 8
The purpose of this program is to support the development or expansion of state workforce longitudinal administrative databases.
Collecting and analyzing longitudinal data can provide a comprehensive picture of whether education programs lead to employment in related fields, whether jobseekers
are obtaining training-related employment, and the impact of training on workers’ earnings throughout their careers.
Through such deep dive analyses, states can identify service delivery strategies that improve employment opportunities, as well as demonstrate the benefits of education and workforce programs on employment outcomes.
Data linkages can help state and local leaders identify effective pathways through education and training services that lead to success in the workforce and can provide individuals with information that helps them make informed choices about their education and career(s).
WDQI grants provide funding to eligible SWAs to accomplish all, or a combination, of the following objectives:
Develop or improve the State Workforce Longitudinal Administrative Database.
SWAs can use this funding to develop a new state workforce longitudinal administrative database, to incorporate new data sources, or to expand/strengthen existing data sources into their existing database so individual-level records can be matched across workforce training programs and over time.Connect workforce data with education data contained in the Statewide Longitudinal Data System (SLDS).
WDQI requires that workforce data be matched with education data, consistent with all relevant federal and state privacy and confidentiality laws, to ultimately create a state longitudinal administrative database with individual-level information from pre-kindergarten through post-secondary and training into the workforce system.
The connection of workforce and education data enables the analysis of individuals’ receipt of both education and training services to help determine ways to maximize the outcomes of these services and improve the effectiveness of the programs.Improve the quality and breadth of the data in workforce longitudinal administrative databases.
It is important that data in the workforce longitudinal administrative databases are complete, accurate, and relevant to understand the impact of state workforce development programs on job seekers and employers.
Data collection processes should be streamlined and standardized to ensure that the data are valid.Use longitudinal data to evaluate the performance of federally and state- supported education and job training programs.
Evidence-based decision making is the foundation for effective program management and strategic planning.
Longitudinal administrative databases provide business intelligence for policymakers and stakeholders to make programmatic adjustments in an effort to improve education and workforce programs.Provide user-friendly information to help customers select the education and training programs that best suit their skills.
These state-customized scorecards contain data to help job seekers make informed decisions about programs that offer skills training needed to pursue in-demand jobs.
Publicly-searchable-by-training provider and program-of-study scorecards allow anyone, including policymakers, students, and researchers, to search labor market information and available training and subsequent outcomes, such as program completion, employment, and wage information of participants in these training programs.Integrate performance, fiscal, and/or case-management systems with the longitudinal administrative database.
Integration across multiple components of state data systems is a vital step towards improved program management and enhanced state data analytics capabilities.
WDQI grants become even more vital as states move towards developing and building a more integrated data system structure, as envisioned under WIOA.
ETA believes that these system enhancements will facilitate SWA’s development of comprehensive information sharing tools (e.g., mobile applications, dashboards, or interactive scorecards) enabling access to longitudinal administrative data system for different program needs including case managers, fiscal staff, or performance staff, to name a few.
Linking information from longitudinal data systems, state-based wage-data-matching systems, and cross-program/departmental systems has the potential to improve workforce data quality.
Collecting and analyzing longitudinal data can provide a comprehensive picture of whether education programs lead to employment in related fields, whether jobseekers
are obtaining training-related employment, and the impact of training on workers’ earnings throughout their careers.
Through such deep dive analyses, states can identify service delivery strategies that improve employment opportunities, as well as demonstrate the benefits of education and workforce programs on employment outcomes.
Data linkages can help state and local leaders identify effective pathways through education and training services that lead to success in the workforce and can provide individuals with information that helps them make informed choices about their education and career(s).
WDQI grants provide funding to eligible SWAs to accomplish all, or a combination, of the following objectives:
Develop or improve the State Workforce Longitudinal Administrative Database.
SWAs can use this funding to develop a new state workforce longitudinal administrative database, to incorporate new data sources, or to expand/strengthen existing data sources into their existing database so individual-level records can be matched across workforce training programs and over time.Connect workforce data with education data contained in the Statewide Longitudinal Data System (SLDS).
WDQI requires that workforce data be matched with education data, consistent with all relevant federal and state privacy and confidentiality laws, to ultimately create a state longitudinal administrative database with individual-level information from pre-kindergarten through post-secondary and training into the workforce system.
The connection of workforce and education data enables the analysis of individuals’ receipt of both education and training services to help determine ways to maximize the outcomes of these services and improve the effectiveness of the programs.Improve the quality and breadth of the data in workforce longitudinal administrative databases.
It is important that data in the workforce longitudinal administrative databases are complete, accurate, and relevant to understand the impact of state workforce development programs on job seekers and employers.
Data collection processes should be streamlined and standardized to ensure that the data are valid.Use longitudinal data to evaluate the performance of federally and state- supported education and job training programs.
Evidence-based decision making is the foundation for effective program management and strategic planning.
Longitudinal administrative databases provide business intelligence for policymakers and stakeholders to make programmatic adjustments in an effort to improve education and workforce programs.Provide user-friendly information to help customers select the education and training programs that best suit their skills.
These state-customized scorecards contain data to help job seekers make informed decisions about programs that offer skills training needed to pursue in-demand jobs.
Publicly-searchable-by-training provider and program-of-study scorecards allow anyone, including policymakers, students, and researchers, to search labor market information and available training and subsequent outcomes, such as program completion, employment, and wage information of participants in these training programs.Integrate performance, fiscal, and/or case-management systems with the longitudinal administrative database.
Integration across multiple components of state data systems is a vital step towards improved program management and enhanced state data analytics capabilities.
WDQI grants become even more vital as states move towards developing and building a more integrated data system structure, as envisioned under WIOA.
ETA believes that these system enhancements will facilitate SWA’s development of comprehensive information sharing tools (e.g., mobile applications, dashboards, or interactive scorecards) enabling access to longitudinal administrative data system for different program needs including case managers, fiscal staff, or performance staff, to name a few.
Linking information from longitudinal data systems, state-based wage-data-matching systems, and cross-program/departmental systems has the potential to improve workforce data quality.
Agency: Department of Labor
Office: Employment and Training Administration
Estimated Funding: $11,600,000
Office: Employment and Training Administration
Estimated Funding: $11,600,000
Who's Eligible
Obtain Full Opportunity Text:
http://grants.nih.gov/grants/guide/pa-files/PA-11-113.html
Additional Information of Eligibility:
The following organizations are eligible to apply: • State Workforce Agencies (SWAs) - SWAs in the 50 States, the District of Columbia, the Commonwealth of Puerto Rico, the U. S. Virgin Islands, American Samoa, Guam, and the Commonwealth of the Northern Mariana Islands.
• Among the eligible applicants listed above, SWAs planning to apply for the $2,900,000 award that identify as a LP2 will be given priority of selection.
Applicants that previously received three or more WDQI grants are ineligible to apply.
The following States’ SWAs have received three or more WDQI grants and are ineligible for this reason: Maine, Michigan, New Jersey, Texas and Rhode Island.
• Applicants that have an active WDQI grant are ineligible to apply, unless the grant period of performance will end on or by June 30, 2021.The following States’ SWAs have active WDQI grants and are therefore ineligible to apply: California, Colorado, Idaho, Illinois, Maine, Michigan, New Jersey, North Carolina, Texas, Wisconsin.
Full Opportunity Web Address:
http://grants.nih.gov/grants/guide/pa-files/PA-11-113.html
Contact:
Agency Email Description:
Please email questions to the contact listed.
Agency Email:
Date Posted:
2021-03-22
Application Due Date:
Archive Date:
2021-05-26
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