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Case Study: Texas

For data to be trusted, policies and protocols must be in place to ensure consistent collection of reliable, valid and complete career readiness data. States can establish universal definitions and automated processes to collect and interpret data and work with practitioners and the public to foster an understanding of data elements to build trust in the data. In Texas, state leaders have developed statewide programs of study and automated identification of Career Technical Education (CTE) learners that have made data collection and reporting more efficient and accurate.

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Case Study: Maryland

An effective career readiness data ecosystem has a clear governance structure in place that designates roles and responsibilities for collecting, validating and reporting career readiness data as well as for setting a strategic vision for the publication and use of data. The absence of a clear and effective data governance structure can lead to entities collecting data in silos, a lack of alignment across data collection and analysis, inconsistent quality of data analysis, and an overall mistrust in the data being collected and reported.

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Case Study: New Jersey

For a data system to be effective, silos between and within state-level agencies must be broken down. Data alignment across agencies and learner levels is critical to understanding a learner’s experience along the K-12, postsecondary and workforce continuum.

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Case Study: North Dakota

Career Technical Education (CTE) stake-holders — including families, employers and local practitioners at the secondary and postsecondary levels — need access to relevant and timely data to make informed decisions when it matters. For all the data CTE leaders collect, processing, cleaning and sharing relevant information can take a year or more, making it far less useful for practitioners on the ground.

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Case Study: Kentucky

In a high-quality career readiness data ecosystem, states do not report data for data’s sake but rather to foster understanding and to spur users to action. Meeting these goals requires a thoughtful approach to designing and presenting career readiness data and a robust system of professional development, technical assistance and supports to ensure that practitioners understand how to use the data. Additionally, data elements are integrated into a state’s communications strategy to tell a career readiness story.

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Case Study: Ohio

A high-quality career readiness data ecosystem should not only collect, analyze and report data but also use the information to promote quality and equity. State leaders should integrate career readiness data into policymaking and decision-making processes to further a statewide career preparation system that is high quality and equitable.