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Doctoral Degrees, Novices, Scholarship, Data, Information Management, Social Networks, Social Support Groups, Fellowships, Postdoctoral Education, and Data Collection

Established in 2004, the Council on Library and Information Resources (CLIR) Postdoctoral Fellowship Program (program) had as its goal the recruitment, training, and creation of cohorts of new PhDs working within the library or cultural heritage digital environment to help manage, sustain, and generate valuable information in support of research and learning. With the data curation fellowships, introduced in 2012, the goal was for the fellows to "contribute to a more sophisticated understanding of data curation and its often determining role in the conduct of scientific and social science research" (Bishop and Williford 2019). This report: (1) discusses the methodology of the 2018-2022 assessment of the CLIR program; (2) provides an analytical review of prior program assessments; (3) identifies the types of data curated through the fellowships; (4) identifies differences in data curation across the different cohorts; (5) explores the challenges emerging from those curation activities; (6) identifies the impact of the fellows' work on their host organizations and communities; (7) assesses the impacts of the COVID-19 pandemic and contemporaneous social movement events on the fellows; and (8) identifies future priorities for the program.

Longitudinal Studies, State Programs, State Policy, Data Collection, Federal Aid, Data Use, Elementary Secondary Education, Data Processing, Decision Making, Accountability, Automation, and United States

Statewide longitudinal data systems (SLDSs) can enable researchers, policymakers, and practitioners to identify and understand important relationships and trends across the education-to-workforce continuum. A well-developed SLDS can increase state and territory governments' ability to establish more informed and equitable policies, enable agency leaders to act more strategically, and help practitioners make more data-informed decisions. The SLDS Survey was created to capture information about the data capacity of states' and territories' SLDSs across these varying circumstances. In addition to inventorying information about whether a given data type, link, or use is in place, the SLDS Survey explores the development of SLDSs and their varying degrees of implementation. By providing standard measures for various aspects of data capacity, the SLDS Survey helps stakeholders understand and assess the ability of SLDSs to store, manage, link, and use key data types across the preschool through workforce (P-20W+) spectrum. This Statistics in Brief provides aggregate data from the 2019 and 2020 administrations of the SLDS Survey. The primary focus of the report is on the 2020 SLDS Survey with results specific to the 2019 SLDS Survey. This brief is structured to address the following four research questions: (1) What types of K-12 data are included in the statewide longitudinal data system (SLDS)?; (2) What is the capacity for linking K-12 student data in the SLDS to other data? How are the data linked?; (3) Are there data dictionaries published publicly? Are data aligned to the Common Education Data Standards (CEDS)?; and (4) How do states and territories use data for reporting and decision-making?

Parent Attitudes, Data Collection, Information Dissemination, Parents, Decision Making, Academic Achievement, Scores, Student Characteristics, Graduation Rate, High Schools, and Educational Quality

The Data Quality Campaign (DQC) has been reviewing state report cards for the past seven years. They continue to examine the landscape of state report cards because they believe states must increase transparency and build trust by sharing information. But after many years, it was time to look at state report cards with fresh eyes. In addition to the regular review of state report cards from all 50 states and the District of Columbia--conducted in March and April 2023-- DQC decided to ask parents, who are the audience that these report cards are meant to serve, what they think. [For "Show Me the Data 2022 Deep Dive: Data for Equity," see ED629865. For "Show Me the Data 2022 Deep Dive: Making Data Meaningful," see ED629871. For "Show Me the Data 2022 Deep Dive: Postsecondary Pathways," see ED626465.]

Early Childhood Education, Child Care, Young Children, Access to Education, Equal Education, Data, Data Collection, Data Analysis, Systems Development, Information Technology, and California

As California invests in early learning and care, the state is also moving forward with a long-overdue plan to build a statewide longitudinal data system (SLDS) -- known as the Cradle-to-Career (C2C) Data System -- which will eventually connect data over time and across sectors like education, health, human services, and the workforce. This is a significant milestone that will allow California to identify inequities and roadblocks to success while also recognizing where things are going well, especially for children of color, those living in poverty, children with disabilities, and dual-language learners. However, California's early learning and care system has shortcomings in the way data is collected, managed, and used which present challenges in accessing and integrating data from the "Cradle" side of the C2C Data System. In this policy brief, we provide an overview of the current early learning and care data landscape in California, three key shortcomings, and recommendations for a coordinated, cross-agency effort to design a comprehensive Early Childhood Integrated Data System (ECIDS). A fully operational ECIDS will also provide the foundation necessary for stronger "Cradle" data that is an essential component of a robust C2C Data System.