Early Childhood Implementation Snapshots, No. 5: Data and Evaluation Systems

Resource Spotlight

The Tip Sheet Series: Evaluating the Implementation of Evidence-based Practices is a helpful resource to consider when developing and improving the Data and Evaluation Systems structure. The series provides guidance on what to measure, characteristics of a high-quality measurement tool, establishing a fidelity threshold, and summarizing data for decision making.

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Voices from the Field: Wisconsin

Wisconsin collaborated with the Pyramid Model Consortium (PMC) to pilot the Pyramid Model Implementation Data System (PIDS). PIDS was developed by the New York State Council on Children and Families and State University of New York Center for Health and Social Research (SUNY CHSR) with federal Preschool Development Grant (PDG) Birth to Five funding. PIDS holds all Pyramid Model data including social emotional screenings, coaching observations using the Teaching Pyramid Observation Tool (TPOT) and Teaching Pyramid Infant-Toddler Observation Scale (TPITOS), Benchmarks of Quality assessments, and coaching logs. In addition to being used to plan and improve at the program level, program data are shared with Wisconsin Alliance for Infant Mental Health (WI-AIMH) Pyramid Model Coordination in order to report effectiveness, identify professional development gaps at the community, regional and state level, and advise on the development of resources at the state level. Massachusetts, Tennessee and Iowa have all committed to using PIDS based on New York and Wisconsin's efforts. To learn more, watch the PIDS Quick Overview video about Wisconsin's Pyramid Implementation Data System and be sure to review the Pyramid Information Data System (PIDS) Resource List:

"The Pyramid Implementation Data System (PIDS) is able to record all the data, synthesize it, and display it in graph form. It lets you use the data almost instantly."

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Considerations for Equity

• Data systems that disaggregate data by race, ethnicity, gender, financial resources, etc. help to identify disparities. Engage stakeholders representing the disaggregated groups in interpreting the data to provide a deeper understanding of the context from lived experience.
• Data analysis that includes investigating the context for and systemic inequities that impact the data helps to provide more accurate impressions, conclusions, and recommendations for improvement. Consider the conditions that allow the identified issue or concern to persist to identify systemic and societal root causes.
• Representativeness gives a more accurate and comprehensive view of the landscape. Consider which voices are missing from survey and feedback data and identify strategies for developing a better understanding of why their perspectives are underrepresented in data. Partner with leaders identifying with underrepresented groups to identify ways to engage missing voices more meaningfully and successfully.

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Equity Planning Tools

No Longer Invisible: Addressing Equity Through Data Use

This presentation by Grace Kelley and Cindy Weigel reviews the role of leadership in asking critical questions about equity which can be answered through the use of data. It shares ways community perspective can influence understanding of data. The session supports awareness of the importance of addressing equity at each step of data collection, analysis, reporting, and use cycle.

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Name It to Tame It: Using Data to Promote Equity

By the end of this session, participants will begin to:

1. Understand and embrace their roles as leaders in asking questions about equity and using data to answer those questions,
2. Understand a culture of data use and how data helps address equity, and
3. Gain awareness of the importance of addressing equity throughout the cycle of inquiry.

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Analyzing Child Outcomes Data for Program Improvement: A Guidance Table

This document presents a series of questions, including questions about equitable service delivery and equitable outcomes, that state and local programs can use to drive program improvement. Guidance is presented on how to analyze data and report and describe the results for each question.

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Using Child Outcomes Data to Understand Equity

In this Recorded IDIO 2020 session, DaSy staff facilitated discussion with state Part C and Part B/619 staff about analyzing child outcomes data through an equity lens. Topics included asking critical questions without bias, considering data elements to use for disaggregation, and digging deeper in Part C and Part B/619 child outcomes data. Small groups shared out their discussions about data review scenarios and approaches to further equity analyses.

Part C and Part B 619 staff can learn from the reflections of their peers on analyzing child outcomes data with an equity mindset.

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Inclusive, Collaborative Processes that Build Equity into the Data Life Cycle

DaSy Poster on processes to select or avoid to effectively address inequities in early childhood and education structures and systems.

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More Than Numbers: A Guide Towards Diversity, Equity and Inclusion in Data Collection

DaSy guide for organization on how to design demographic data collection in a way that is intentional, inclusive, and equitable.

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A Toolkit for Centering Racial Equity Throughout Data Integration

Many folks have been engaged in equity work at a personal and professional level. But what does it mean to have an equitable system? This session focused on how to intentionally include equity in your system through the indicators of quality in the revised ECTA/ DaSy System Framework. We shared how to use data at the leadership level to inform policy development, and provide opportunity to dig deep to identify needs, priorities, and opportunities for action at both the state and local level within your own system.

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References

• Statewide Implementation Guide. (2019). ECTA Early Childhood Technical Assistance Center. https://ectacenter.org/sig

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