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Implementation Development Map IDM © 2020 CulƟvate Learning at University of WashingtonThe Partnership for Pre-K Improvement (PPI) was a five-year collaboraƟve learning strategy between states, research organizaƟons, and advocacy groups. The culminaƟon of knowledge from this effort is an accessible, online toolkit designed to guide statewide pre-K improvement from the iniƟal stages of idenƟfying crucial partners and creaƟng a shared vision for equitable and high-quality pre-K, through implementaƟon of specific, effecƟve, and measurable conƟnuous-quality improvement efforts. Access the free PPI toolkit here: hƩps://upk-improvement.org The Partnership for Pre-K Improvement (PPI) Project Visit hƩps://upk-improvement.org or contact us at ppitoolkiƟnfo@uw.edu to have your quesƟons answered. Acknowledgements The ImplementaƟon Development Map (IDM) was developed with funding from the Bill & Melinda Gates FoundaƟon (BMGF). The tool was developed as part of the BMGF’s NaƟonal Early Learning Strategy - Partnership for Pre-K Improvement (PPI), an effort led by three organizaƟons, CulƟvate Learning at the University of Washington, Start Early (formerly known as the Ounce of PrevenƟon Fund), and the Alliance for Early Success. We are incredibly grateful for the Ɵme and experƟse that supported the development of the IDM. We want to thank state agency leads, researchers, and advocates from three key states that parƟcipated in the PPI project - Oregon, Tennessee, and Washington. Early learning leaders from addiƟonal states also provided feedback through a one-day stakeholder feedback session, and through several rounds of A/B tesƟng and cogniƟve interviewing.Table of Contents Introduction 4. The Implementation Development Map (IDM) 5. Equity-Driven Quality Improvement 7. Components of the IDM Tool 8. User Guide 9. IDM At-A-Glance The Seven Essential Elements for High-Quality Pre-K 11. Political Leadership 21. Professional Development 31. Instructional Leadership 39. Research-Based Curriculum 49. Formative Child Assessment 57. High Quality Teaching 69. Data-Driven Decision Making 3The Implementation Development Map (IDM) The ImplementaƟon Development Map (IDM) is a process- oriented tool designed to help state leaders implement high-quality equitable prekindergarten (pre-K) systems and pracƟces that produce posiƟve early learning opportuniƟes for every child. The overarching purpose of the IDM is to support equitable implementaƟon and improvement of state pre-k systems by defining essenƟal Elements of high- quality pre-k and delineaƟng a measurable progression of high-quality policies and pracƟces. The IDM can be used to describe, assess, prioriƟze, plan, and measure implementaƟon of state pre-K policies and infrastructure along seven Elements essenƟal to equitable high-quality pre-K: professional development, research-based curriculum, formaƟve child assessment, high-quality teaching, data-driven decision making, instrucƟonal leadership, and poliƟcal leadership. The IDM disƟnguishes key indicators of recommended research- based pracƟces within each essenƟal Element and delineates a developmental progression of these pracƟces. Introduction To begin your state pre-K system evaluaƟon, visit hƩps:// upk-improvement.org/app/idm/ You can also access addiƟonal tools and resources from the PPI work, including stakeholder engagement templates, state agency and advocacy capacity and partnerships, job- embedded professional learning (JEPL) tools and much more! Data-Driven Decision Making High-Quality Teaching Formative Child Assessment Reasearch-Based Curriculum Instructional Leadership Professional Development Political Leadership 4Equity-Driven Quality Improvement A primary purpose of the ImplementaƟon Development Map (IDM) is to examine policies and pracƟces grounded in an equity approach, including collecƟng and disaggregaƟng data to beƩer understand where and how to transform systems to improve opportuniƟes for all children. What We Mean by Equity In the IDM, equity is defined as the condiƟon that would be achieved if one’s idenƟty no longer predicted, in a staƟsƟcal sense, how one fares. In this light, equity is a journey, a desƟnaƟon, and an examinaƟon of the history that brought us to our current state, as it seeks to create communiƟes and environments where ascribed traits (race, ethnicity, income, and language) can no longer predict the social outcomes of an individual or group (Center for Social Inclusion, 2017). Achieving equity requires addressing the imbalance of risks and advantages that have been accumulated over Ɵme. Equity is specifically called out in the IDM tool to ensure an intenƟonal focus on systems improvement that is accountable for every child. CreaƟng a high-quality and equitable pre-K system requires recognizing whichchildren, families, and early learning professionals are furthest from educaƟonal jusƟce, idenƟfying extant barriers, and implemenƟng targeted strategies to remove or address barriers. A key part of equity is analyzing and understanding the narraƟves and processes that create and jusƟfy inequiƟes and working proacƟvely to dismantle them. Research demonstrates that access to high-quality early learning fosters posiƟve long-term educaƟonal outcomes. However, state systems are inequitable and reproduce disparate outcomes that favor children from White, English speaking, and affluent backgrounds. Ongoing data collecƟon and analysis are essenƟal to understanding instrucƟonal pracƟces that improve early learning outcomes for every child and support their transiƟons to and through the K-12 system. How Equity is Embedded We have ensured the IDM is focused on equity by meaningfully incorporaƟng diverse stakeholder voices in the development process and ensuring that criƟcal data on diverse populaƟons are collected and used for decisionmaking. To center equity in using the IDM as a conƟnuous quality improvement tool, we chose to use Targeted Universalism as a framework. “Targeted Universalism means seƫng universal goals pursued by targeted processes to achieve those goals” (Powell et al., 2019, p. 4). Using the framework of Targeted Universalism, the IDM helps state teams set universal quality goals for state-level pre-K and develop targeted strategies to achieve those goals differently based on the needs of different populaƟons (in essence engage in conƟnuous quality improvement that targets what works, for whom, and under what circumstances). Data collecƟon, disaggregaƟon, and analysis are used to assess how pre-K is working for different populaƟons, making it easier to idenƟfy groups who need more support. Using data as a basis for acƟon planning, a state can then conduct pilots and create strategies that increase the quality of pre-K for each group specifically. The IDM allows the user to engage in three criƟcal acƟviƟes for improving and implemenƟng equitable pre-K policies and pracƟces. These include stakeholder engagement, conƟnuous quality improvement (CQI), and integraƟng equity in pre-K improvement efforts across the essenƟal Elements of the IDM. These acƟviƟes and how they map onto the five steps necessary for Targeted Universalism involve: 1. Establishing a universal goal based upon a broadly shared recogniƟon of a societal problem and collecƟve aspiraƟons (e.g., state pre-K stakeholders come together to establish an understanding of the current state pre-K system and establish a collecƟve vision for high- quality). 2. Assessing general populaƟon performance relaƟve to the universal goal. 3. IdenƟfying groups and places that are performing differently with respect to the goal. Groups should be disaggregated by race, class, and language. 4. Assessing and understanding the structures that support or impede each group or community from achieving the universal goal. Steps 2-4 outline the CQI approach of assessing, planning, implemenƟng, and collecƟng evidence to examine the success of the implementaƟon (what worked, what didn’t, and why) and using this evidence to make data-informed decisions. 5. Developing and implemenƟng targeted strategies for each group to reach the universal goal. Commiƫng to an equity agenda ensures that soluƟons and improvements are targeted for specific populaƟons as needed. The targeted populaƟon categories (e.g., race, ethnicity, income, and language) are designed as a guide for states to idenƟfy criƟcal groups that are historically furthest from educaƟonal jusƟce. It is also important for each state to focus on the children that make up their target populaƟons when using the IDM. In some instances, the IDM focuses on specific groups to ensure that states are paying parƟcular aƩenƟon to those groups, including Dual Language Learners (DLLs) and children with developmental delays and disabiliƟes. In such instances, the literature that undergirds the indicators points to a need for a different approach in assessing DLLs and children with developmental delays and disabiliƟes. We have incorporated an analysis of such literature in our literature reviews. 5Equally important, through comprehensive collecƟon and analysis of data, we hope the IDM will encourage ‘double-loop learning,’ a theory of inquiry created by Chris Argyris in the mid-1980s which is meant to encourage people to examine their assumpƟons and beliefs, parƟcularly around race and ethnicity. This requires examining one’s hidden assumpƟons about the nature and causes of inequity in the system and understanding how these perspecƟves play a role in decisions about the specific data collected, how data is understood and interpreted, and the decisions made based on the data. Equity Tools and Resources A focus on equity must be foundaƟonal to improvement efforts at all levels of the system. If equity is not the foundaƟon of system reform at all levels, improvement efforts risk perpetuaƟng and exacerbaƟng societal inequiƟes rather than working to ameliorate them. Focus on equity must include an intenƟonal sharing of power and decision-making in the planning and improvement process, including the nature of data collecƟon and creaƟng equitable goals. As you prepare to assess your system using the IDM and assemble an improvement planning team, please review the ConsideraƟons for Equity Commitments guidance to help you enter the IDM process with an intenƟonal commitment to equity. 6Components of the IDM Tool Elements The seven essenƟal Elements in the IDM are grouped into four categories: PoliƟcal Leadership, Workforce Development, Classroom PracƟce, and Data-Driven Decision Making. The Workforce Development category represents two Elements (Professional Development and InstrucƟonal Leadership), and the Classroom PracƟce category represents three Elements (Research-Based Curriculum, FormaƟve Child Assessment, and HighQuality Teaching). Each Element has a set of indicators. Indicators Indicators are targets and measures of equitable state pre-K systems that describe and quanƟfy various aspects of quality and collecƟvely make up the Element. Each Indicator includes a scale for measuring the quality of the state pre-K system (1 = IniƟal stages, 2 = In development, 3 = In place, and 4 = Well established). Indicators are categorized into Equitable Infrastructure or Equitable ImplementaƟon Indicators. Infrastructure Indicators Equitable Infrastructure Indicators focus on state systems, policies, and pracƟces that support high- quality preK. The Infrastructure indicators appear at the beginning of the Element and are labeled as policy (e.g., established in policy and statewide standards), supports (e.g., dedicated resources), and data (e.g., data collecƟon standards and protocols and data use). Policy AdministraƟve requirements, incenƟves, regulaƟons, or legislaƟon designed to define and support equitable quality pracƟces. The policy is formally wriƩen in regulaƟon or legislaƟon • The text of this policy is easily discoverable for all stakeholders • The policy is widely known within the pre-K program • The policy is adequately funded • There is a mandate around following the policy • There is a defined process and resources for overseeing the successful implementaƟon of the policy • Policies that define high-quality teaching align with other such policies (e.g., PD standards align with credenƟaling standards) • Processes and resources are available and used by pre-K programs • Programs collect data on implementaƟon Supports The resources, guidance, training, technical assistance, or ongoing supports necessary to foster the high-quality, equitable implementaƟon of a pracƟce or policy. • Supports are universally available to all (e.g., programs, teachers, instrucƟonal leaders) • Funding for supports is allocated regularly and sufficiently • AddiƟonal supports are available for the lowest- performing programs or classrooms Data at the State Level The data, informaƟon, and reporƟng processes or tools state agencies use for accountability and equitable conƟnuous quality improvement. • A data system exists • Data from programs is collected equitably • Data is collected regularly and disaggregated by race, socioeconomic status, language, and differences in developmental abiliƟes • Data is analyzed regularly • Data is used for improvement • Data and data analyses are made available for relevant stakeholders • The quality of data is conƟnually monitored • Training in the use of the data system is provided equitably to all those required to use the data system ImplementaƟon Indicators Equitable ImplementaƟon Indicators focus on the degree to which high-quality pre-K pracƟces occur at the program level and who is benefiƫng. These indicators require acƟve and High Quality Data collecƟon, including representaƟve samples in order to evaluate the progress of all subpopulaƟons. This approach helps illuminate which children are progressing and experiencing the benefits of improvement efforts at the program or classroom level, as well as determine progress toward equitable, high-quality standards. These indicators cannot be scored if the state does not collect the data or does not have access to these types of data. Data at the Program Level The data, informaƟon, processes, or tools program leaders use for conƟnuous improvement of pracƟce and to report to families and state or district agencies. • Data is collected regularly using reliable and valid methods • Data is analyzed regularly, including disaggregaƟon by idenƟfied subgroups to reveal inequiƟes • Data and data analyses are made available for relevant stakeholders • The quality of data is conƟnually monitored • Relevant data systems can be linked to support decision making • Equitable stakeholder engagement is a component of a data-driven decision making process • Data is used for improvement • Training in the use of the data system is provided equitably to all those required to use the data system 7The IDM is designed to be used by state agencies as a self-assessment of their progress along a conƟnuum, or map of seven Elements of high- quality pre-K. States can use the tool to look at where they are currently and where they can go next based on their unique early childhood infrastructure, capacity, and strategic plans. The tool is not meant to evaluate the overall efficacy of a state pre-K system, but rather to idenƟfy areas of strength and potenƟal growth for each unique state system and within each essenƟal Element. Because each state’s early learning landscape is different, the tool is also not meant to compare the relaƟve strength of state pre-K systems but rather to inform internal actors within each state. An intended purpose of the tool is to guide state agency leaders with a baseline understanding of their state pre-K system across the seven essenƟal Elements, which will allow them to determine areas of growth and inform resourcing and personnel decisions focused on pre-K improvement. Depending on the state’s level of early learning data collecƟon, state-level administrators and other actors can use available documentaƟon and expert knowledge to assess where their state falls on the different indicators. The process of compleƟng the IDM, in addiƟon to highlighƟng areas of strength and potenƟal growth, can also serve to idenƟfy gaps in the state’s early learning data landscape that may be important for implemenƟng conƟnuous quality improvement efforts. Longitudinal use of the tool can provide administrators with feedback on the overall effecƟveness of improvement efforts and allow states to make data-informed decisions for the purpose of conƟnuous quality improvement. Below is one way a state administrator might use the tool: 1. A state administrator can either choose an Element to focus on, a few Indicators within an Element, or a few Indicators from several Elements. This choice can be made for a variety of reasons. Perhaps the state wants to improve in certain Elements or Indicators, or exisƟng data shows that one area of the state pre-K system might need further examinaƟon and improvement. 2. Once a state determines an area of focus, the administrator can use exisƟng data to determine where on the Indicator(s) their state appears (1-4). 3. A state administrator can create a plan for improvement, including specific and measurable goals, Ɵmelines for these goals, and what data is needed to track progress. 4. At the established Ɵme, the state administrator can review the IDM Indicators using the new data and plan next steps accordingly. If sufficient progress has been made, the administrator may choose to set new goals, or further improve on exisƟng goals. If liƩle or no progress was made, the administrator may first evaluate the original plan, idenƟfy if the data source is accurate and adequate, and revise plans for improvement as necessary. While the IDM is a tool meant for the state, most Indicators can also be used locally to understand program level progress. This can help states to collect implementaƟon progress data at local levels and use the informaƟon to customize improvement efforts at the local and program levels. Similarly, data from programs can help states look at equity by disaggregaƟng informaƟon to understand how state pre-K systems support children from historically disadvantaged backgrounds. User Guide 8Next >