The presentation will begin at approximately 1:00 p.m. ET

1. Early Childhood Data Use Part III The presentation will begin at approximately 1:00 p.m. ET Information on joining the teleconference can be found on the “Info” tab in the upper left of this screen. Be sure to use the “Attendee ID” number on the Info tab when dialing in to associate your name with your phone. In order to cut down on background noise, please mute your phone by dialing *6 upon entry into the meeting. During the question and answer portion of this presentation: • You can re-enter *6 to unmute your phone and ask a question; or • Type your question into the Q&A panel below the participant list and click “Send.” A copy of this presentation and a link to the recording will be shared with the IES Grantees and EIMAC listservs. SLDS Webinar

2. Introduction to • Early Childhood • Data Use • Part III

3. Welcome Panelists Avisia Whiteman (Minnesota) Casey Hanson (Missouri) Dr. Lori Bland (George Mason University) Agenda Review of early childhood data use - Plan & Create phases from the first two webinars Introduction to using early childhood data use – Support phase Learn about examples from other states creating early childhood products and use Share ideas about future possibilities of using EC Data Questions from participants SLDS Webinar

4. Early Childhood Data Use What does it mean to effectively use early childhood data?

5. Data Use Framework large images

6. Review: PLAN Mission and Goals • What is the point? Identification and prioritization of users • Who are we serving? Identification of uses • What types of decisions and/or actions will the system inform?

7. Review: CREATE Stakeholder Engagement • How do we involve those whom we intend to serve? Products/Resources • What types of products and resources will the SLDS generate? Delivery • How will you deliver data to key users?

8. Data Use Framework: Support User Support • How will users know how to use the system? • How will users understand the data provided by the system? • How will users know what to do with the data provided by the system?

9. Data Use Framework: Support(continued) Evolution and Sustainability • How do we continue to support users and their needs as they expand and evolve? • How do we make the system an essential resource for users? • How do we ensure we have the resources to continue meeting users’ needs?

10. Data Use Framework • Identificationof Uses • Stakeholder Engagement • Identification & Prioritization of Users • Products/Resources • Mission & Goals • Delivery large images • Evolution & Sustainability • User Support

11. Data Use: Support Strategies How will users know how to use the system? How do we continue to support users and their needs as they expand and evolve?

12. Data Use: Support Strategies How will users understand the data provided by the system?

13. Data Use: Support Strategies How will users know what to do with the data provided by the system? How do we ensure we have the resources to continue meeting users’ needs?

14. Data Use: Support Strategies How do we make the system an essential resource for users (sustainable)?

15. Understanding the Context for the Research Research has typically: been conducted in K-12 focused on use of student achievement data, in this order • state-level accountability tests • district-level benchmark tests • classroom assessment focused on use of specific technological tools (fewer studies) been conducted with, in this order • special education teachers (response to intervention) • classroom teachers • leadership (principals and superintendents (but in broader context)) Applications of principles can be made to Early Childhood.

16. Research in Practice What does research say about how users of the data (state administrators, policy makers, program administrators) understand the data provided by the data system?

17. User Understanding of Data & Data Use Data is complex and multi-layered: • build understanding of relationships across data. Use is influenced by user understanding and social interactions among users: • build understanding with organizational groups. Data use isn’t and shouldn’t be linear: • build understanding of data use as an iterative and recursive process.

18. Research in Practice What does the research say about whether users know what to do with the data provided by the data system?

19. User Use of Data Incorporation of micro-level (classroom) data is key because macro-level data (state) is less useful. Specific feedback from data impacts learning. Skill drill should not be the only focus for data use – because development of conceptual understanding and deep learning is lost. User anxiety about DDDM affects efficacy for using data tools and understanding the data which, in turn, affects collaboration about data use and ability to internalize DDDM as a regular practice.

20. Research in Practice What does the research say about how we continue to support users and their needs as they expand and evolve?

21. Continuous Support of Users Leader at meso-level (organization) is a key player to model data use, but typically lacks training: • Cultivate leadership. DDDM + instructional coaching within an organization influences practice and increases outcomes: • Cultivate a coaching culture. Use is based on data skills, data use skills, and content understanding of users: • Cultivate expertise development in context/content.

22. Continuous Support of Users(continued) Use is influenced by the context of the decision and/or content area in which the decision is made (i.e., literacy data and decisions are different than those for numeracy). • Construct sessions to build efficacy for data skills, data understandings, and suggestions for use • To do this, use modeling, elaboration, and feedback. • Cultivate collaborative work groups within organizations. • Focus workshops on one context/content area. • Identify key problems for users based on data analysis. • Bring in content experts to help with solutions. • Disseminate easily understood, colorful 1-2 page flyer with visualized data, problem identified by the data, solutions to the problem, and implications for decisions.

23. What does the research say about decision making resulting from data use?

24. For Effective Decision Making Focus on continuous organizational or implementer improvement, rather than on summative judgment. Focus on underlying processes related to client outcomes--focus decisions that improve learning rather than test scores. Use programs that have at least good evidence of effectiveness (See IES What Works Clearinghouse.) Capacity for use is necessary, but not sufficient: • Start with goals, then align data to goals • Embed within systemic change • Create common language and culture • Develop multiple structures/layers for decision-making Translate Numbers into Meaning Translate Meaning into Action

25. Sources Biesta, 2007. Bowers, 2009. Datnow, Park, & Kennedy-Lewis, 2012. Dunn, Airola, Lo, & Garrison, 2013. Ikemoto & Marsh, 2007. Luo, 2008. Mandinach, 2012. Mandinach, Honey, & Light, 2006. • Marsh, McCombs, & Martorell, 2010. • Park & Datnow, 2009. • Rogosa, 2005. • Slavin, et al., 2013. • Supovitz, 2009. • Swan & Mazur, 2011. • Wohlstetter, Datnow, & Park, 2008. • Wohlstetter, Park & Datnow, 2008. • Wu, 2009.

26. SLDS Webinar 5-18-11 Questions or comments?

27. Contacts State Support Team & SLDS Team: Missy Cochenour, (909) 241-4264 Missy.cochenour@sst-slds.org Maddie Fromell, (202) 219-7117 Maddie.fromell@ed.gov Panelists: Casey Hanson, hansoncb@missouri.edu Avisia Whiteman, avisia.whiteman@state.mn.us Dr. Lori Bland, lbland2@gmu.edu SLDS Webinar