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Integrated Data Based Problem Solving:

Integrated Data Based Problem Solving:. Model Development & District Capacity. Don Kincaid and Brian Gaunt University of South Florida. Advanced Organizer. Context & Foundation MTSS Defined IDBPS process as core MTSS component Core features of Problem Solving

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Integrated Data Based Problem Solving:

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  1. Integrated Data Based Problem Solving: Model Development & District Capacity Don Kincaid and Brian Gaunt University of South Florida

  2. Advanced Organizer Context & Foundation • MTSS Defined • IDBPS process as core MTSS component • Core features of Problem Solving Designing an IDBPS process • Purpose, Assumptions, and Goals • Defining/Characterizing “Integration” Implementation and Sustainability • Active Leadership • Resource Management • Data Technology/Management • Effective Teaming/Coaching Supports/PD • Fidelity of Data Use Practices • Data System Alignment

  3. Design vs. Use • Designing an IDBPS process requires common language and understanding of a structured problem-solving process. • Using an IDBPS process requires understanding of how key questions around PS guide integration of all MTSS components and implementation and sustainability of practices.

  4. General Data Use Practices & Critical PS Questions Context & Foundation

  5. 1. MTSS Defined MTSS is a term used to describe an evidence-based framework of educating students that includes providing high quality, effective core instruction, intervention supports matched to student needs and uses data based problem solving to integrate all academic and behavior instruction and interventions.

  6. 1. MTSS Key Components • Resolute & Effective Leadership • Professional Development • Systems Coaching/Supports • Content Coaching/Supports • IDBPS Process • Three Tiered model of service delivery • Tier 1 goals; HQ-EBPs; Aligned C-I-A • Family & Community Engagement • Fidelity & Accountability of Practices • Program Evaluation – “effectiveness” • Resource: MTSS Q&A Doc

  7. 2. IDBPS as Core Component • Overall Assumptions: • “Data” should include both quantitative and qualitative. • Data is used with all steps of a 4-step problem-solving model. • Data should always be used to drive both implementation practices and decisions around student supports/instruction. • Guiding questions are an effective strategy to guiding efficient & effective data utilization practices.

  8. 2. Data Utilization – In General • Educators should use key questions to guide data use (Feldman & Tung, 2001; Lachat & Smith, 2005; Protheroe, 2001) • Structured data use approaches: use data rather than be used by data (Wayman & Stringfield, 2006) • Recognize & plan for common barriers to data use (Coburn & Talbert, 2006; Honig & Venkateswaren, 2012; Kerr et al., 2006; Lachat & Smith, 2005; Little, 2012; Young, 2006)

  9. 2. Data Utilization – In General • Ensure Common Lang/Understand (Wade, 2001; Young, 2006) • Expand definition of a “data system” beyond just technology – include data practices/culture!! (e.g., Armstrong & Anthes, 2006; Honig & Venkateswaren, 2012; Ingram et al., 2004).

  10. 3. Core Features of an IDBPS process • Let’s ensure common language and understanding of a 4-step PS model • Handout – guiding questions • Tier 1 • Tiers 2 & 3

  11. Purpose, Assumptions, & Goals Designing an IDBPS Process

  12. 4. Purpose of an IDBPS Model • 4-step PS process is core to integrating A & B • Engaging in effective IDBPS process as a “way of work” requires • Common language and understanding of PS • Clear/shared strategies for implementing an IDBPS framework • IDBPS process should include both micro and macro applications.

  13. 4. Assumptions to Developing an IDBPS Process • An IDBPS process should be a “best case scenario” for schools to set as a long-term goal • School level application vs. District/State level support • Description of IDBPS process requires context

  14. 4. Assumptions to Developing an IDBPS Process • Common IDBPS process at all grades vs. use of different data types or sources across grades. • An IDBPS process should be flexible to local context, prescriptive research-based practices, but also set a minimum expectation of common practice across all grades/content.

  15. 4. Goals of an IDBPS Model • Define and describe “integration” • Articulate essential components of IDBPS process • Describe range of implementation levels • Balance conceptual understanding & prescriptive practices • Use IDBPS process to guide development of self-evaluative methods to monitor: • Implementation of IDBPS process, • Fidelity of use if IDBPS process • Sustainability of IDBPS process over time.

  16. 5. “Integration” Defined • An effective IDBPS process should allow us to “Integrate” the following: • Academic standards & Behavior expectations • Tiers of instructional delivery and supports • Multiple sources/types of data • School & district resources to support fidelity of PS • All of the above are achievable through use of critical PS guiding questions.

  17. 5. Integrate Academic/Behavior • Note: Academics need to be integrated in their own right. CCSS, anyone? • Defining “behavior” or “engagement” on a continuum • Problem ID to integrate the Tiers; A& B goals • Problem Analysis to integrate academic and behavior problem-solving • Plan Intervention to integrate A & B supports • Plan evaluation to integrate student outcomes with fidelity of educator practices • Resource: handout -“Engagement” defined.

  18. 5. Integrate Tiers of Service Delivery Problem Identification I II Response to Intervention III Problem Analysis Intervention Design

  19. 5. Integrate Data Sources/Types • Use Critical PS questions to: • Align assessments/data with appropriate questions. • Develop decision-rules for interpretation and decision-making for particular questions. • Ensure availability of appropriate data to answer questions. • Design efficient data management systems

  20. 5. Integrate school/district data resources • Resource Types: • Communication Resources (schedules, data reports, culture of data use/expectations) • Human Resources (knowledge, skills, availability) • Material Resources (Curr./Instruc./Assess/tech-management) • Financial Resources (flexible vs. fixed allocation)

  21. 5. Integrate school/district data resources • Implications for guiding… • Avail. of Personnel • Leadership roles/responsibilities • Coaching roles/responsibilities • Teacher roles/responsibilities • Technology design and operation

  22. Benefits to Resource Mapping Available Data/Resources Wasted time/$? Or Compliance Reporting? Data available to answer PS questions Gaps in data system infrastructure Alignment of Critical PS Questions & Available Data Resources Problem-Solving Questions

  23. Structures, Resources, & Skills to Support IDBPS Practices Implementation & Sustainability

  24. Active Leadership • Ensure “culture of valuing data use” (Armstrong & Anthes, 2001; Bernhard, 2000; Honig & Venkateswaren, 2012; Ingram et al., 2004; Kerr et al., 2006; Lachat & Smith, 2005; Supovitz & Klein, 2003) • Create sense of urgency for improvement through data • Communicate and Model IDBPS Expectations • Monitor efficiency and fidelity of IDBPS practices. • Promote IDBPS as a “way of work” – roles/respons. • Ensure selection/use of evidence-based practices • Monitor and ensure sufficient resources

  25. Active Leadership • Invest in ongoing PD on IDBPS practices (Cromey, 2000; Leithwood, 2010) • Develop effective schedules to support IDBPS practices that are goal oriented

  26. IDBPS Resource Management • Time to collect, organize, enter, share, & use the data to make important decisions • User-friendly technology – integrated reports • Authority to make decisions/allocate • Personnel skills sets (common & advanced)

  27. IDBPS Resource Management • Communication • Matched PD for staff based on data • Available curr./instruc./assess. Materials • “resource mapping” as a tool.

  28. Data Technology • Technology is only good if it is used! • Critical PS questions guide tech development and report options. • Staff roles & responsibilities for data system from collection to interpretation.

  29. Data Technology • Efficiency of access to relevant data. • Build with “end user” in mind. • Align tech use demands with roles/responsibilities of staff • User Friendly – PD needs/Coaching? • Potential to integrate multiple sources/types

  30. Effective Teams &Coaching Supports • Effective team structures/processes • Communication protocols and decision rules for data use (i.e., triggering resource allocations) • Alignment of roles/responsibilities • Common skills vs. Unique/Expert Skills

  31. Effective Teams &Coaching Supports • Effective team facilitation • Coaching: PD & fidelity of IDBPS process • Knowledge of available resources & allocation authority to design instruction/interventions

  32. More Infrastructure & Fidelity of IDBPS • Goal: All students receive matched, integrated instruction/supports as needed and when needed! • Some threats to reaching goal: • Fidelity of using a structured IDBPS process • Adherence (fidelity) to assessment protocols and appropriate assessment selections • Fidelity of implementing instruction/intervention plans.

  33. Data System Alignment • Common “data use” barriers • (high probability hypotheses) • Use structured problem solving process as leaders to resolve system barriers affecting educators’ efficient and effective use of data at the grade/classroom/individual levels. • Handout – Common Data Use Barriers • Handout – Checklist of Data System Components

  34. Thank You! • Questions/Comments?

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