1 / 14

Module 5: Data based decision making

Module 5: Data based decision making . Data Analysis—How will we know to make changes?. Three Tiered Model. SMART Goals. S—specific, clearly stated, simple M —measurable based on quantifiable data A—Attainable and realistic R—Related to student performance and achievement T —Time bound.

dotty
Download Presentation

Module 5: Data based decision making

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Module 5: Data based decision making Data Analysis—How will we know to make changes?

  2. Three Tiered Model

  3. SMART Goals • S—specific, clearly stated, simple • M—measurable based on quantifiable data • A—Attainable and realistic • R—Related to student performance and achievement • T—Time bound

  4. DATA??? • Baseline: Data before interventions are put in place • Aim line or goal: How much you want to achieve • Graph the data to determine whether or not progress is being made.

  5. Progress Monitoring • Key features of effective formative evaluation systems • Student performance is measured frequently (e.g., once/week) and results in quantitative data • Progress is monitored toward an observable, measurable, and ambitious goal • Progress is graphed and viewed regularly • Data decision rules are used to evaluate the effectiveness of interventions and determine when modifications to interventions are needed

  6. Progress monitoring • Valid • Reliable • Fidelity of data

  7. Activity 1 Let’s practice

  8. Data Analysis • Comparison • What are you comparing? • What is the standard for comparison? • How do you know if you are making progress?

  9. Develop Decision-Making Rules for Progress Monitoring • How will I know if the student is making adequate progress? • Two general types of decision-making plans • 3-Point or 4-Point Decision-Making • Trend line Analysis

  10. Data Driven Decisions for Tier II and Tier III • How will I know if I need to change interventions? • How will I know if enough progress has been made? • When will I know if the Tier level needs to change? • Do I have appropriate documentation?

  11. Data decisions at Tier I • Have we looked at the data? • Class wide • Building wide • District wide • Have we made decisions based on the data? • Class wide • Building wide • District wide

  12. Activity 2 Reflection

  13. Professional development • Needs • What type of professional development do we need? • Who is going to do it? • When are we going to do it? • Length of time needed • Follow-up/Accountability • Options

  14. This Presentation was Created byHigh Plains Educational Cooperative For more information on MTSS, contact HPEC 620-356-5577 For additional information on MTSS visit http://www.kansasMTSS.org

More Related