1 / 27

Analyze the Data

Comprehensive Needs Assessment Professional Development. Analyze the Data. Session Questions. Why is data analysis a critical aspect of school/district improvement? How can data analysis focus the improvement work in a school/district?. 2. Data Analysis Can Help Us Answer Several Questions:.

ezra-wynn
Télécharger la présentation

Analyze the Data

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. Comprehensive Needs Assessment Professional Development Analyze the Data

  2. Session Questions • Why is data analysis a critical aspect of school/district improvement? • How can data analysis focus the improvement work in a school/district? 2

  3. Data Analysis Can Help Us Answer Several Questions: • Who are we? • How do we do business? • Where are we now? • What are the gaps? What are the root [underlying] causes of the gaps? • Where do we want to be? How can we get to where we want to be? (Bernhardt, 2006) 3

  4. Delightful School Scenario 4

  5. Questions About Delightful School 1. What data are currently being collected by Delightful Intermediate School? 2. What additional data might the school want to collect? 3. What strengths and weaknesses do you notice as you read the scenario? 5

  6. Predictions and Assumptions About What Exists 6

  7. Possible Predictions • Which is higher? • reading or math performance • district compared to school • Has performance increased or decreased over 3 years? • Which groups of students are performing high? Low? • Ethnicity • Economically disadvantaged • Special education • LEP • Other predictions? 7

  8. Prediction Cards (Index cards) Prediction 2 Prediction 1 Prediction 3 Prediction 5 Prediction 4 This activity is adapted from Data-Driven Dialog: A Facilitators Guide to Collaborative Inquiry, by Bruce Wellman and Laura Lipton. 8

  9. Predictions and Assumptions • One person draws a card and reads a prediction. • Everyone speculates on assumption(s) underlying the prediction. • Next person draws a card and process continues. • Spend no more than 3 minutes on each prediction. 9

  10. Predictions and Assumptions Predictions Assumptions 10

  11. Why Assumptions Are Important • Accepted as fact • No actual proof that they are true • Serve as frames of reference for what we believe to be true • Underlie our predictions about future events • Usually unaware of our assumptions 11

  12. AYP Indicators 12

  13. 2009 Adequate Yearly Progress Guide http://ritter.tea.state.tx.us/ayp/2009/guide.pdf 2009 AYP Indicators 13

  14. AYP Indicators 14

  15. 15

  16. 16

  17. Delightful School Scenario: Data Analysis 17

  18. Rules of Engagement • Make sure everyone participates. • Respect each other’s ideas. • Stay focused on the task. • Avoid • “because” statements, • the “blame game,” and • being defensive. 18

  19. BECAUSE 19

  20. Rules of Engagement • Review one piece of data, with everyone at the table simultaneously looking at the same data. • While the data are important to understand, also important is the collective nature of this activity—everyone discussing the same data. 20

  21. District and School AYP Data • Three years of AYP reports for ABC District and Delightful Intermediate School • Graphs of these reports disaggregated by ethnicity, economically disadvantaged, special education, and LEP 21

  22. Adequate Yearly Progress Guide http://ritter.tea.state.tx.us/ayp/2009/guide.pdf 22

  23. Additional Data Sets • Demographic data • Attendance data • Content area survey results • Themes from focus groups and conversations with leaders • If available—Findings from system capacity rubric, additional relevant data 23

  24. Examining the Data • Use highlighters to indicate data that “pop out” • Differences among subgroups of students • Content areas in the greatest need for improvement • Patterns or trends in demographics or other data • Need for clarification or more information 24

  25. Examining the Data • Recorder will chart group’s “pop outs” • Remember: No “becauses” You have 30 minutes for this review. Spend approximately 5–6 minutes on each data piece. 25

  26. Reflection • What are the benefits and challenges of analyzing data collaboratively? 5 minutes for table discussion, then report out 26

  27. References • Bernhardt, V. L. (2006). Using data to improve student learning in school districts. Larchmont, NY: Eye on Education. • Texas Education Agency. (2009). 2009 adequate yearly progress (AYP) guide for Texas public school districts and campuses. Austin, TX: Division of Performance Reporting. • U.S. Department of Education. (2006). Designing schoolwide programs: Non-regulatory guidance. Washington, DC: Author. • Wellman, B., & Lipton, L. (2004). Data-driven dialog: A facilitators guide to collaborative inquiry. Arlington, MA: MiraVia. 27

More Related