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DATA: What is it? Where is it? What do I do with it?

DATA: What is it? Where is it? What do I do with it?. Gwen Giddens, CASL Past-President and Director, Learning Resource Services for Colorado Springs School District 11 giddegb@d11.org 719-520-2254. Purpose.

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DATA: What is it? Where is it? What do I do with it?

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  1. DATA: What is it? Where is it? What do I do with it? Gwen Giddens, CASL Past-President and Director, Learning Resource Services for Colorado Springs School District 11 giddegb@d11.org 719-520-2254

  2. Purpose • Purpose of this workshop – To develop your leadership skills through understanding the use of data to improve your school’s library program. • What do you most want from this day? • Hooray for Diffendoofer Day!

  3. Data: What is it? What is data?

  4. Data prediction What % of people were on a diet during the last week of December ?

  5. 24% according to Dec. 2003Newsweek

  6. How does this prediction compare to analyzing school data?

  7. Overview of types of school data Data should not be punitive. It should be used for improvement. Use data to collaborate. Data are plural. Data demonstrate correlation not causation.

  8. - biases

  9. Data: What is it? Pair and Share PERCEPTION, DEMOGRAPHIC, SCHOOL PROCESSES, STUDENT LEARNING • What type of data is CSAP test scores? • Frameworks? • Student subgroups? • Parent surveys? • Library circulation data?

  10. Group temperature rating on“Data: What is it?”

  11. Data: Where is it? • Where are CSAP test scores found? • Frameworks? • Student subgroups? • Parent surveys? • Library circulation data? • Other?

  12. Data: Where is it? Learning Buddy 1 What & where are your school’s or library’s… Or Give an example of… 1. …demographic data? 2. …perception data? 3. …student learning data? 4. …processes?

  13. Group temperature rating on“Data: Where is it?”

  14. Data: What do I do with it? Learning Buddy 2 • Look at frameworks, item maps, and released items for a particular grade level. • Where are these found on the web? • Highlight ones which correlate with information literacy. • What should you do with this?

  15. Data: How can I use it to improve my school’s library program? • What should students know and be able to do in my school’s library by the time they leave/graduate from my school? • What data could I use to help get this accomplished?

  16. What could you do with this data?

  17. What could you do with this data?

  18. Data: How can I use it to improve my school’s library program? Learning Triads – chart paper • What data should I utilize to improve my school’s library program? • PERCEPTION • DEMOGRAPHIC • SCHOOL PROCESSES • STUDENT LEARNING

  19. Group temperature rating on “Data: What do I do with it?”

  20. Group work at 10:30 • Group table work -Data Driven Dialogue

  21. Data Driven Dialogue Phase 1 Predict Phase 2 Observe Phase 3 Infer/Question

  22. Ground Rules for Data Driven Dialogue • Respect for Divergent Opinions • Listen • Avoid finger pointing and blame • Agree that student learning comes first • Use inquiry and data, not assumptions

  23. Phase 1: Predict • I predict… • I assume… • I wonder… • I am expecting to see…

  24. Phase 2: Observe Starters • I am struck by… • I notice that… • I’m surprised by… • I see…

  25. Phase 2: Observe • What important points seem to pop out? • What patterns or trends are emerging? • What is surprising, unexpected? • What questions do we have now? • How can we find out?

  26. Because

  27. Go Visual Graph and Share It!

  28. Collaboration norms for small work groups • Pausing • Paraphrasing to let someone know they have been heard • Probing • Putting ideas on table • Paying attention to self and others • Presuming positive presuppositions • Pursuing a balance between advocacy and inquiry

  29. Small work groups • Facilitator/ Task master – Keep things going with all voices heard (round robin or brainstorming). Predict, observe, and go visual with data on the wall (agree to consensus or near consensus). • Timekeeper – finish by 10:50 am • Materials getter – chart paper, markers, school data • Recorder - Record what you hear, not what you may have been thinking. • Reporter – Reports out to large group.

  30. Data to improve the school’s library program Building Your Data Wall to share Phase 2: Observations with “no because.” Remember that data are used for correlation not causation. Phase 1: Predictions (Put biases on table.)

  31. “It is a fatal fault to reason whilst observing, though so necessary beforehand and so useful afterwards.” Charles Darwin

  32. Working lunch from 11:30-12:30 • Read Allison Zmuda’s article, “Where Does Your Authority Come From?” • At your table, comment on something that that stands out in your mind about the article.

  33. References • Bernhardt, Victoria L. Using Data to Improve Student Learning in Elementary Schools. Larchmont, NT: Eye of Education, 2003. • Love, Nancy. Using Data/Getting Results: A Practical Guide for School Improvement in Mathematics and Science. Norwood, Massachusetts: Christopher-Gordon Publishers, Inc., 2002. • Zmuda, Allsion. Where Does Your Authority Come From? School Library Media Activities Monthly, Sept. 2006.

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