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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.

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Presentation on theme: "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."— Presentation transcript:

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. 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? What do you most want from this day? Hooray for Diffendoofer Day! Hooray for Diffendoofer Day!

3 What is data? Data: What is it?

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

5 24% according to Dec. 2003 Newsweek

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.

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11 - biases

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

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

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

21 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?

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

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

24 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 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? What data could I use to help get this accomplished?

25 What could you do with this data? CSSD #11 School Library Collection Report - Fall 2006 Name of SchoolTotal VolumesNumber of TitlesMost RecentAverage Pub. Yr.Oldest Middle84157280200719871903 1367210482200619911894 1368411331200719841868 186999106200619961930 98288538200619901870 94318591200619891889 1286710166200619901903 1500711550200619841905 1390412071200619851903 High12641046200619891904 1948817419200619821837 1297711898200619861893 1487613262200619781849 1824517520200619741866 76404744200719911923 1496514062200719841887

26 What could you do with this data?

27 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? What data should I utilize to improve my school’s library program? –PERCEPTION –DEMOGRAPHIC –SCHOOL PROCESSES –STUDENT LEARNING

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

29 Group work at 10:30 Group table work - Data Driven Dialogue Group table work - Data Driven Dialogue

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

31 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

32 Phase 1: Predict I predict… I assume… I wonder… I am expecting to see…

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

34 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?

35 Because

36 Go Visual

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

38 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). 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 Timekeeper – finish by 10:50 am Materials getter – chart paper, markers, school data Materials getter – chart paper, markers, school data Recorder - Record what you hear, not what you may have been thinking. Recorder - Record what you hear, not what you may have been thinking. Reporter – Reports out to large group. Reporter – Reports out to large group.

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

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

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

42 References Bernhardt, Victoria L. Using Data to Improve Student Learning in Elementary Schools. Larchmont, NT: Eye of Education, 2003. 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. 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. Zmuda, Allsion. Where Does Your Authority Come From? School Library Media Activities Monthly, Sept. 2006.


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