1. Principal Connections: Using Data to Inspire Esther Rosenfeld OLA SuperConference February 3, 2006

2. Education Facts of Life in Ontario 2006 Focus on Improving Student Achievement Provincial EQAO Literacy and Numeracy Targets School Boards Must Have Plans to Achieve Targets Schools must have Individual School Improvement Plans Board and School Plans are based on the concept of Data-Driven Decision Making Resource allocation is based on all of the above

3. The Data-Driven Education Universe Data-driven decision making is a process of making choices based on appropriate analysis of relevant information. A similar term is Evidence-Based Practice. It is now standard practice in all aspects of education. It involves:  Using quantitative data to diagnose a problem  Developing a plan to deal with the problem  Creating quantifiable targets to assess success in dealing with the problem  Assessing the success of the plan/initiative by looking at measurable improvements  Being accountable for the success or lack of success of the plan/initiative

4. Intent: Improving Student Achievement by Improving Instruction and Improving Operations and Supports Ideally, more access to better information enables educational professionals to test their assumptions, identify needs, and measure outcomes. Ideally, schools can use data-driven decision making to provide more individualized instruction to students, identify successful instructional strategies, better allocate resources, and communicate better with parents and the community. Ideally, it can transform teaching and learning through continuous improvement.

5. School Improvement Planning Process 1. REVIEW: –Examine what makes a school effective –Establish a school improvement team –Review Board system plan and priorities –Review current school plan –Identify School Issues and Needs through use of quantifiable data (e.g. Demographic profile) –Examine evidence and collect additional data 2. PLAN: –Develop plan in the context of Provincial Curriculum and Provincial Initiatives –Develop plan in the context of Key Board System Priorities. –Identify school priorities based on data –Develop School Plan with quantifiable outcomes and improvement targets and indicators 3.IMPLEMENT and ASSESS: –Monitor implementation using indicators

6. Another look at SIP Planning AwarenessWhere are we now?..collecting information...establishing a baseline Decision making (Cooperative Planning) Where are we going? How do we get there?...developing plans...establishing timelines Action (Make the plan happen) How will we know we have been successful?...making it happen over a period of time...evaluating outcomes for all stakeholders

7. So? Where is the school library in this process? How is the library accountable for student achievement How can the school library become a central part of the School Improvement Plan? What needs to be done to make this happen? What kind of quantifiable data can the school library provide at the various stages of the School Improvement Process?

8. So? What kinds of evidence, quantitative and qualitative, can teacher-librarians collect about the impact of the school library on student achievement? How can this collected evidence enable a central role for the school library in raising achievement?

9. Types of Quantitative School Library Data Library Automation Systems provide valuable circulation statistics and collection data that can be used at the planning stage to identify problems and set targets. Library Automation Systems then can provide statistics to analyze progress and determine whether targets have been met. TLs can easily collect many types of quantitative data related to aspects of the school library program

10. Areas of the Library Program which need to be measured David Loertscher asserts that all aspects of library program need to be measured in order to boost student achievement and make the library central to school improvement planning: Collaboration Reading Information Literacy Technology Loertscher provides a variety of templates in We Boost Achievement!

11. Ross Todd’s Framework Ross Todd asserts that: There needs to be a framework for collecting evidence at: -the learner level -the teaching unit level -the organization level Both direct and indirect evidence and data should be collected

12. Using Library Automation System Statistical Reports: Examples Total circulation—monthly and yearly—with month to month and year to year comparisons Number of books checked out per student with monthly and yearly comparisons Number of books checked out per class with monthly and yearly comparisons Number of books checked out by boys, girls with % comparisons Statistics on number of books checked out by individual students (e.g. at-risk students) with monthly and yearly comparisons or comparisons with school average

13. Using Library Automation System Statistical Reports: Examples Number of titles in the school library in various forms (books, videos, audios, kits, etc.) Number of books per student in the school library collection (can be compared with system-wide average or regional average) Number of titles for curriculum areas or special programs (e.g. astronomy books, books for boys, ESL, reading clubs) Age of the books in the school library collection (statistics can be generated by date of publication in various subject areas or by Dewey range, e.g. books on Canadian history) Number of new books added to the school library collection within a time period Number of books weeded

14. Titlewise Collection Analysis Provides a quantitative analysis of the age of the library collection as a whole and segmented by Dewey ranges An essential tool which provides information which goes far beyond library automation system reports Useful for gap analysis and collection development planning, and budget planning as part of whole school plan

15. Quantitative Data to Collect: Some Examples Number of students who have taken part in reading clubs, independent reading programs, reading contests, etc. Number of collaborative teaching units with teacher- librarian and classroom teachers Number of lessons/projects/units that address specific skills related to information literacy (e.g. research process lessons, Internet and database searching, academic honesty) Usage by students of the school library web page and online information databases Tracking free voluntary reading

16. Quantitative Data to Collect: Some Examples Number of book talks Number of special events organized (e.g. Black History Month, Author visits, Family Reading Night, etc.) Number of students using the library to read and do research before and after school. Pre and post tests to assess student learning of information literacy skills and ICT skills Number of presentations to staff and parents Number of teacher requests for resources Number of classes booked into the library for various purposes Measuring increase in collaboration with various teachers

17. Collecting Qualitative Data “The most common statistics collected by teacher-librarians are quantifiable data such as the number of books circulated and the number of instructional sessions conducted. Such data are important; however, they do not begin to describe the tangible outcomes…that are directly linked to local student success. In today’s schools where accountability for student learning extends to the entire educational community, teacher- librarians must be able to provide qualitative evidence of student performance in library-led instruction.” --Ross Todd, 2003

18. Examples of Qualitative Data: Direct and Indirect Evidence Student, Teacher, and Parent Surveys –Questionnaires, Checklists Reflections, Response Journals, Learning Logs, Blogs Samples of Student Work Rubrics Portfolios and Research Folders Interviews with Students—video and audio Collaboration Templates Tracking change from low-level research assignments to assignments which stress critical thinking Annual Reports Student and Teacher pre and post self-assessments

19. Collecting Data: Action Research Action research is a means to more systematically and rigorously examine one’s teaching and its impact on student learning. The current school restructuring movement has site- based, shared decision-making at its core. School teams are now accountable for their programs and practices. It is not enough for teams merely to make decisions. They must make decisions that are data driven. Therefore, it is necessary for them to be much more deliberate in documenting and evaluating their efforts. Action research is one means towards that end. Violet Harada 2002

20. Data Driven Decision Making and Evidence based practice: Key question for School Libraries “Evidence based practice revolves around the key question: What differences does our school library and its learning initiatives make to student learning? That is, what are the differences, the tangible learning benefits, defined and expressed in ways that lead a school community to say: "we need more of this!"? Ross Todd

21. The School Library can have a central role in the school plan Literacy Information Literacy Information Technology Student Success (Grades 7-12) Facility Improvement Numeracy Safe Schools

22. Resources David Loertscher and Ross Todd, We Boost Achievement!: Evidence-Based Practice for School Library Media Specialists, 2003. OSLA Toolkit www.accessola/osla Toronto District School Board, Improving Student Achievement @your library: A School Library Handbook for Administrators, 2004.