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My Nine “Truths” of Data Analysis A Discussion and Exploration of Implications Dr. Ronald Thomas Center for Leadership in Education at Towson University.

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Presentation on theme: "My Nine “Truths” of Data Analysis A Discussion and Exploration of Implications Dr. Ronald Thomas Center for Leadership in Education at Towson University."— Presentation transcript:

1 My Nine “Truths” of Data Analysis A Discussion and Exploration of Implications Dr. Ronald Thomas Center for Leadership in Education at Towson University

2 Objectives for this Session In this session, we will: React to several possible “truths” of data analysis Make then our “truths” and explore ways that they might be taken to scale in every data- analysis team in every school

3 My Ten Seconds of Fame On the back page of the June 15, 2011, issue of Education Week: “My Nine ‘Truths’ of Data Analysis” Commentary

4 Our “Low Tech” Blog Please read the commentary and the blog that followed it (pages of the handout). React to my truths or your colleagues’ insights by posting notes under the appropriate “truth.”

5 Not “My,” But “Our” Truths Is this true? If not, what is? How do we make it true in every data team, in every school?

6 Not “My,” But “Our” Truths Is this true? If not, what is? How do we make it true in every data team, in every school?

7 “Our” Truth # 1 We don’t need “data driven” schools. We desperately need “knowledge driven” schools.

8 “Our” Truth # 2 Data analysis is not about numbers. It is all about improving instruction. All educators can be involved, whether they are number wonks or number phobics.

9 “Our” Truth # 3 Data are not best analyzed alone. Data analyses are most effective when they are performed with other teachers who share the same standards and assessments.

10 “Our” Truth # 4 Teacher teams need to be able to meet in “data dialogues” during the school day for 45 minutes to an hour at least once every two weeks, and more often, if possible.

11 “Our” Truth # 5 The most productive data- driven teams follow established analysis protocols and enforce clear procedural and relationship norms.

12 “Our” Truth # 6 The most important questions in data analyses are not “What did the students score?” and “How many passed?” The most important questions are: “What do the students know?” “What do they not know?” and “What are we going to do about it?”

13 “Our” Truth # 7 We have achieved maximum impact from using student interventions as the primary improvement strategy. For accelerated progress, we need to center faculty members on strengthening the alignment of their curricula, instruction, and assessment around the standards.

14 “Our” Truth # 8 We need to build the capacity of teacher teams to reflect on their work and to make ongoing instructional adjustments based on their analysis of what does and does not work for their students.

15 “Our” Truth # 9 We must clearly articulate compelling reasons why teachers should invest time and effort in data analysis, and that reason is NOT to meet AYP or Race to the Top goals.

16 Acting on “Our” Truths 1. Which “truth” are you most passionate about? 2. What is one actionable step that you will take before Christmas to move your school toward “living this truth” more fully?


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