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] Using Data to Improve Instruction: Building on Models that Work St. Louis, MO Professional Development Model Using the Surveys of Enacted Curriculum.

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Presentation on theme: "] Using Data to Improve Instruction: Building on Models that Work St. Louis, MO Professional Development Model Using the Surveys of Enacted Curriculum."— Presentation transcript:

1 ] Using Data to Improve Instruction: Building on Models that Work St. Louis, MO Professional Development Model Using the Surveys of Enacted Curriculum Gary Money and Maren Harris Learning Point Associates September 13, 2007

2 ] SEC Collaborative ODE www.ode.state.oh.us/Accountability/ sec/ Council of Chief State School Officers www.SECsurvey.org Wisconsin Center for Education Research www.SEConline.org Learning Point Associates/NCREL www.SECsupport.org TERC Regional Alliance DEC Project www.ra.terc.edu/DEC

3 ] Purpose: What data might we use to inform decisions that would addressing student learning issues?

4 ] Traditional Model Identify “Best Practices” for Achievement Problems Identify Shortcomings in Student Performance

5 ] PHASE 1 Predict PHASE 3 Infer/Question PHASE 2 Observe Go Visual Data-Driven Dialogue With what assumptions are we entering? What are some predictions we are making? What are some questions we are asking? What are some possibilities for learning that this experience presents us with? Surfacing experiences, possibilities, expectations What important points seem to “pop out”? What are some patterns or trends that are emerging? What seems to be surprising or unexpected? What are some things we have not explored? Analyzing the data What inferences and explanations can we draw? What questions are we asking? What additional data might we explore to verify our explanations? What tentative conclusions might we draw? Generating possible explanations copyright TERC 2006, adapted from Data-Driven Dialogue: A Facilitator's Guide to Collaborative Inquiry by Bruce Wellman and Laura Lipton, MiraVia, LLC, 2004.

6 ] Context: Fifth grade math teachers meet to reviewing state level student assessment data

7 ] Context: Predict: Strengths and Weaknesses of Student Assessment Geometry (GE) Data Analysis and Probability (DA) Number Sense and Operations (N&O) Measurement (M) Algebraic Concepts (AL)

8 ] Question: What other data sets might inform us about student weaknesses we observe?

9 ] Three Lenses: Curriculum Instruction Assessment

10 ] Data Sets: District Math Curriculum State Standards Fifth Grade Math (Fifth Grade Indicators) SEC Teacher (Enacted) Math Content Course Grain Map All Fine grain maps Selected Instructional Practices SEC Fifth Grade Math State Standards

11 ] What are your recommendations to address the area of weakness? What research can be used to justify suggested changes in instruction? How would we measure progress?

12 ] Categories of instructional strategies that effect student achievement Identifying similarities and differences Summarizing and note taking Reinforcing effort and providing recognition Home work and practice Nonlinguistic representations Cooperative learning Setting objectives and providing feedback Generating and testing hypothesis Questions cues, and advance organizers Marzano What Works in Schools

13 ] Maren Harris P: 312-288-7606 > F: 312-288-7601 E-Mail: maren.harris@learningpt.orgmaren.harris@learningpt.org Gary Money P: 231-668-1853> F: 630-649-6700 E-Mail: gary.money@learningpt.org


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