DATA REVIEW A Comprehensive Needs Assessment For School Improvement Planning Susan Wright, Program Evaluator Northside ISD 1/18/2019

What will we do in this session? Discuss the process. Conduct a data review. Share the product, “Promising Practices,” that arose from data review discussions. 1/18/2019

What is Data Review? formal process of structured communication Data review is a formal process of structured communication designed to increase student achievement. 1/18/2019

Why Data Review? Comprehensive needs assessment is crucial to campus success. Campuses need assistance and staff development in collecting and analyzing data. District staff and campus staff need to communicate about specific needs and expectations. 1/18/2019

Providing Decision Support Data-driven decision making improves performance. Instruction Staff Dev Funding DATA Federal Titles Special Programs Account-ability Testing Planning 1/18/2019

School Improvement Planning Team Instruction Executive Director (Chair) Administration Assistant Superintendent Compensatory Programs Director Special Education Executive Director Bilingual Education/ESL Director Title 1 Supervisor At-Risk Coordinator Program Evaluator Instructional Supervisors for Subjects 1/18/2019

Campus Representatives Principal Grade Level Team Leaders Reading and Math Specialists/Coordinators Others Vice Principal or Academic Dean Counselor Special Program Campus Coordinators Other Leaders 1/18/2019

Meeting Agenda Introductions Purpose of the Meeting Orientation to the Data Forms Data Review Discussion of Other Factors Not Covered Discussion of Strengths and Weaknesses Discussion of School Improvement Plan 1/18/2019

Data Collection State Tests National Tests TAKS, SDAA, RPTE National Tests CogAT, ITBS Primary Achievement Measures & Standards IRI, TPRI, Local Benchmark, etc. Other Measures Retention, F/R Lunch, Suspensions, Stability, Attendance, etc. 1/18/2019

Orientation to the Data Forms Distribute forms and highlighters. Walk through the data. Examine the relationships. 1/18/2019

Data Review Measures 1 District MME/TLI 2 Grade Level/Program Trends What percentage of students are passing? How do grade levels do from year to year? How do groups of students grow as they move through the school? What subgroups are struggling? How do subgroups do compared to District? How about higher level achievement? What other factors impact achievement? 1 District MME/TLI 2 Grade Level/Program Trends 3 Cohort Analysis 4 Substantial Subgroup Variance 5 District Comparison 6 TAAS Excellence Indicators 7 Other Factors 1/18/2019

Data Analysis Compare to targets/goals. Did campuses meet their targets? Should targets be adjusted? Compare to district, state and nation. Compare to last year. Do cohorts grow as they move through school? Are subgroups experiencing problems? Triangulate with multiple measures. 1/18/2019

We’re from Central Office and we’re here to help. Let the data speak for itself. Ask campus to provide context for interpretation. Recognize campus efforts. Be positive and supportive. Find ways to improve support. 1/18/2019

Discussion Gains higher than expected: Gains lower than expected: Document successful strategies. Gains lower than expected: Reasons? Low cohort? Next grade ready? Successes on other campuses? Staff concerns Trained in programs? Program consistency? Staff development? New staff supported? Curriculum alignment? Grade level planning? 1/18/2019

Grade 3 performance – a critical measure How does primary program support 3rd? Are TAAS/TAKS scores consistent with other measures, i.e. aptitude? Low subgroups Are special strategies in place? Did they work? Are safeguards in place? How are at-risk students targeted? How are special programs operating (DOI)? Special factors Are there boundary changes, overcrowding, high mobility, staff factors (high turnover, etc.)? 1/18/2019

School Improvement Plan Were district initiatives addressed? Were campus goals addressed? Were needs uncovered in data review addressed? 1/18/2019

Promising Practices Successful practices are discussed on each campus. Examples and documents are collected. Books are produced and disseminated to each campus at the end of the process. 1/18/2019

Remember… “Not everything that can be counted counts, and not everything that counts can be counted.” Albert Einstein 1/18/2019