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10+ Ways to Analyze Data

10+ Ways to Analyze Data. Presenter: Lupe Lloyd Lupe Lloyd & Associates, Inc. Accountability Systems. State Accountability or AEIS Federal Accountability or AYP Performance-Based Monitoring Analysis System or PBMAS Data Validation (Leaver, Assessment, Discipline). Critical Success Factors.

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10+ Ways to Analyze Data

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  1. 10+ Ways to Analyze Data Presenter: Lupe Lloyd Lupe Lloyd & Associates, Inc.

  2. Accountability Systems • State Accountability or AEIS • Federal Accountability or AYP • Performance-Based Monitoring Analysis System or PBMAS • Data Validation (Leaver, Assessment, Discipline)

  3. Critical Success Factors

  4. Paradigm shift from intuition, tradition, or convenience… • Scattered staff development / smorgasbord • Budgetary decisions based on prior practice or priority programs • Staff assignments based on interest and availability • Reports to the community about school events • Goal setting by administrators or teachers based on favorite initiatives or fads

  5. …and other school culture cycles • Staff meetings that focus on operations and dissemination of information • Parent communications via twice-a-year conferences, open-houses and newsletters • Grading systems based on each teacher’s criteria of completed work and participation • Periodic administrator team meetings focused solely on operations

  6. To Data-Driven Decision Making • Focused staff development that addresses problems/needs identified by data • Budget allocations to programs based on data-informed needs • Staff assignments based on skills needed as indicated by the data • Organized factual reports to the community about the learning progress of students • Goal–setting based on data about problems and possible explanations

  7. …and more… Data Driven Decision Making • Staff meetings that focus on strategies and issues raised by the local school’s data • Regular parent communication regarding the progress of their children with specific data • Grading systems based on common criteria for student performance that reports progress on the standards as well as work skills • Administrative team meetings that focus on measured progress toward data-based improvement goals

  8. Top 10 Uses of Data in Schools • Data can uncover problems that might otherwise remain invisible • Data can convince people of the NEED for CHANGE • Data can confirm or discredit assumptions about students and school practices • Data can get to the root cause of problems, pinpoint areas where change is most needed, and guide resource allocation • Data can help schools evaluate program effectiveness and keep the focus on student learning results

  9. Top 10 Uses of Data in Schools • Data can provide the feedback that teachers and administrators need to keep going and stay on course • Data can prevent over-reliance on standardized tests 8. Data can prevent one-size-fits-all and quick solutions • Data can give schools the ability to respond to accountability questions • Data can build a culture of inquiry and continuous improvement (Love, 2000)

  10. DAILY Formative Assessments Are the teachers asking higher order thinking questions to assess on-going learning? Are students learning it? Is there other evidence of learning taking place? Complexity of Student Assessment Data

  11. WEEKLY Classroom Curriculum Tests, Quizzes Are we testing what was taught? Did students learn it? Is there evidence of learning? Complexity of Student Assessment Data

  12. CURRICULUM UNITS Performance assessments Can students apply and generalize what they have learned? What evidence of cognitive learning skills do they have? Complexity of Student Assessment Data

  13. STUDENT REPORT CARDS How are students reporting in general? Do the grading standards truly reflect their performance? Complexity of Student Assessment Data

  14. Diagnostic Assessments What are students’ cognitive strengths and needs? How are those needs supported in the classroom? Complexity of Student Assessment Data

  15. BENCHMARKING Are students meeting the state standards? Are we testing what is taught? Are we testing with the same rigor? Complexity of Student Assessment Data

  16. State and National Assessments Are all students performing optimally? Are all subgroup populations performing optimally? Complexity of Student Assessment Data

  17. Factors That Affect Student Performance Individual, educational, and demographic factors Previous educational experience and success Education Factors Student Factors Current programs, practices, & support Behaviors, attitudes, & aspirations

  18. An Integrated Database DEMOGRAPHIC DATA INTEGRATED DATA BASE STUDENT EDUCATION DATA STUDENT PERFORMANCE DATA DATA THAT SUPPORTS EQUITY, ACCOUNTABILITY, AND IMPROVEMENTS

  19. Systemic Database System Student Demographics Gender, ethnicity, disability, economic level, English proficiency, mobility, & other characteristics • Education Data • Grade level • Feeder School • Prior Education • Subjects/Courses • Special Ed. • Bilingual Ed. • School-to-career • Title I • Performance Data • State Assessment Data • Standardized Test Data • Performance Assessments • Diagnostic assessments • Classroom Assessments • Grades • Attendance • Disciple • Dropout rates • Graduation rates INTEGRATED DATA BASE • Unlimited Disaggregation Across: • Multiple Student Characteristics • Multiple Educational Factors • Multiple Performance Measures

  20. DATA TEAM Establishes goals Defines questions Collects and organizes data Makes meaning of data or disaggregates Communicates actions needed Evaluates actions DATA COACH Member of Data Team Communicates goals Provides Data Training Assists with data disaggregation Assists with implementation of actions Collects outcomes for evaluation PLC Data Team for Data Driven Dialogue

  21. CRITICAL QUESTIONS FORDATA COLLECTION Performance • How are specific groups of students; i.e., All, African American, Hispanic, White, Economical Disadvantaged performing on state and standardized assessments in all contents? • How are students, who are enrolled in different learning academies, specific course offerings, and special programs performing? • What are the proficiency levels of various student groups in content and skill areas? • How do the grades given to students compare to their scores on state and other standardized measures?

  22. CRITICAL QUESTIONS FORDATA COLLECTION Feeder System Analysis: • What are the characteristics and literacy skills of the incoming ninth-grade class? • How has each subgroup performed in the last three years for state assessments, attendance, and discipline trends? • What is the failure rate of students by gender and ethnicity in core courses?

  23. CRITICAL QUESTIONS FORDATA COLLECTION ATTENDANCE • What are the enrollment patterns at different grade levels? • What are the characteristics of students with high absence rates? • How does absence affect student performance? • Are students with high attendance rates achieving success? • What types of students are dropping out?

  24. CRITICAL QUESTIONS FORDATA COLLECTION CURRICULUM • Is the curriculum vertically and horizontally aligned to the TEKS. • Is the scope and sequence aligned to the testing schedule? • Are teachers teaching the TEKS to be assessed with Student Expectations and rigor? • In the areas of low performance such as reading and math, what strengths and weaknesses are in the curriculum?

  25. INSTRUCTIONAL PROGRAM Do grading patterns suggest inconsistencies in grading criteria across learning academies, subject areas, or course offerings? Are students who are enrolled in specific programs achieving positive results on different measures? Are specific groups of students enrolling in specific courses? What is the failure rate of students by gender and by ethnicity in core courses? How is SES or other interventions showing improvement? CRITICAL QUESTIONS FORDATA COLLECTION

  26. DROPOUTS What is impacting the completion, graduation, and dropout rates? What are the characteristics of these students? By subgroup, what programs have they participated in that have not resulted in graduation? How many overage students are in need of credit recovery? CRITICAL QUESTIONS FORDATA COLLECTION

  27. Data Driven Dialogue

  28. The Inquiry Cycle

  29. Create a Data Room with Data Walls

  30. Contact Information • LUPE LLOYD • National Educational Consultant • Lupe Lloyd & Associates, Inc. • Data and Instructional Coach • Specialist in Bilingual/ESL support • Professional Service Provider • lupelloydinc@sbcglobal.net • (210) 872-1960

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