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Bilingual, Immigrant, and Refugee Education Directors’ Meeting Seattle, WA May 18, 2012

Effective Data Systems and Data Reflective Practices for ELL Achievement. Dr. Katherine Meads, Executive Director CMS ESL Department Charlotte “Nadja” Trez, ESL Specialist CMS ESL Department Danielle Miller, Director CMS Office of Accountability.

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Bilingual, Immigrant, and Refugee Education Directors’ Meeting Seattle, WA May 18, 2012

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  1. Effective Data Systems and Data Reflective Practices for ELL Achievement Dr. Katherine Meads, Executive Director CMS ESL Department Charlotte “Nadja” Trez, ESL Specialist CMS ESL Department Danielle Miller, Director CMS Office of Accountability Bilingual, Immigrant, and Refugee Education Directors’ MeetingSeattle, WAMay 18, 2012

  2. Performance Management Performance management requires collaboration and a change in the district’s culture. It is intended to strengthen employee performance at all levels of the district by helping individuals understand how his or her effectiveness impacts CMS. Access to real-time performance data will lead to continuous improvement, so that CMS becomes an organization that nurtures and fosters professional excellence.

  3. Managing for Performance Portals SuperintendentPrincipalTeacherExceptional ChildrenData Wise

  4. Data Wise Process

  5. Student Profile Provides information regarding exit requirements, demographic information, and student schedule.

  6. Assessment History Snapshot Under the student summary, a comprehensive chart of a student’s assessment history will appear with grade level, subject, test, scale score, achievement level, percentile, LEA status, and date the test was taken.

  7. Comprehensive Assessment History Current year attendance information, attendance history, EOG Assessment results, and EOC assessment records.

  8. Language Minority LEP Report

  9. Language Minority LEP Report • Demographic Information • Grade Level • Student ID • Student Name • NOMS Language • Country of Origin • US School Entry Date • LEP Exit Date • LEP Status • ESL Status

  10. Language Minority LEP Report • Achievement Information • ELP Test Date • ELP Test Type • ELP Proficiency Levels • Reading • Writing • Listening • Speaking • Comprehension • Literacy • Overall ACC • NC EOG / EOC Achievement • Reading • Math • Science • English I • Algebra I • Biology

  11. Language Minority LEP Report • Parameters provide end users with the ability to customize the reports to their specific needs

  12. Language Minority LEP Report ESL Status Grade Level Language LEP Status

  13. Dynamic Filtering Options

  14. Graduation Exit Standards Data

  15. Transcript Analysis Data Transcript Analysis Report

  16. EOC and EOG Predictive Data

  17. Lexile & Quantile Data

  18. End of Year Assessment Data

  19. End of Year Assessment Data The EOC Report offers student-level roster of students currently enrolled in an EOC course, their ABC pre-test information before 2008-09, and their EOC expected score for the current class enrollment.

  20. ELL Data Reflective Practices • LEP Committee Chairs Meeting • Data Collection Applications Training • Data Wise Process Training • Data Portal Training • ELL Data Mining and Reflective • Practices

  21. ELL Data Collection Applications • English Language Proficiency Test Data • ELL Testing Accommodations Data • Language Minority / ELL / ESL Program

  22. ELL Data Apllication

  23. ELL Data Application

  24. Language Minority LEP Report • Achievement Information • ELP Test Date • ELP Test Type • ELP Proficiency Levels • Reading • Writing • Listening • Speaking • Comprehension • Literacy • Overall ACC • NC EOG / EOC Achievement • Reading • Math • Science • English I • Algebra I • Biology

  25. Using Data-Why? • The need for communication and reflection. • The need for collaboration. • The need for inquiry, improvement, and growth in student learning.  • A reflective analysis of the data to inform your instructional practices.

  26. How Do You Know? Data analysis as a collaborative process of inquiry leads to consensus about what is most effective in program effectiveness and curriculum and instructional approaches.

  27. Analyzing Data – The Process

  28. WIDA

  29. The table of grades 9-12 ACCESS Data Step 1 – Data Table

  30. Step 2 – Graphic Representation

  31. Step 3 – Observe, Discuss, Document Patterns Identified: • There was a drop in the number of students tested across all grade levels from 2009-2010. • Low distribution of students at opposite ends of the spectrum (bell curve). • Differences of each of the levels is no more than 4 % at grade 10 from 2008-09 to 2009-10. • Percentages only tell so much. It is interesting to see the numbers of students across the grade levels for each year.

  32. Step 4 – Hypotheses of Practice Pattern/Observation: Overall numbers of LEP students tested on ACCESS in the district dropped significantly Hypothesis: More students exited LEP status as a response to SIOP Hypothesis: The district is losing students to other districts Hypothesis: Not all eligible LEP students are being assessed on the ACCESS test

  33. Step 5 – Classroom Connections • SIOP Hypothesis • Classroom connections: • Provide initial training for new teachers in SIOP strategies • Provide on-going professional development for teachers who have previously been trained • Visit and collaborate with teachers at other schools/districts who have proven to be successful in the implementation of SIOP

  34. Next Steps • Future Projects • ELL Transcript Evaluations driven by “Data Portal Transcript Analysis Report • Scheduling recommendations to meet the state graduation requirements • Title III program researcher for SIOP and ExC-ELL impact studies • ELL achievement and progress monitoring • Building capacity of LEP Chairperson at each school

  35. Next Steps • Future Projects • Strategic ELL Data Literacy PD for administrators and LEP Chairpersons

  36. Questions and Answers

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