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Comprehensive Data Analysis for Educational Leaders

Explore detailed data submissions for teachers, administrators, and parents. Analyze student performance and system outcomes to drive positive change. Understand different data sources and tools available.

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Comprehensive Data Analysis for Educational Leaders

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  1. December 2006 Data Presentation to Michigan Leadership Institute February 12, 2007

  2. Data Portrait Summary Counts

  3. Invariable Comments #1 When first seeing Data Portraits, people will say “Where did you get this?” AND “This is wrong.”

  4. Teacher Cert • Due Process • Financial Records • Financial Records Detailed Data Submissions/Collections Parents, Teachers Administrators Others Summary Data Outputs • Due Process • Teacher Cert Data Portrait IEP MiCIS CA60 Local Data AYP Report Card CEPI FORMS Students (reality) Systems Standard & Poors GALDRE OTHER TESTS MEAPMiACCESS MEAs Data Sources Chart

  5. Data Tools Available – Dec count • Data Portraits – one variable summary • Detail Reports – student detail with two-variable cross-tabs • Excel file with all YOUR data • Trend charts to see changes over time and filter further

  6. Cross Tabs in the Details

  7. EdCharts Trend

  8. Invariable Comments #1 When first seeing Data Portraits, people will say “This is not enough?” AND “This is wrong.”

  9. The meaning behind the comments • “this is not enough” – type 1 means • “I am not sure what this data says about our system, and I need to know more in order to understand what is going on” • “this is not enough” – type 2 means • “we know how to code our data so you won’t bug us” OR “you have to spoon-feed us more”

  10. Other Data Silos In Addition to the December Count • Assessment from OEAA • Outcomes from TOPS • Exit, Discipline, Referral from SRSD • Personnel from REP • SPSR from LEA Workbooks • Due Process from prototypes • Survey results from multiple grants • LEA Enrollment from SRSD

  11. The QUALITY of Other Information • Exit Data from SRSD – we have to do the Data Verification thing all over again because unused data is likely to be inaccurate • MEAP data is likely to be good because it is used regularly • WSU survey data is likely to be good because they have a rigorous process and review • Cleaning OUR data is a lot easier than cleaning or using OTHER data

  12. Going Further • What does your data mean? • How does your system affect outcomes? • Are you satisfied OR do you need to change something? • How can you communicate the data to others?

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