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Managing District and School Information
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  • Talk about the multiple measures of data based upon Victoria Bernhard and ask how they are measuring these. http://eff.csuchico.edu/ is Victoria Bernhardt’s website All school data can fall into one of the 4 categories Student demographics can predict results at the district and school levels – need to look at policies for unit of change at district level Student leanring is the test scores. Answers often found tied to district demographic level School process is the instructional strategies. Standards and assessment at the school and classroom level Organize participants’ data around the room. Do a gallery walk and write three sentences “What I saw.” Share. The discuss with neighbor “so what”.
  • Data Warehousing is a process , not a product It is a process for properly assembling and managing data from various sources for the purpose of answering educational questions and making decisions that were not previously possible. The Educational Imperative Planning and Design The User Environment The Implementation Operation and Maintenance Accessible at different levels Builds graphs Disaggregates on the fly Point and click/drag and drop user interfact Creates standards reports with click of a mouse Able to follow a cohort Ex www.tetradata.com
  • http://www.mediabrains.com/client/eschooln/bg1/search.asp What is the scope of this integration project? What efficiencies (“most useful” automations) do you want to gain through integration? What data needs to move and to where? What are the changes you expect to see through integration?
  • Learnia is the Online Assessment Solution that your school/district has chosen for you to implement and use to gather formative data on your students. Site Code: LN02 Username: Sayre Password: S4936
  • What this training will answer for the attendees:
  • EDsmart is a solution for data driven decision-making from Public Consulting Group Username: njsmart\\spaul Password: T3ch!cian

Managing District and School Information Managing District and School Information Presentation Transcript

  • Managing District and School Information Sandi Paul Director of Technology Sayreville Public Schools NJ EXCEL MIS Session
    • AGENDA
    • Tuesday, April 7, 2009
    • Using Data to Increase Management Efficiency
    •  
    • 5:30 – 6:00 Technology To Increase Management Efficiency – Overview by Barbara Longo
    • 6:00 – 7:00 Discussion
    • Sandi Paul – EdAnalyzer, Learnia, PowerSchool, Budget/Payroll, and other research.
    • l
    • 7:00 – 7:45 PM Blog entry in http://njexcel.ning.org
    • Prompt: You are to reflect on what defines a data rich district. What data needs to be collected and for what purpose? What resources are needed and what systems need to be in place to effectively manage student data? Cite what your district is using and suggest areas of improvement. Include URL links to back-up your reflection of managing student data. You may want to reflect back on Vicki Bernhardt’s work.
    •  
    • 7:45 – 8:00 Read a colleague’s data blog and share your thoughts
    •  
    • 8:00 – 8:30 Group sharing of what defines a data-rich district.
  •  
  •  
  •  
  • Schools Interoperability Framework (SIF)
    • .. a set of standards developed to dramatically improve the overall efficiency of educational administration in K-12 schools, particularly in the areas of data entry and data management.
  • Learnia New Jersey 2009-2010 Content Description Assessment & Information Pearson
  • Learnia ClassViews
    • Learnia has 2 pre-built benchmark assessments, ClassViews, at each grade level 3-8 in the subjects of reading and math
    • Item bank containing items in math (G3-8), reading (G3-8), science (G4&8), and writing (G3-8)
  • Learnia Item Bank: 2008-09
    • Now
    • – Initial item bank (G5-8) containing items in math and reading
    • Spring 2008
    • – Complete item bank (G5-8)containing items in
        • - Math and reading (G5-8) with 5 items per assessable CPI
        • -Science (G8) with 5 items per assessable CPI
        • -Writing (G5-8) with 10 prompts per grade
    • Fall 2008
    • – Initial item bank for grades 3 and 4 in math and reading
  • Item Bank (continued)
    • Winter 2008
    • – Complete item bank for grades 3-8 containing items in:
        • - Math and reading (G3-8) with 5 items per assessable CPI
        • -Science (G4&8) with 5 items per assessable CPI
        • Writing (G3-8) with 10 prompts per grade
  • Learnia Items
    • All items are aligned to the New Jersey CPIs!
    • There are open-ended and multiple choice items in the item bank for math, reading, and science, as well as writing prompts.
    • Patented answer rationale for all math, reading, and science items in the bank
  • Learnia Supports Your Instruction by:
    • Providing data that can be integrated into the instructional process
    • Allowing for differentiated planning and instruction
    • Monitoring student progress toward proficiency on NJ CCCS.
  • ClassViews™ State Benchmark Tests Key Feature Accountability snapshot Purpose Reports proficiency on assessments modeled after NJ ASK Content Areas Reading and mathematics Grades 3-8 Number of Forms (tests) 2 forms (per grade and subject) Length of Form Between 25-33 items per form About 2-6 open-ended (SCR & ER – in math) items per form
  • ClassLinks™ Item Bank Key Feature Answer choice rationale Purpose Diagnose student strengths and weaknesses Content Areas Reading, math, science, writing Grades 3-8, except science (4, 8) Number of Forms (tests) To be determined by educator Length of Form To be determined by educator
  • EDanalyzer Training January 2008
  • What is NJ SMART?
    • NJ SMART is a statewide multi-phased initiative that provides a comprehensive state data warehouse for student level data reporting
    • Phase I: State Assessment Data Warehouse
    • Phase II: Statewide Student Level Data Submissions (Oct 15, Dec 1 and EOY June 30)
    • Phase III: Unique Statewide Student Identifiers (SIDs)
    • Phase IV: EDanalyzer Roll-out & Training
    • Phase V: Additional Reporting Capabilities
    • Phase VI: District Data Marts
  • What is EDanalyzer?
    • EDanalyzer is an intuitive, easy-to-use tool that allows users to view and analyze their district’s assessment data in the NJ SMART data warehouse
    • Uses live data, meaning results are always as current as the most recent data loaded into the system.
      • Assessment data from 1999-present are currently loaded in the NJ SMART data warehouse
      • In the future, districts will be able to create local data marts
    • Helps districts begin to understand trends in achievement, and prompts users to ask questions and dig deeper into the data
    • Presents data that cannot be changed so there is no way to “mess it up”
  • Message from NJ DOE
    • EDanalyzer is one of several tools being provided to districts, and will supplement NJ DOE-based resources for evaluating student performance and using assessment data to inform instruction
    • Other resources include assessment score reports, electronic student data files, and score interpretation training materials
    • NJ DOE Office of State Assessments is currently rolling out an online formative assessment resource to support professional development in assessment literacy
  • Data Use Framework
    • To help data consumers gain a richer understanding of their data, PCG has developed a Data Use Framework centered around:
    • Measures
      • Multiple data sets allow for a more complete picture of student performance
      • Data sets can be broken down by proficiency level, scaled scores, program levels, and cluster scores
    • Disaggregators
      • Allow student data to be filtered to focus on a particular group of students based on certain characteristics
      • Reveal how the performance of one group of students differs from that of another
    • Analyses
      • Provides the ability to look at the data through different lenses
      • Will help answer questions that arise from the data
  • Measures
    • Current data loaded into the NJ SMART Warehouse:
      • Alternate Proficiency Assessment (APA)
        • Grades 3, 4, 5, 6, 7, 8, 11 and 12
      • Elementary School Proficiency Assessment (ESPA)
        • Grade 4
      • Grade Eight Proficiency Assessment (GEPA)
        • Grade 8
      • High School Proficiency Assessment (HSPA)
        • Grade 11 – Fall and Spring
      • High School Proficiency Test (HSPT)
        • Grade 11 – Fall and Spring
      • New Jersey Assessment of Skills and Knowledge (NJASK)
        • Grades 3, 4, 5, 6 and 7
      • Assessing Comprehension & Communication in English State to State for English Language Learners (ACCESS for ELLs)
        • Grades K-12
  • Disaggregators
    • Examples:
    • School
    • Demographics
    • Programs
    • Race/Ethnicity
    • Testing Accommodations
    • Time in District/School
    • Title 1
    • Void Reasons
  • Analyses
    • Examples:
    • Student Listing
      • Shows individual student information
      • A Student Profile shows all data of a particular student
    • Summary Statistics
      • Shows the mean, max, min, and standard deviation for a group of students
    • Correlation
      • Shows the strength of the relationship between two or more data sets
    • Explore For Measure
      • Provides a tool for analyzing multiple data sets over a number of years
    • Range Analyzer
      • Displays data for students who fall within a particular score range
  • Data Warnings
    • Do not compare performance on tests that have not been aligned
      • Don’t compare 3rd grade scale scores to 5th grade scale scores (except in a correlation analysis)
      • Don’t compare 3rd grade Math scale scores to 3rd grade ELA scale scores (except in a correlation analysis)
    • Do not make large inferences on only a few data points
      • If you apply multiple filters and have a small group of students, that may not be indicative of that entire demographic
      • Be wary of conclusions about a subject area based on one item on a single test
      • Be wary of conclusions about a student’s proficiency in a subject area based on performance on one test
  • Blog Assignment
    • You are to reflect on what defines a data rich district. What data needs
    • to be collected and for what purpose? What resources are needed and what systems need to be in place to effectively manage student data? Cite what your district is using and suggest areas of improvement. Include URL links to back-up your reflection of managing student data. You may want to reflect back on Vicki Bernhardt’s work.