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The Massachusetts Early Indicator Index Project

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The Massachusetts Early Indicator Index Project Vladimir Hyppolite Current State of Early Warning Index Department of Early Education Care (DEEC) EWI system in the ... – PowerPoint PPT presentation

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Title: The Massachusetts Early Indicator Index Project


1
The Massachusetts Early Indicator Index Project
  • Vladimir Hyppolite

2
Current State of Early Warning Index
  • Department of Early Education Care (DEEC)
  • EWI system in the planning stages
  • Need Identified- Early childhood experts believe
    that the probability of high school drop out
    starts before kindergarten due to
  • Inadequate access to quality pre-school education
  • Family risk factors (limited English proficiency,
    unstable or low income, health issues)
  • Attendance rate of children enrolled in early
    care
  • Department of Elementary Secondary Education
    (DESE)
  • EWI system began as 2008 pilot in 24 urban
    districts for incoming 9th graders. It is now
    available to districts statewide
  • Started with 8 indicators but now four used 8th
    grade attendance, MCAS scaled scores (English
    Math), age as of Sept 1, number of in/out of
    school suspensions
  • Districts use EWI to mitigate high school dropout
    risks by targeting students for enrollment into
    existing programs and creating new policies that
    can improve outcomes

3
Early Indicator Index (2009-10 version)
4
SLDS Early Warning Index Project
  • Goals Outcomes
  • Create a EWI model that
  • Provides student level risk indicators that span
    birth to 16
  • Focuses on students falling off track for their
    level rather than just at-risk for not graduating
    high school on-time
  • Is based on national research from experts in
    risk identification for early childhood care and
    k-12 education
  • Uses linked student data from the MA birth to 16
    longitudinal data systems project being developed
    through SLDS
  • Deliver an EWI system integrated with the
    birth-16 data systems
  • Provide educators useable information that inform
    decisions on interventions that help at risk
    students stay on track
  • Resource permitting, evaluate incorporating
    college dropout indicators
  • Challenges
  • Reliance on data collected in existing systems
  • Do EEC, ESE and DHE systems capture the same data
    elements
  • Quality of data entered in each agencies systems
  • Data sharing MOUs between agencies
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