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Related Experiment Videos

20/20 Analysis: taking a close look at the margins

M C Reynolds1, A G Zetlin, M C Wang

  • 1University of Minnesota.

Exceptional Children
|February 1, 1993
PubMed
Summary
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This study introduces 20/20 Analysis, an innovative method for identifying students needing support. It focuses on students with the least and most progress, offering a noncategorical approach to improving educational opportunities for all learners.

Area of Science:

  • Educational Psychology
  • Special Education
  • Learning Analytics

Background:

  • Traditional special education identification methods are often categorical and may not fully capture student needs.
  • There is a need for output-oriented, noncategorical alternatives to identify students for targeted educational support.

Purpose of the Study:

  • To present and evaluate "20/20 Analysis" as an experimental, output-oriented alternative for identifying students for special education.
  • To explore broad, noncategorical approaches to improving learning opportunities based on student progress data.

Main Methods:

  • The "20/20 Analysis" method identifies students in the lowest 20% and highest 20% of progress toward educational objectives.
  • Case studies of two schools were conducted to examine the application of this analysis.

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Main Results:

  • The analysis identified students with both the least and most progress, highlighting diverse learning needs.
  • Examining these student groups provided a basis for developing broad, noncategorical strategies for educational improvement.

Conclusions:

  • "20/20 Analysis" offers a promising noncategorical framework for identifying students and informing educational interventions.
  • This approach supports a shift towards output-oriented, individualized strategies for enhancing learning opportunities in schools.