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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
Summary
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.
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.