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Artificial Intelligence-Based System for Detecting Attention Levels in Students

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Using administrative data to identify elementary schools at increased risk for student absences

¹Dept. of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA.

The Journal of School Health

|September 1, 1995

Summary

Administrative databases can identify elementary schools with high absence rates, aiding targeted interventions. This method efficiently identifies at-risk schools for absence reduction programs.

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Area of Science:

Public Health
Education Policy
Data Science

Background:

School absenteeism is a significant issue impacting student success.
Identifying at-risk schools is crucial for effective intervention strategies.

Purpose of the Study:

To demonstrate an analysis method for identifying elementary schools at risk for high absenteeism using administrative data.
To support the targeting of absence reduction interventions.

Main Methods:

Utilized existing administrative databases for data analysis.
Developed a method for generating relative risks of school absence.

Main Results:

The analysis method successfully identifies elementary schools with high percentages of school absence.
Relative risks for school absence were generated using administrative data.

Conclusions:

Administrative databases offer a resource-efficient way to identify schools needing absence reduction support.
This approach can assist in developing targeted strategies to decrease elementary school absence.