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Palomar Project: Predicting School Renouncing Dropouts, Using the Artificial Neural Networks as a Support for Educational Policy decisions

NCJ Number
170588
Journal
Substance Use and Misuse Volume: 33 Issue: 3 Dated: (1998) Pages: 717-750
Author(s)
V Carbone; G Piras
Date Published
1998
Length
34 pages
Annotation
The use of Artificial Neural Networks (ANN) as a data processing method to aid educators in identifying and determining interventions for potential school dropouts was examined using data from 96 high school students in Italy.
Abstract
The Palomar project aimed to provide an instrument for use by educators and administrators who want to intervene in truancy, dropping out, and other school problems. The research was designed to predict which students are at risk for school problems or failure; select and focus on a student based on the information given; verify the effectiveness of the interventions; and produce scenarios for a group of students, a class, or a group of schools. The analysis revealed that the Prediction System ANN using the program SCHEMA is able to determine intervention strategies to produce the maximum results of a group of students and determine an optimal path for a whole institution to prevent or limit the need for school guidance. Tables, figure, footnotes, author biographies and photographs, and 28 references (Author abstract modified)