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Evaluation of a Predictive Model -- Montana Early Warning System. Technical Report

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Bibliographic Details
Title: Evaluation of a Predictive Model -- Montana Early Warning System. Technical Report
Language: English
Authors: Robin Clausen (ORCID 0009-0005-4212-0224), Montana Office of Public Instruction
Source: Grantee Submission. 2023.
Peer Reviewed: Y
Page Count: 87
Publication Date: 2023
Sponsoring Agency: National Center for Education Research (NCER) (ED/IES)
Contract Number: R305S210011
Document Type: Reports - Research
Education Level: Elementary Secondary Education
Descriptors: Identification, Dropouts, At Risk Students, Prediction, Models, Evaluation, Reliability, School Districts, Adoption (Ideas), Elementary Secondary Education
Geographic Terms: Montana
Abstract: Research over the monitoring of at-risk youth. Behavioral interventions have been the primary focus of this literature past two decades has focused on one aspect of dropout prevention: early identification an however, there is renewed emphasis placed on attendance and academic risk factors under ESSA. Recognizing a need to promote early identification, stakeholders within the Montana Office of Public Instruction (OPI) framed a comprehensive system of supports in FY 2013, principally a diagnostic tool, which allows for the linkage of data to intervention and the ability to target resources where the intervention is most likely to be effective. Such supports became known as the Montana Early Warning System (EWS). This evaluation is based on three separate tasks. The first of which is an analysis of the functional process of predicting dropout and graduation. Does the system predict as reliably dropout and graduation? We know the system predicts dropout well based on the process of refinement of the model. However, we do not know if the model reliably predicts graduation. The second task focuses on analyzing the degree of implementation of the program by creating a classification of low, medium, and high adopters. It further analyzes mediating and moderating factors to the implementation, the quality of the tool, the role of interventions, and the effectiveness of the tool. The third task is primarily quantitative and focuses on subgroups identified in the analysis.
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2025
Access URL: https://opi.mt.gov/Leadership/Data-Reporting/Research-Portal#9965312917-evaluation-of-a-predictive-model-montana-early-warning-system-2023
Accession Number: ED672196
Database: ERIC
Description
Abstract:Research over the monitoring of at-risk youth. Behavioral interventions have been the primary focus of this literature past two decades has focused on one aspect of dropout prevention: early identification an however, there is renewed emphasis placed on attendance and academic risk factors under ESSA. Recognizing a need to promote early identification, stakeholders within the Montana Office of Public Instruction (OPI) framed a comprehensive system of supports in FY 2013, principally a diagnostic tool, which allows for the linkage of data to intervention and the ability to target resources where the intervention is most likely to be effective. Such supports became known as the Montana Early Warning System (EWS). This evaluation is based on three separate tasks. The first of which is an analysis of the functional process of predicting dropout and graduation. Does the system predict as reliably dropout and graduation? We know the system predicts dropout well based on the process of refinement of the model. However, we do not know if the model reliably predicts graduation. The second task focuses on analyzing the degree of implementation of the program by creating a classification of low, medium, and high adopters. It further analyzes mediating and moderating factors to the implementation, the quality of the tool, the role of interventions, and the effectiveness of the tool. The third task is primarily quantitative and focuses on subgroups identified in the analysis.