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Predicting NAT Scores of Public Schools
Predicting NAT Scores of Public Schools
PREDICTING
NAT SCORES
OF PUBLIC
SCHOOLS
Using Machine Learning Algorithms in
Predicting NAT School Performance
AUGUST 10, 2019| JEMS (JEAN.EDLIN.ESA)
What is
NAT?
Standardized Test given to Grade 6, Grade 10
and Grade 12 students nationwide. Its
objective is to determine the academic level,
strengths and weakness of students.
NATIONAL ACHIEVEMENT TEST
Our
Problem
1. Can we predict the NAT scores of a
public school?
2. What are the key factors that
greatly affect the NAT results?
OUR DATASET
ELEMENTARY SCHOOLS (ES) SECONDARY SCHOOLS (SS)
OUR DATASET
NAT
PERFORMANCE
DISTRIBUTION
INTERNET
CONNECTION BY NAT
PERFORMANCE
POWER
DISTRIBUTION BY
NAT PERFORMANCE
CLASS SIZE
SCHOOL TYPE
DISTRIBUTION
DISTRIBUTION OF
SCHOOLS PER
REGION AND THEIR
AVERAGE NAT
SCORES
DISTRIBUTION OF
SCHOOLS PER
REGION AND THEIR
AVERAGE NAT
SCORES
PARTIAL BUDGET
FOR OPERATIONS
PER REGION
POVERTY INCIDENCE
MACHINE LEARNING METHOD
LOGISTIC REGRESSION
DECISION TREES
RANDOM FOREST CLASSIFIER
XGB CLASSIFIER
NAT Test Score
Interpretation
Score Descriptive Equivalent
96 to 100% Mastered (M)
86 to 95 % Closely Approximating Mastery (CAM)
66 to 85% Moving Towards Mastery (MTM)
35 to 65% Average Mastery (AM)
16 to 34% Low Mastery (LM)
5 to 15% Very Low Mastery (VLM)
0 to 4% Absolutely No Mastery (ANM)
Correlation
of features
to NAT
Scores
ES SS
Model
Performance
ES
SS
Feature
Importance
using XGB
Classifier
SS
ES
Feature
Importance
using Random
Forest
Classifier
SS
ES
RECOMMENDATION
• FURTHER STUDY
• DATA CULTURE
• USE OF DATA SCIENCE FOR
POLICIES
“The youth is the hope
of our future.”
Jose Rizal

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Predicting NAT Scores of Public Schools