Model Description:
According to KAG 2020-21 dataset, primary school is divided into lower primary and higher primary categories. Classes 1-5 come under lower primary and classes 6-8 come under higher primary. The Bayesian network models the school drop-out ratio in primary schools (lower and higher) of Karnataka districts/talukas.
Model:
Variables:
Node/Attribute | Description | Data Source |
Enrolment Proportion | The proportion of students enrolled in the lower and higher primary to the total population | KAG 2020-21 |
BPL Proportion | The proportion of Antyodya card holders to total population | KAG 2020-21 |
Girls’ Toilet | Availability of girls’ toilets in schools | KAG 2020-21 |
Boys’ Toilet | Availability of boys’ toilets in schools | KAG 2020-21 |
Drinking Water Availability | Availability of clean drinking water in schools | KAG 2020-21 |
Playground | Availability of playgrounds in schools | KAG 2020-21 |
Electricity | Electricity supply in schools | KAG 2020-21 |
Library | Availability of libraries in schools | KAG 2020-21 |
Ramp | Availability of ramps in schools | KAG 2020-21 |
Compound | Availability of compounds in schools | KAG 2020-21 |
Computer | Availability of computers in schools | KAG 2020-21 |
Student-teacher Ratio | Student-teacher ratio | KAG 2020-21 |
Student Dropout | Student dropout ratio in lower and higher primary schools | KAG 2020-21 |
Variables Correlation Matrix :
Intervention Modelling:
Intervention Code | Intervening Node | Description | Ease of intervention | Total models impacted | Models impacted | Domains impacted | Data stories impacted |
I1 | Student: teacher ratio | Hire more teachers to reduce the dropout rate | 3 | 1 | E2.2 | Education | |
I2 | Girls Toilets | Safe hygiene and sanitation for female students | 4 | 1 | E2.2 | Education | |
I3 | Boys Toilets | Safe hygiene and sanitation for male students | 4 | 1 | E2.2 | Education | |
I4 | Availability of drinking water | Basic drinking water facilities for high participation in school attendance | 4 | 1 | E2.2 | Education |
DISCLAIMER: AI predictive models are meant to support and augment expert decision-making, and not a replacement for the same. It is important for AI model predictions to be vetted by domain experts before committing to action