Skip to content

Final project for the 2019 Colombia Data Science for All (DS4A) program.

Notifications You must be signed in to change notification settings

CarlosLlano/ds4a-app

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

ds4a-app

Final project for the 2019 Colombia Data Science for All (DS4A) program.

For any doubts, please contact:

Name Email Github Linkedin
Carlos Llano [email protected] https://github.com/CarlosLlano linkedin.com/in/carlosllanolozano
Jaison Gonzalez [email protected] https://github.com/jagd724 linkedin.com/in/json724
Jaime A. Vargas [email protected] https://github.com/jaimevargascruz linkedin.com/in/jaime-a-vargas-c

Introduction

In Colombia, the ICFES exam is the standard way to measure the quality of secondary education. Five different topics (mathematics, natural sciences, english, language and social science) are tested, and the student is given a normalized global score that allows to rank a person within the whole set of students.

Each year, it is said that these results are influenced by the inequality between regions (departments). Some explanations are related with social factors like the family average income. However, there is no clear understanding of what socioeconomic factors affect truly the performance on the ICFES exam.

For this very reason, we consider it is important that elected officials such as mayors, governors and ministers have a tool to better understand how the performance in ICFES results is affected by socioeconomic factors in order to formulate well-informed policies that have a real impact on Colombian society.

Application Overview

Dashboard

It allows the user to explore all the data available that contains information of the last 11 years in regard to scores and socioeconomic factors of approximately six million students.

ICFES SCORES

1 icfes scores

SOCIOECONOMIC FACTORS

2 socioeconomic

3 socioeconomic

DIFFERENT GEOGRAPHIC LEVELS

4 city level

DIFFERENT PERIODS

5 different periods

DETAILED ANALYSIS

6 detailed-1

6 detailed-heatmap

Simulator

It allows to predict the average score in a city by changing certain socioeconomic variables.

7 simulator

Segmentation

It gives a general overview of how the schools in Colombia are characterized by identifying groups with similar features.

8 segmentation

About

Final project for the 2019 Colombia Data Science for All (DS4A) program.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published