Final project for the 2019 Colombia Data Science for All (DS4A) program.
For any doubts, please contact:
| Name | Github | ||
|---|---|---|---|
| Carlos Llano | carlos.llano9499@gmail.com | https://github.com/CarlosLlano | linkedin.com/in/carlosllanolozano |
| Jaison Gonzalez | jaison.gonzalezd@gmail.com | https://github.com/jagd724 | linkedin.com/in/json724 |
| Jaime A. Vargas | jaimevargasc92@gmail.com | https://github.com/jaimevargascruz | linkedin.com/in/jaime-a-vargas-c |
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.
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
SOCIOECONOMIC FACTORS
DIFFERENT GEOGRAPHIC LEVELS
DIFFERENT PERIODS
DETAILED ANALYSIS
It allows to predict the average score in a city by changing certain socioeconomic variables.
It gives a general overview of how the schools in Colombia are characterized by identifying groups with similar features.
