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Data Science Blog > Featured > Baccalaureate Results Data Analyzing the BAC

Baccalaureate Results Data Analyzing the BAC

Tristan Dresbach
Posted on Jan 8, 2019

Project GitHub | LinkedIn:   Niki   Moritz   Hao-Wei   Matthew   Oren

The skills we demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

I. Context

The French Baccalaureate (BAC) is the final exam all French students must pass to graduate from high school. Not only is it necessary for graduation, but a student's performance on the BAC is the American equivalent to one's performance on the ACT/SAT for college applications. As I am myself a product of the French Lycee (high school) system and more specifically the BAC with a science specialization, I was hoping to answer questions I always had regarding the test as well as provide insights to future BAC takers through an R shiny app I built.

Before delving deeper, it is important to highlight the fact that a "departement" (correctly spelled with an "e" after the "t") is a French word denoting a region of France which has its own jurisdiction to a certain extent.

There are 3 general Baccalaureate sections offered to students, for which I analyzed the passing rates:

S: Scientific

ES: Economic & Social

L: Literary

I sought to create a general platform that French students could use to compare the performance of their school/departement against that of other students.

Questions I wanted to answer:

1) With S (Scientific) being the section geared towards hard sciences, I assumed that on average more students would gravitate towards ES (economic & social) which is less quantitative. Is this valid?

2) However, contrary to 1), there is a widely-accepted stereotype that โ€œsmartโ€ students choose S regardless of whether or not they are interested in science, which would contradict 1) and push more students towards S. Is this valid?

3) L is considered to have some of the most talented but also lazy students, meaning distributions of their passing rates should be more spread out compared to S and ES. Is this valid?

4) With the option of โ€œre-dosโ€ of the exam for students with grades between [8;10] out of 20 and all 210 students in my graduating class having passed their BAC I expected passing rates to be above 95%. Is this valid?

5) What are the strongest performing and weakest performing Lycees and departements in France? Are there any patterns between strong and weak Lycees being in certain departements?

II. The Data Set

I obtained the Lycee-level data on the French Government's website. I made several modifications to the data set before building out my shiny app:

1) Modification of column names that were duplicates for purposes of clarity

2) Creation of a rank feature for each school

3) Creation of a feature to isolate non-technical baccalaureates

4) Modification of the two Corsica departement codes from 2A and 2B to 29 and 30 to allow for mapping departement names over a map

5) French special characters were substituted for their traditional counterparts

III. Data Analysis

I built my shiny app to explore Baccalaureate passing rates from 3 main perspectives so that users can answer any potential question they may have:

1. National: One can examine the passing rates for all three sections individually as well as combined on an interactive map of France. Hovering your cursor over a departement will show the departement's name as well as its passing rate for the BAC type selected (its passing rate is the average passing rate of all of the schools located in that departement). In addition, 3 widgets under the map will show the user what the country's maximum, average and minimum passing rates are for a given section.

2. Departement: One can examine passing rates by selected departement for several different key statistics as shown below. All four charts can be combined to build one's understanding of the key drivers of a departement's performance.

3. Lycee: One can study the passing rates and student distribution amongst the sections for individual schools via a table. The table offers multiple ways the user can find the information they are looking for:

  1. there is a search bar to find a specific lycee
  2. the user can click on any of the column headers to sort by ascending or descending
  3. the user can control how many schools are displayed at once

IV. Conclusion

I was able to resolve my 5 questions thanks to app, and I hope that you will as well!

  1. Close to all departements have more S students than ES students.
  2. The S section actually has a lower national average passing rate than that of ES and has both a lower max. and min. than that of ES.
  3. Even though L has the largest distance between its max. and min., it actually has the least amount of departements with passing rates under 90%. L students are the most consistent in terms of being able to pass the BAC.
  4. The national average passing rate for all sections is 92.6%, quite close to 95%.
  5. The Hautes-Pyrenees is the best performing departement and Ille-et-Vilaine is the worst performing departement (96.1% and 87.4% respectively). Schools that are private and that do not offer a technical degree to students fare much better in their passing rates than their counterparts. 7.1% of Lycess had a 100% passing rate, with the worst three being Lycee Auto-Gere: 42%, Lycee Georges Briere: 50% and Lycee de l'Union: 63%

IV. Feedback

If you have any feedback or questions, please do not hesitate to contact me via LinkedIn.

About Author

Tristan Dresbach

Tristan is an aspiring data scientist with a track record of using data to drive significant and tangible business results in retail and financial services. He has hands on experience in R and Python in web-scraping, data visualization,...
View all posts by Tristan Dresbach >

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