French Baccalaureate Results

January 8, 2019
By

(This article was first published on R – NYC Data Science Academy Blog, and kindly contributed to R-bloggers)

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 to graduate, 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 Scientific BAC, I was hoping to answer questions I always had regarding the test as well as provide insights to future BAC takers. 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) In opposition to 1), there is a perpetuating stereotype that “smart” 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 and 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 “re-dos” 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) Column names that were duplicates were modified for clarity purposes

2) Created a rank feature for each school

3) Created a feature to isolate non-technical baccalaureates

4) Modified 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 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 finally 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. Feedback

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

To leave a comment for the author, please follow the link and comment on their blog: R – NYC Data Science Academy Blog.

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