Reference : BacAnalytics: A Tool to Support Secondary School Examination in France
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/42639
BacAnalytics: A Tool to Support Secondary School Examination in France
English
Roussanaly, Azim mailto [University of Lorraine - LORIA]
Aleksandrova, Marharyta [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Boyer, Anne [University of Lorraine - LORIA]
May-2020
25th International Symposium on Intelligent Systems (ISMIS 2020)
Yes
International
25th International Symposium on Intelligent Systems (ISMIS 2020)
from 20.05.2020 to 22.05.2020
[en] academic analytics ; secondary school examination ; classification
[en] Students who failed the final examination in the secondary school in France (known as baccalauréat or baccalaureate) can improve their scores by passing a remedial test. This test consists of two oral examinations in two subjects of the student's choice. Students announce their choice on the day of the remedial test. Additionally, the secondary education system in France is quite complex. There exist several types of baccalaureate consisting of various streams. Depending upon the stream students belong to, they have different subjects allowed to be taken during the remedial test and different coefficients associated with each of them. In this context, it becomes difficult to estimate the number of professors of each subject required for the examination. Thereby, the general practice of remedial test organization is to mobilize a large number of professors. In this paper, we present BacAnalytics - a tool that was developed to assist the rectorate of secondary schools with the organization of remedial tests for the baccalaureate. Given profiles of students and their choices of subjects for previous years, this tool builds a predictive model and estimates the number of required professors for the current year. In the paper, we present the architecture of the tool, analyze its performance, and describe its usage by the rectorate of the Academy of Nancy-Metz in Grand Est region of France in the years 2018 and 2019. BacAnalytics achieves almost 100% of prediction accuracy with approximately 25% of redundancy and was awarded a French national prize Impulsions 2018.
Researchers ; Professionals
http://hdl.handle.net/10993/42639

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