![]() ; Aleksandrova, Marharyta ![]() in 25th International Symposium on Intelligent Systems (ISMIS 2020) (2020, May) 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 ... [more ▼] 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. [less ▲] Detailed reference viewed: 125 (2 UL)![]() ![]() Aleksandrova, Marharyta ![]() in Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2017 9th IEEE International Conference on (2017) Detailed reference viewed: 148 (6 UL)![]() ![]() Aleksandrova, Marharyta ![]() in ECAI (2016) Detailed reference viewed: 60 (1 UL)![]() ![]() Aleksandrova, Marharyta ![]() in Tools with Artificial Intelligence (ICTAI), 2016 IEEE 28th International Conference on (2016) Detailed reference viewed: 130 (3 UL)![]() ![]() Aleksandrova, Marharyta ![]() in Journal of Intelligent Information Systems (2016) Detailed reference viewed: 191 (15 UL)![]() ![]() Aleksandrova, Marharyta ![]() in 2nd European Workshop on Chance Discovery and Data Synthesis (EWCDDS16) (2016) Detailed reference viewed: 66 (1 UL)![]() ![]() Aleksandrova, Marharyta ![]() in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2014), PhD Session Proceedings (2014) Detailed reference viewed: 71 (0 UL)![]() ![]() ; Aleksandrova, Marharyta ![]() in Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)-Volume 02 (2014) Detailed reference viewed: 134 (0 UL) |
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