In recent months, school service centers have seen the emergence of two new products from Société GRICS, linked to the Mozaïk-Data data management platform. Based on artificial intelligence, these are intended to facilitate decision-making within school organizations, especially to more quickly identify students at risk of failing or dropping out of school.
Roberto Bacos Junior, owner of Business Intelligence and Artificial Intelligence products from GRICS’s Mozaïk-Data suite, took advantage of the Digital Education Conference to present two platforms: Mozaïk-dVision and Mozaïk-dStudio. Initially, these were intended for the management of CSS and educational institutions in the Francophone and Anglophone youth sectors.
According to Mr Bacos, deployment is ongoing in all CSS in Quebec and the majority already have access to it.
The development of these new products has been made possible thanks to the GRICS data space, which combines structural (or unorganized) data from a variety of sources in the school environment. So these are basically tools for improving and visualizing this data in the form of dashboards, which make it possible to predict specific situations.
“School staff get a portrait of their clients more quickly at the beginning of the school year. The information transmitted does not replace their judgment, but it can guide them and in some cases allow them to intervene more quickly. They represent an additional resource among those available, “explained Mr Bacos.
dVision makes it possible to view processed data from the GRICS database and analyze it to guide decisions. dStudio is a self-service workplace where CSSs can manage their data. The latter is therefore primarily intended for CSS IT departments.
The first written information of the 4th year of primary school
Initially, the development of platforms focused on predicting the success or failure of 4th year elementary school students in writing. It will be able to identify students who are at risk of failing the compulsory ministerial writing test. Similarly, early identification of students at risk of failing to acquire writing skills will provide them with adequate support and reduce delays for the rest of their school careers, Bacos said.
New dashboards can be created at the beginning of the school year (based on previous year’s results), at the end of the first phase in November and at the end of the second phase in March. Data, such as gender, age, mother tongue, number of absences, previous results are used. Each variable can be isolated and the effects are then analyzed.
To date, the accuracy rate has been between 87% and 90%, and has identified “silent failures.”
The morality of artificial intelligence
Clearly, the task is not done without a constant concern to limit the potential biases associated with the development of tools based on artificial intelligence. Nesrin Jemirley, an expert in the field who is supporting GRICS in this project, has come to testify to the ethical governance structure that is being created. The purpose is not to discriminate from the interpretation of information.
3 principles that govern work:
- Everyone must have the same opportunity to be well predicted by algorithms.
- The algorithm will certainly not perform less for a division.
- A trend detected by algorithms should not be scandalous.
The development of governance structures is strongly inspired by the Montreal Declaration for Responsible AI.
To read, or to read again:
Dossier: Artificial intelligence in education