Technology, Innovation, and Data Science have the potential to revolutionize the Education sector, bringing innovative solutions that improve the quality of teaching and learning. With the use of technologies like Artificial Intelligence and Machine Learning, it is possible to personalize teaching and adapt it to the individual needs of each student.
We can analyze large volumes of educational data, allowing for a broader view of the challenges faced by the sector.
With this information, it is possible to develop more efficient public policies and identify areas that need more investment.
From the analysis of data obtained from Learning Management Systems (LMS), it is possible to identify tacit knowledge – that which is difficult to be explained, but can be captured, somehow, by technologies.
This knowledge can support the construction and improvement of courses and curricula. This data can also be cross-referenced with the types of tasks proposed and student interaction.
It is possible, for example, to further personalize this learning path, given the identification of knowledge gaps and the presentation of specific content for each student.
Data Science can help evaluate student profiles to identify which teachers are most likely to improve your learning in a certain class, school, or subject.
This brings more possibilities for personal satisfaction and fulfillment for the student.
Using Machine Learning makes it possible to identify (with an accuracy of over 85%) the students most likely to drop out of school, through the cross-referencing of multiple databases (whether from the educational institution itself, education secretariats, or other publicly available ones).
Evasion is a complex phenomenon that, if not combatted, compromises the social and economic goals of society in the medium and long term.
Some institutions and courses offer elective and extracurricular subjects where the number of enrolled students can vary depending on popularity.
With predictive analysis, it is possible to better plan the school curriculum and all the necessary management. so that these subjects are taught with quality, without overcrowded classes, but with the concern of serving everyone who is interested in them.
Furthermore, all private schools have a certain number of delinquent students. In some, this number is so high that it can even lead to the closure of the institution!
This shows how important it is for schools to have a clearer forecast of non-payments. what will happen and plan financially to support them.
Another possibility with predictive analytics is New enrollment scenario forecast.
Because this is an issue that also affects the school's budget, it's important to have a more precise estimate for it.
It is possible to explore patterns and relate various factors to predict trends and present a probable enrollment result for the school for the following year.
Thus, the educational institution can determine the amount of revenue it can count on from enrollments, as well as the need to devise new strategies to improve the scenario, reversing negative results or enhancing positive ones.
