AI in education: supporting teachers, not replacing them
Well-applied educational technology expands teachers' reach and improves access to learning, without removing the educator from the center of the learning process.
The principle guiding our education evaluation
AI technology applied to teaching should expand a teacher's ability to identify individual difficulties and personalize follow-up, never replace human pedagogical judgment. We evaluate tools through that lens: do they give educators more information and time, or do they attempt to automate decisions that require human context?
That distinction guides everything from selecting adaptive learning platforms to institutional performance analytics systems, always prioritizing solutions that keep the teacher as the final authority on pedagogical decisions.
Applications in educational settings
Adaptive learning
Illustrative scenario: study paths that adjust to a student's pace, with reports supporting the teacher's lesson planning.
Accessibility and language
Illustrative scenario: translation and text-to-speech resources supporting students with specific needs.
Institutional analytics
Illustrative scenario: dashboards tracking dropout and performance indicators to support pedagogical and administrative management.
Administrative support
Illustrative scenario: automation of repetitive enrollment and document-issuing tasks, freeing up school staff time.
Protecting student data
Data belonging to children and adolescents receives reinforced treatment under LGPD, requiring proper consent, restricted purpose and heightened care with any third parties involved in processing. Any technology evaluated for a school environment goes through this check before any recommendation, including verification of where and for how long data is retained.
Teacher training as part of the project
No tool generates value if pedagogical staff do not know how to interpret it and incorporate it into classroom routine. That is why we treat teacher training as a mandatory step in any education project, not an optional item to be resolved after deployment.
Initial training
Practical training before the tool is used in class, focused on data interpretation rather than just technical operation.
Ongoing support
Recurring support during the first months of use to adapt the tool to each institution's pedagogical reality.
Team autonomy
Progressive knowledge transfer so the institution can operate the solution without permanent external dependence.
Frequently asked questions
Assess technology for your institution
Tell us about your institution's profile so we can identify the technology categories best suited to your pedagogical context.