EduTrack AI
An AI API for academic performance prediction in gamified environments, complementing the EduTrack platform, with academic support from CEDIS.
Project Description
EduTrack AI is an artificial intelligence API for academic performance prediction in gamified environments, complementing the EduTrack platform. The product was developed by Daniel Rodrigues da Rocha, Davi Rodrigues da Rocha, and Mylena Angélica Silva Farias, with the involvement of Prof. Sergio Freitas , as part of their undergraduate research (scientific initiation) at CEDIS.
The API consumes the diagnostic indicators collected by EduTrack — prior knowledge, autonomy, expectations, curiosity, and motivation — to generate academic performance predictions that support pedagogical decisions on personalization and gamification.
Project Objectives
The main objectives of the project are:
- to provide academic performance prediction based on motivational and profile indicators collected at the start of the semester;
- to integrate artificial intelligence and machine learning techniques with the educational gamification practiced in EduTrack;
- to anticipate academic risk signals before they show up as low grades, delays, or reduced participation; and
- to serve as an experimental basis for teaching, research, and outreach initiatives supported by CEDIS in artificial intelligence, learning analytics, and gamification.
Resources and Features
EduTrack AI exposes an API that receives the diagnostic indicators collected by EduTrack and returns academic performance predictions, allowing the platform to proactively flag classes or students who may benefit from more targeted pedagogical interventions or gamification strategies.
Academic Link
- Daniel Rodrigues da Rocha (product development as part of undergraduate research)
- Davi Rodrigues da Rocha (product development as part of undergraduate research)
- Mylena Angélica Silva Farias (product development as part of undergraduate research)
- Prof. Sergio Freitas (academic supervision)
Related Scientific Output
The diagnostic instrument underpinning EduTrack AI was described in a paper accepted at the XXXVII Brazilian Symposium on Computers in Education (SBIE 2026), authored by Prof. Sergio Freitas , Daniel Rodrigues da Rocha, Davi Rodrigues da Rocha, and Mylena Angélica Silva Farias.
Access
The API is available at ai.edutrack.cedis.tec.br.