NOVA AI for Education Analytics Lab

The NOVA AI for Education Analytics Lab (AI-EDU Lab) develops artificial intelligence and data analytics solutions to better understand and improve how people learn. The lab transforms educational data into actionable insights that support teaching innovation, personalized learning, and evidence-based decision-making across educational institutions.

Combining expertise in artificial intelligence, learning analytics, and educational data mining, the AI-EDU Lab analyzes learning behavior, predicts academic performance, identifies at-risk students, and helps design more effective learning environments.

Mission

To transform educational data into actionable knowledge using artificial intelligence and advanced analytics, supporting evidence-based teaching practices, personalized learning, and innovation in education.

Areas

Predictive Analytics & Educational Data Mining
Development of predictive models using machine learning to analyze academic performance, identify at-risk students, predict dropout, and understand academic trajectories and progression patterns.
Learning Behavior Analytics
Analysis of student engagement and behavior in digital learning environments using interaction data, learning logs, clickstream analysis, and network analysis of social learning interactions.
Learning Space Analytics & Optimization
Data-driven analysis of physical and digital learning environments to optimize space usage, support pedagogical innovation, and understand the relationship between learning spaces and educational outcomes.
Adaptive Learning Systems & Personalization
Development of AI-powered systems that personalize learning paths, recommend educational resources, and support adaptive assessment, intelligent tutoring, and learner profiling.
Curriculum Analytics & Assessment
Quantitative analysis of curriculum effectiveness, learning sequences, and competencies, including assessment analytics and A/B testing of pedagogical methodologies.
Ethics, Fairness & Privacy in Educational AI
Research on responsible AI in education, including ethical frameworks, bias detection in AI systems, transparency and explainability, and privacy-preserving educational data management compliant with GDPR.

Skillset

Development of artificial intelligence and machine learning models for educational data analysis.
Learning analytics and educational data mining applied to digital learning platforms.
Integration of analytics solutions with learning management systems and educational technologies.
Educational data architecture and information management to support institutional decision-making.
Application of learning sciences and pedagogical innovation to improve learning experiences.

Projects in Development

HELM.AI – Aligning Higher Vocational Education with Labor Market Demands
This project integrates artificial intelligence, data science, and cybersecurity into higher vocational education programs to better align curricula with current and future labor market needs, particularly in public administration.

Funded by: FCT – Fundação para a Ciência e a Tecnologia
Greenshift – European Master’s Program in High-Performance Computing, Sustainability, and Data Science
Greenshift is a European master’s program that combines high-performance computing, sustainability, and data science to prepare students to address complex challenges in business and industry.

Funded by: European Commission – DIGITAL Skills Program
SUCCESS@NOVA – Strategies to Underpin College Course Engagement and Student Success
SUCCESS@NOVA develops data-driven strategies and tools to increase student engagement and improve academic success across NOVA courses through digital transformation and learning analytics.

Funded by: PRR – Impulso Mais Digital
DIGITAL4Business – Master’s Program in Advanced Digital Skills
DIGITAL4Business provides hands-on training in advanced digital skills designed for application in European companies, helping bridge the digital skills gap and support business innovation.

Funded by: European Commission – DIGITAL Skills Program
STEPS@NOVA – Student Tracking for Enhanced Performance and Success
STEPS@NOVA develops a student tracking system that monitors academic progress, identifies students at risk, and supports targeted interventions to improve academic outcomes.

Funded by: POCH – Programa Operacional Capital Humano
RADAR-AIM – AI Micro-credential Courses
RADAR-AIM develops modular micro-credential courses on artificial intelligence and sustainability, designed for integration into undergraduate, postgraduate, and continuing education programs.

Funded by: Erasmus+ Program
LexA – Artificial Intelligence for Legislative Document Retrieval
LexA develops an AI-powered system for retrieving and analyzing legislative documents using natural language processing and large language models, supporting decision-making in public administration.

Funded by: FCT – Artificial Intelligence, Data Science and Cybersecurity for Public Administration

Team

Roberto Henriques

Scientific Coordination (NOVA IMS)
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Guilherme Victorino

Scientific Coordination (NOVA IMS)
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Mauro Castelli

Scientific Coordination (NOVA IMS)
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Alexandre Marques

Researcher (Greenshift)
Frederico Santos

Researcher (Radar AIM)
Rafael Rippel

Project Manager (Digital4Business, Sucess@NOVA)
Yuriy Perezhohin

Researcher (Digital4Business)

Arif Maharramov

PhD Student
Ricardo Santos

PhD Student
Alexandra Pinto

Scholarship MSc Students (Sucess@NOVA)
Diogo Fernandes

Scholarship MSc Students (Helm.AI)
Jorge Cordeiro

Scholarship MSc Students (Helm.AI)