Full Professor. Universidade Federal de Alagoas, Brazil.

Professor Ig Ibert Bittencourt is a Computer Scientist and Psychologist whose career in Artificial Intelligence in Education (AIED) is driven by a clear purpose: using computation and AI models to connect rigorous research, educational innovation, and public policy so every student, especially in underserved communities, has a real chance to learn.

He brings together a technocentric understanding of how AI systems work with a deeply humanistic concern for student well-being, equity, and social justice, asking not only what learners can achieve, but how they feel, who gets left out, and how to prioritize people over infrastructure.
These perspectives led him to create two subfields of research within AIED:
Positive Artificial Intelligence in Education (P-AIED); and AIED Unplugged, which rethink how AI can support both learning and thriving in schools and communities around the world, even where devices and internet are scarce.

Description of his work

Dr. Bittencourt serves as a Principal Investigator and coordinator of multiple large-scale research initiatives, including the National Institute of Science and Technology in Artificial Intelligence in Education (INCT IA.Edu).
His work focuses on designing, implementing, and evaluating AI-based educational innovations that are ethical, equitable, and centered on the real needs of learners and teachers, particularly in underserved communities across the Global South.

He leads public policy–oriented projects on AI in education across Latin America and works closely with Brazil’s Ministry of Education on digital transformation, educational data analytics, and educational innovation, helping decision-makers use evidence.

At the same time, he collaborates with interdisciplinary teams to explore how learning, technology use, and well-being intersect in educational contexts.

“Across all these efforts, my central objective is to translate research findings into scalable solutions that can positively impact educational systems and learners.”

Key findings

By analyzing roughly three decades of digital transformation policies in education, Dr. Bittencourt and his collaborators have shown that, at the current rate of progress, it could take close to a century for low-income countries to reach levels of educational technology equity similar to those of high-income nations.

This finding challenges the belief that simply adding devices and connectivity will eventually close the gap, and it motivated the proposal of the AIED Unplugged framework, which promotes low-cost, context-sensitive, and pedagogically grounded approaches to AI in education that can work even where infrastructure is limited—prioritizing people, pedagogy, and proxies over top-down tech investments.

A second major line of his work confronts a global tension in learning: Our studies indicate the existence of a widespread mental health crisis, which calls for interventions that explicitly target both learning and well-being. Through the Positive Artificial Intelligence in Education (P-AIED) framework, his team designs AI-supported learning experiences that intentionally nurture cognitive development alongside psychological health and socio-emotional well-being, showing, in diverse settings, that it is possible to create interventions that advance both learning and well-being rather than forcing a choice between them.