Proposal Description

The rapid integration of Artificial Intelligence and learning analytics into educational settings is reshaping the ways in which teaching, learning and assessment are designed, delivered and experienced. Intelligent learning environments offer unprecedented opportunities for personalized support, early identification of students at risk, adaptive interventions and data-informed decision-making. At the same time, they raise important questions concerning algorithmic bias, transparency, privacy, equity, reliability and the unintended consequences of increasingly automated educational processes. Understanding these opportunities and vulnerabilities requires robust statistical approaches capable of dealing with uncertainty, complex data structures and evolving patterns of learner behavior.
This invited session seeks to explore the notion of risk and resilience in AI-enhanced educational ecosystems by bringing together contributions that address both methodological developments and practical applications. Topics may include predictive modelling of academic outcomes, early-warning systems based on learning analytics, fairness and accountability in educational AI, statistical approaches to monitoring intelligent tutoring systems, quality assurance in digital learning environments, and the use of evidence to support ethical and effective educational interventions. Particular emphasis will be placed on how statistical reasoning can help institutions anticipate challenges, strengthen resilience and promote student success in increasingly complex learning contexts.
By promoting dialogue among statisticians, learning scientists, educational researchers and technology specialists, the session aims to advance a more critical and balanced understanding of the role of data and AI in education and how to avoid known and emerging associated hazards and risks. It will highlight the contribution of statistical science not only to the development of intelligent educational systems but also to their responsible governance, ensuring that innovation is accomplished by excellency, inclusiveness and a sustained commitment fostering learning opportunities for all.