Workshop on Artificial Intelligence for Engineering Education (AI4ENGED)

Scope

In the current era of digital transformation, engineering education faces significant challenges driven by rapid technological advances, evolving industrial demands, and a growing need for flexible, scalable, and personalized learning models. Universities and educators must respond to these challenges while ensuring educational quality, academic integrity, and meaningful learning outcomes.

Artificial intelligence (AI) has emerged as a key technology for supporting teaching and learning processes in engineering education. From intelligent tutoring systems and learning analytics to automated assessment and generative AI tools, AI-based approaches are increasingly being integrated into educational environments. However, beyond technological adoption, there is a critical need to rigorously analyze the methodological aspects, educational impact, and empirical evidence supporting these solutions.

This special session aims to provide a forum for researchers and practitioners from academia and industry to present and discuss innovative AI-based methods, tools, and systems applied to engineering education.

Topics

This session offers an opportunity to present and discuss recent theoretical advances, methodologies and practical experiences related to Artificial Intelligence in Engineering Education, including (but not limited to) the following topics:

Artificial intelligence for assessment and feedback in engineering education.
Intelligent tutoring systems for STEM and engineering subjects.
Learning analytics and predictive models in engineering programs.
Artificial intelligence to support project-based learning and laboratory activities.
Generative artificial intelligence in engineering teaching and learning environments.
Personalized and adaptive learning systems for engineering curricula.
Ethical and trustworthy artificial intelligence in education.
Methodological frameworks for evaluating AI-based educational solutions.
Decision-making based on data in engineering education.
Human–AI collaboration in teaching and learning processes.