Education faces significant challenges worldwide, particularly in underserved regions. Limited access to quality education, insufficient resources, and a shortage of qualified teachers hinder students' learning and future opportunities.
Traditional teaching methods may not suit individual learning needs, leading to disengagement and lower academic outcomes.
Additionally, AI's potential in education is limited due to the lack of localized and unbiased training data, affecting students from diverse linguistic and cultural backgrounds. Addressing these issues is crucial to create an equitable and inclusive learning environment, empowering all students to succeed in today's rapidly changing world.
The overall objective of this school is to highlight the benefits of using AI in education in order to enhance the quality of the learning experience and teaching material in different languages.
At the end of this school, the participants will be able to :
Explain the major innovative approaches around AI for a better education;
Implement at least one use case on AI usage for :
- Learning experience personalization (including students with special needs),
- Learning outcomesprediction,
- Administrative workflows,
- Resource planning,
- Curriculum design.
Use AI-based approaches for spreading teaching materials to the largest in local languages seamlessly.
Educators and Lecturers
Masters, PhD students
Young AI researchers
Representatives of the Ministries of Education
Implement an AI model for notes taking and learning outcome predictions based on silent AI listeners and course materials.
Tutorials on LLM models and applications in education
Conversational agents for teaching
Intelligent tutoringsystems (ITS)
Dialogue-based tutoring systems (DBTS)
AI-driven Personalization for students learning paths
Ethical considerations in AI-driven education