With the generalization of Artificial Intelligence, the field of education is changing fundamentally. AI contributes to the appearance of new ways to teach and learn, which can make the educational experience more efficient and engaging. For example, it is a way to solve the « one size fits all » problem faced by traditional teaching.

Artificial Intelligence is thus becoming a hot topic in education.  Keywords as customisation, dashboards, intelligent tutors, learning analytics, quality improvement, student motivation, engagement, etc. are now buzz words in the domain.

However, introducing AI in education cannot come down to designing and using AI tools. Dimensions such as pedagogy, social and educational sciences, psychology also have to be considered. AI in education is therefore a multidisciplinary domain.

As part of the “AI and Education: Modeling real-world problems” autumn school, we aim to understand, foster and support the development of AI in education, by considering several disciplines, topics and points of view, from theoretical to practical problems.

To this end, the school provides basic concepts, state-of-the-art and new insights in several domains, such as educational data mining, statistical learning, knowledge management, user (teacher/learner) experience, co-design, personalised stakeholders support, acceptance, adoption, evaluation, etc., considering obviously the links between them.

The summer school will proceed in three successive phases:

• From 17^th October to 21^st October, researchers in the field of education and AI will give lectures covering a broad range of the previously mentioned topics. Interaction between instructors and participants will highly be encouraged during these lectures.
• 22^nd October and 23^rd October, participants will attend the LSAC conference, dedicated to – talks by researchers, practitioners and industrials of practical experiments as well as theoretical proposals, - discussions about privacy, ethics and policies.
• 24^th October and 25^th October participants will take part in a two-days datathon to apply the notions presented in the preceding week. Multidisciplinary teams will compete on an innovative real-world problem with real data.

The ‘AI and Education: Modeling real-world problems’ summer school will be held as a co-located event of the LSAC conference from Thursday the 17^th  of October  to Friday the 25^th of October, in Nancy, France.

Target Audience

Any practitioner, Ph.D. student, post-doc, researcher, or Master student, interested in AI or in education is invited to attend the school, whatever is his/her main area of knowledge (education, psychology, computer science, etc.). As it is a multidisciplinary school, no specific background is required to attend it, an interest in all disciplines will be appreciated.

Originality of the Summer School

• The school involves three phases, from theoretic (first phase) to practical (datathon), through discussions and presentations of practical experiences by researchers and teachers. It will be rich and dynamic.
• The school is multidisciplinary, the main discipline of the participants will range from computer science to psychology and includes education, statistics, etc. This diversity of topics and the variety of participants will make this school full of fruitful discussions and works.

Social events

Four social events the autumn school will take place during the autumn school.

• On Thursday the 17^th: an opening cocktail that will be the opportunity for the attendees to start knowing each other.
• On Sunday the 20^th: a visit to Nancy City. You will discover our nice city, UNESCO classified for its 18^th century Place Stanislas.
• On Tuesday, the 22^nd: a gala dinner with attendees of the LSAC conference.
• On Wednesday the 23^rd: a dinner with all the participants of the datathon. New attendees will join us, you will meet each of them, and start discussions with your teammates and other teams. 

How to Pre-register and register, registration fees

Participation at the autumn school requires pre-registration via: http://enquetes.univ-lorraine.fr/index.php/883718?lang=en.

The autumn school has a limited number of places, so the allocation of places will be on a first-come, first-served basis.

Pre-registration will remain open until the capacity limit is reached.

Reserving an accommodation lies in the responsibility of participants, recommended dormitories and hotels are on the website.

Registration fees

Registration fees include coffee breaks (twice each day) and lunch for each day (except Sunday 20^th), and the four social events.

Registration closes on 1^st October.

Students (PhD Thesis and Master): 350 €

Academic (Post Doc, Researchers): 400 €

Private attendee: 600 € 

Reduced fees for Université de Lorraine students.