1st International Workshop on Education through Advanced Software Engineering and Artificial Intelligence (EASEAI)
Co-located with ESEC/FSE '19 in Tallinn, Estonia.
On August 26, 2019.
Website: https://easeai.github.io

** DESCRIPTION **

In the past years, with the development and widespread of digital technologies, everyday life has been profoundly transformed. The general public, as well as specialized audiences, have to face an ever-increasing amount of knowledge and learn new abilities. The EASEAI workshop addresses that challenge by looking at software engineering, education, and artificial intelligence research fields to explore how these fields can cross-fertilize and benefit from each other. Specifically, this workshop brings together researchers, teachers, and practitioners who use advanced software engineering tools (such as software development tools and methods, productivity tools, software inspection and analysis tools, automated testing techniques, etc.) and artificial intelligence techniques in the education field as well as researchers and teachers in education science who tackle how to improve awareness regarding digital technologies through a transgenerational and transdisciplinary range of students.

** TOPICS OF INTEREST **

Topics include, but are not limited to:

- New and unexpected usage of established software engineering practices in education environments.
- Integration of agile methods principles in education environments.
- Integration of software quality standards and methods dedicated to continuous improvement in education environments.
- Application to serious game and gamification in the context of education.
- Advances in automated grading of assignments.
- Advances in automated feedback and recommendations to provide support to students.
- Visualization of technical and/or scientific information in various fields (chemistry, software engineering, physics, history, sociology, etc.).
- Efforts related to the improvement of usability of advanced tools for non-experienced users.
- Dropout prediction in learning environments using machine learning.
- Feedback on case studies using cutting edge techniques, methods, and tools applied to educational environments.
- Improvement of computational thinking skills and digital literacy through software engineering.
- Integration of software engineering and artificial intelligence research into teaching and training.
- Introduction to artificial intelligence and machine learning principles for younger audiences.

** TYPES OF SUBMISSIONS **

We invite original papers in the conference format (two columns ACM sigconf publication format) describing positions and new ideas (short papers up to 4 pages) as well as new results and reporting on innovative approaches (long papers up to 8 pages). All accepted papers will be published in the ACM digital library, together with the other ESEC/FSE 2019 workshops proceedings. The review process is single-blind. Each contribution will be reviewed by at least three members of the program committee.

The workshop also welcomes presentations of previously peer-reviewed published papers. We will invite authors to submit a one-page extended abstract that will not be included in the proceedings. As previously published papers have been already reviewed and accepted, they will not be reviewed again for technical content. If needed, the presentations propositions will be prioritized, based on the content and structure of the sessions.

** IMPORTANT DATES **

Submission of full papers: June 7th, 2019
Notification of acceptance: June 24th, 2019
Camera ready: July 1st, 2019
Workshop date: August 26th, 2019
Submission: see https://easeai.github.io/#call

** WORKSHOP CHAIRS **

Benoît Vanderose, PReCISE, University of Namur (Belgium)
Benoît Frénay, PReCISE, University of Namur (Belgium)
Julie Henry, PReCISE, University of Namur (Belgium)
Xavier Devroey, Delft University of Technology (Netherlands)