Data-Driven Intelligent Agents for Personalized Training on Design & Computational Thinking Skills

Computational thinking, i.e., the ability to formalize and solve problems with the assistance of computers, has become crucial in a growing range of jobs. Recent research in education has provided encouraging evidence that the development of computational thinking is the most effective when it is taught in the early childhood, and that game-based learning (GBL) technologies are extremely valuable in this context. However, children often need help when learning with GBL software. The goal of this project is to explore how to provide such help automatically and in a personalized way, which is important as personalization is a key aspect to facilitate human learning, as is it has been demonstrated by the effectiveness of one-to-one human tutoring.

Faculty Supervisor:

Cristina Conati

Student:

Sébastien Lallé

Partner:

UME Academy

Discipline:

Computer science

Sector:

Education

University:

University of British Columbia