Profiling students from their questions in a blended learning environment

Automatic analysis of learners' questions can be used to improve their level and help teachers in addressing them. We investigated questions ( N =6457) asked before the class by 1st year medicine/pharmacy students on an online platform, used by professors to prepare their on-site QA and a cluster (D), made of students with higher grades, high attendance, asking more questions which are less popular. This work demonstrates the validity and the usefulness of our taxonomy, and shows the relevance of this classification to identify different students' profiles.