Abstract
Intelligent Tutoring Systems (ITS) are Systems designed to help students to learn. The main objective of research in this area is to emulate a human Tutor that can help in different ways. The different adaptive components of the ITS are implemented by algorithms of Machine Learning and Artificial Intelligence. In this seminar we will focus on the algorithms and approaches used to choose the different representations and modalities of hints and feedbacks.
The questions to answer for a correct hint and feedback scheduling are: When? What? and How? The help should be provided at the correct time (“when”), then one should consider “what” additional information the student should receive. Finally, it has to be decided “how” the hint should be presented.
Hints and feedbacks management could help effectively in several occasions. It has been demonstrated, that the affective state of a student can be enhanced through support and that when, what and how questions are crucial to do it in the correct way. Moreover, they are also effective against the students that try to ‘game’ the system, and it has been shown how in multiple step exercises’ hints can induce a correct problem-solving attitude.
Instructor: Carlotta Schatten