Delianidi Marina (Phd Candidate)

Thesis title: Predicting Student Performance Using Time-Dependent Machine Learning Methods and Recommending Educational Content

Supervisor: Diamantaras Konstantinos

Advisory Committee Members:

Evangelidis Georgios, Professor University of Macedonia
Sidiropoulos Antonios, Associate Professor IHU

Abstract:

In the field of education and especially in e-learning, through the huge volume of the educational information disseminated on the World Wide Web, the correct recommendation of both a series of courses and educational materials is valuable information for the evolution of students’ educational level. The prediction of students’ knowledge state is the most important information for the successful recommendations of educational content that will contribute to both the improvement and the progress of knowledge state. The aim of the doctoral dissertation is the research of Machine Learning methods for the dynamic assessment of student performance and the development of Recommendation Systems for recommendation educational content to the positive progress of the students’ knowledge state.