Authors:
Nader N. Nashed
1
;
2
;
Christine Lahoud
2
and
Marie-Hélène Abel
1
Affiliations:
1
HEUDIASYC, Université de Technologie de Compiègne, Compiègne, France
;
2
Université Française d’ Égypte, Cairo, Egypt
Keyword(s):
Education, Recommender System, Semantic Web, Ontology, Sentimental Impact, COVID-19.
Abstract:
The educational process is greatly impacted by the coronavirus pandemic (COVID-19) and this impact outreaches teachers, learners, and all participants. This pandemic is responsible for multiple modifications to the traditional teaching and learning techniques and technologies which leads to social and cultural changes. Due to the accompanied social changes, teachers are experiencing different degrees of stress, burnout, and work difficulties during learning new technologies and preparing to their courses’ contents. Teacher’s sentimental state can be represented by one’s mood and can present an accurate measurement to a teacher experiencing the mentioned difficulties. Accordingly, this study proposes a possible solution for one of the main participants in the educational process, the teacher, by recommending him educational resources to cope with stress and prevent burnout. The proposed recommender system analyses the teacher’s mood and accordingly recommends educational resources tha
t can enhance the teacher’s sentimental state. Through the investigation of this proposal, we found that the enforcement of the sentimental state impacts the resulting recommendations that are presented to teachers.
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