Authors:
Christos Troussas
;
Akrivi Krouska
and
Cleo Sgouropoulou
Affiliation:
Department of Informatics and Computer Engineering, University of West Attica, Egaleo, Greece
Keyword(s):
Assistive Messages, Computer Knowledge Level, COVID-19, e-Learning, Feedback, Fuzzy Logic, Human-Computer Interaction, Personalized System, Recommender System, Rule-based System.
Abstract:
The fast growth of the internet and communication technology in recent years has resulted in rendering computers easily accessible to everyone. However, people have different knowledge and characteristics that can affect their ability to use computers and at the same time create barriers to achieve an effective user experience. The reason for this is to provide dynamic adaptability to users' individual needs. In view of this compelling need, this paper presents a user-centric system that seeks mainly to improve the interaction of users with the software they use. To achieve this, the system employs fuzzy logic to model the computer knowledge of users and based on this classification, it delivers assistive messages, which are pertinent to the interaction with the system. These messages are tailored to the user groups that have been created, as well as the degree of detail which is more adequate for each group. As a testbed for our research, the presented approach has been incorporated
in a learning management system to support tutors towards having a better experience while interacting with this software. The system has been evaluated by users during the COVID-19 lockdown with promising results.
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