Résumé:
E-learning is becoming one of the most effective training approaches
nowadays. Thanks to the E-Learning platforms and their collaboration tools,
students can interact with each other and share their doubts on certain
subjects through online reviews and forums.
Nowadays E-Learning platforms endow for students to review
courses. However, teachers often remain outside this process and are
sometimes, not aware about the learning problems encountered in their
classes. The solution could be adopting a sentiment analysis methodology to
students reviews in order to detect the mood and also the issues during the
learning process. That will guarantee problem solving and the confidentiality
of communications between students. Thus, affecting beneficially the
students experience as a whole in E-Learning platforms
In this thesis we demonstrated the attempt of using sentiment analysis
on E-Learning reviews to detect E-Learning students problems. In particular
we focused on proposing a feedback method guaranteeing the confidentiality
of communication and helping to improve of the E-Learning experience.
Keywords: E-Learning, Sentiment Analysis, Opinion mining, Machine
Learning, Data Processing, Data Filtration.
