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Nowadays with COVID-19 ongoing epidemic outbreak, containment for weeks was one of the most effective measures adopted to deal with the spread of the virus until a vaccine could be efficient. Over that period, increased anxiety, depression, suicide attempts and post-traumatic stress disorder are accumulated. Several studies referred to the need of using chatbots, which recognizes human emotions in such pandemic contexts. More recently, numerous research papers improved the ability of artificial intelligence methods to recognize human emotion. However, they are still limited. The aim of this paper is the development of a chatbot against the disturbing psychic consequences of the pandemic, taking human emotion recognition into account. The object is to help people; especially students; suffering from mental disorders, by progressively understanding the reasonsbehind them. This innovative chatbot was developed by using the natural language processing model of deep learning. An advanced model of deep learning has been elaborated the intention for people and that to help them to regulate their mood and to reduce distortion of negative thoughts, that why a collection of a new database was done. The sequence-to-sequence model encoder and decoder consist of Long short-term memory cells and it is defined with the bi-directional dynamic recurrent neural network packets.

<p>The face-to-face mode is always considered as the normal mode of teaching, and distance education is often understood as a remedy for the lack of material and human resources necessary to conduct training; but to prevent the spread of the coronavirus (COVID19), the distance course system has been launched in different countries to ensure continuity of teaching during the period when courses are stopped. In order to shed light on the role of distance learning during the spread of the coronavirus and its effectiveness in successfully continuing the learning process, an investigation was carried out in the Moroccan context. This survey was launched as a questionnaire with 565 participants; they are students and teachers from primary, secondary, university and professional training. The objective is to answer several research questions concerning the current use of distance education during the COVID19 pandemic. The results of this survey are presented in this article as well as their analysis showing that solutions and alternatives must be adopted in order to improve the teaching and learning process in the event of a situation like COVID19.</p>

The health crisis and the unprecedented upheaval in the education systems which it caused are far from being over, consequently, the adaptation of the learning experience is most needed, and it should take into consideration the criteria of this specific crisis and its impact on the physical and mental health of the learners. In this article, we aimed to present an ontologybased learner model that will bring together the pedagogical and psychological characteristics, but also the health risks generated by the epidemic on the learners, following a Knowledge-Engineering Methodology. We developed an ontology that combines the IMS-LIP standard features and the learner characteristic. It is ready for different uses in different systems and situations during and after the COVID-19 pandemic, and it will give a global representation of the learner in order to allow him to get the best-adapted courses.