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Despite the importance of physics practical work in higher education, its implementation is often hampered by various constraints and problems. Technology, such as learning management systems (LMS) and mobile learning, can offer solutions to some of these problems and enrich students' learning experiences. Therefore, this research proposes a model called Practical Works in Physics via Mobile Learning and LMS (PWP-MLMS) that exploits features of LMSs and mobile devices to overcome specific challenges encountered in physics practical works and improve students' performance in these works. The model was designed, validated, and evaluated within the teaching context of a Moroccan university. To assess the model's effectiveness, 128 students in the Bachelor of Education, Physics-Chemistry specialization were randomly divided into two groups of 64 students each: an experimental group using the model for practical work on the topic of rectification and filtering in the electronics module, and a control group following the conventional method for the same practical work. The results of the evaluation showed that the proposed model can significantly reduce the time required to complete the practical work, have a positive influence on the students' technical skills, and improve the quality of their laboratory reports.

Osteopetrosis, also known as the disease of marbled bones, refers to a group of constitutional bone diseases resulting from a defect in bone metabolism. This condition is characterized by its manifestation, most often at a young age, and is typically revealed by its complications, primarily fractures. Diagnosis is currently confirmed through genetics but also relies on imaging such as standard radiography and computed tomography. We report the case of a child, aged 13 years, presenting with osteopetrosis revealed by atypical symptoms, confirmed by computed tomography imaging mainly in our country in Morocco where access to care is sometimes difficult for some patients.

This paper reports on the experimentation of a collaborative learning approach in university training for a Master's degree in "Pedagogical and Multimedia Engineering". It is carried out with learner-teachers training in Instructional Design. The approach adopted focuses on the complexity of the collaborative situation, and is based on three andragogical models: shared cognition, self-directed learning and transformative learning. The aim of this study is twofold. On the one hand, to assess the relevance of a totally collaborative approach that fully integrates students into their learning. On the other hand, to design a collaborative model in the form of a grid that can be used to assess the collaborative potential of a learning situation. The indicators evoked by the collaborative groups in relation to each component of the model they developed reflect their level of appropriation of the model, and the impact of the approach on the development of skills for analyzing and designing learning situations.

Hydrocephalus is defined as an anomaly in the flow of cerebrospinal fluid, with multiple and varied etiologies, both acquired and congenital. The most dominant etiology in the congenital aspect is the stenosis or atresia of the Sylvian Aqueduct, whether isolated or associated with other malformations. We report a case of congenital hydrocephalus due to a stenosis of the Aqueduct of Sylvius in a 2 and a half-year-old child, which was unrecognized in the neonatal period, and the importance of imaging, especially MRI, in the rapid diagnosis of this pathology.

Current developments relating to integrating information and communication technologies (ICT) in learning lead us to wonder about the positive impact that pedagogical video can have on e-learning devices mediating between teacher and learner. Determining the concepts of mediatization and mediation constitutes one of the essential bases of any pedagogical engineering of mediated videos to ensure better transmission of knowledge. To articulate the two concepts of mediation and mediatization, designers, teachers, and trainers must not only mediate the contents of the video but also the pedagogical relation, the design and production process, without forgetting the scenarization phase of the pedagogical videos, which occupy an important place in the pedagogical engineering. In our article, after giving an overview of the two concepts, mediation, and mediatization, we define the pedagogical video, the use of the pedagogical video, and the forms of the pedagogical video. Then, we identify the mediatization tools of pedagogical videos and their mediatization articulation according to previous studies.

Multilingual sentiment analysis (MSA) involves the task of comprehending people’s opinions, sentiments, and emotions in multilingual written texts. This task has garnered considerable attention due to its importance in extracting insights for decision-making across diverse fields such as marketing, finance, and politics. Several studies have explored MSA using deep learning methods. Nonetheless, a majority of these studies depend on sequential-based approaches, which focus on capturing short-distance semantics within adjacent word sequences, but they overlook long-distance semantics, which can provide more profound insights for analysis. In this work, we propose an approach for multilingual sentiment analysis, namely MSA-GCN, leveraging a graph convolutional network to effectively capture both short- and long-distance semantics. MSA-GCN involves the comprehensive modeling of the multilingual sentiment analysis corpus through a unified heterogeneous text graph. Subsequently, a slightly deep graph convolutional network is employed to acquire predictive representations for all nodes by encouraging the transfer learning across languages. Extensive experiments are carried out on various language combinations using different benchmark datasets to assess the efficiency of the proposed approach. These datasets include Multilingual Amazon Reviews Corpus (MARC), Internet Movie Database (IMDB), Allociné, and Muchocine. The achieved results reveal that MSA-GCN significantly outperformed all baseline models in almost all datasets with a p-value < 0.05 based on student t-test. In addition, such approach shows prominent results in a variety of language combinations, revealing the robustness of the approach against language variation.

Natural disasters cause immense damage and disruption to the environment, human lives, and property, posing a threat to safety and well-being. These disasters annually affect individuals and communities, severely impacting mental health. Research indicates a significant link between catastrophic events and an increased risk of mental disorders, including anxiety, depression, substance use, and post-traumatic stress disorder (PTSD). Individuals with chronic conditions, like cancer patients, are particularly vulnerable post-disaster due to disrupted healthcare services. The recent earthquake in Morocco highlighted the urgent need for continued care, especially for vulnerable populations living in poverty. Soleterre Foundation’s interventions focus on supporting young cancer patients and their families, emphasizing psychological support following the earthquake. Effective disaster response needs coordinated efforts, clear roles, communication, and standardized healthcare procedures, especially for vulnerable groups like cancer patients. Education programs for patients and clinicians are vital for disaster preparedness. Communication challenges and lack of medical history further emphasize the need for well-defined disaster preparedness plans and continued care guidelines for cancer patients.