A Review Study on the Enhancement of Oral Fluency in L2: An Investigation into Processes and Didactics

This paper principally endeavors to grant a thorough understanding of the cognitive and expressive mechanisms perpetually involved in the production of speech. It must be noted that oral fluency has proven to be one of the major skills that almost all EFL learners strive to achieve through conscious mental efforts and constant exposure. Oral fluency is then a cognitive process that requires the learner to use their meta-cognitive skills to both enhance the effectiveness and flow of speech, and simultaneously avoid speech errors

Illiteracy Effects on Local Development in the Moroccan Rural World: Challenges and Recommendations

This paper fundamentally aspires to make context-based recommendations to the increasingly rising number of Moroccan female cooperatives in rural areas, particularly in the region of Fes-Meknes. Similarly, it endeavors to problematize illiteracy and its effects on local and regional development among rural women in the aforementioned region. It must be noted that solidarity cooperatives unquestionably help mitigate both feminine poverty and unemployment, and simultaneously incrementally establish an ongoing entrepreneurial platform for rural women. Such a platform can directly grant the potentiality of helping these women make quantum leaps in development, as well as become socio-culturally emancipated from the stereotypes and clichés that have kept them invisible for decades in the so-called domestic sphere. The data gathered by means of focus groups’ sessions in different Fes-Meknes areas and villages, Ifrane, Azrou, Imouzzer, Sefrou and Ain Louh, was of paramount importance in making recommendations that are realistically inspired and meticulously drawn from research informants whose participation in local and regional development, albeit challenges, has drawn a significant amount of attention from state actors, such as the Office of Development and Cooperation (ODCO) and associations of civil society, such as the Moroccan Center for Innovation and Social Entrepreneurship (MCISE). One can confidently state that human development can solely be born out of solidarity, collaboration and encouragement in order to ultimately defy social ills and create seamless cohesion and prosperity

ICT-Based Instruction amid COVID-19: The Case Study of Faculty of Sciences and Technologies, Tangier (FSTT)

This paper contextually endeavors to grant insights and perceptions on the teaching of English for Specific purposes (ESP) through ICT-based instruction amid COVID-19 at the Faculty of Sciences and Technologies in Tangier (FSTT). To avoid total curriculum disruption, the FSTT urgently declares online learning, which has palpably manifested a plethora of pitfalls primarily pertinent to logistics according to the study results. Drawing on previously published materials, the use of quantitative research analysis allows the researcher to empirically unravel different challenges and educational gaps among the research population. The findings of the survey indicate that more investment should be made at the level of research in order to enable ICT- based instruction to be more regulated, yet most importantly properly managed. By so doing, students’ motivation and interaction tremendously augment as they become more genuinely and actively engaged in the teaching/learning process

The Significance of English Scientific Writing Proficiency for Publishing Purposes: The Case of Moroccan EFL PhD Students at the Euromed University of Fes

This study aspires to theoretically and empirically investigate the dearth of English scientific writing in the engineering PhD programs at the Euromed University of Fes. It must be noted that the entire absence of English in the curriculum of PhD programs unequivocally creates myriad challenges, mainly in the writing process. Doctoral students find themselves impotent to publish in indexed journals, be it a single-blind peer review or a double-blind peer review, due to the high demands of scientific writing proficiency and accuracy alongside the scrupulous treatment of data. In like manner, novice researchers lack expertise and oftentimes agonize about the writing task as their meta-cognitive skills need to be rejuvenated, revitalized, and rigorously fortified. To that end, the use of numerical data by means of questionnaire is highly estimated by researchers to vigorously help in unveiling the aforementioned challenges, while simultaneously systematically paving the way for context-specific recommendations to be made in order to alleviate some of the pressure that doctoral students undergo with respect to English scientific writing for the purpose of producing quality publishable materials

The Role of ICT in the Teaching of Productive Skills in English during COVID-19: Teachers’ Perceptions and Obstacles

In the current millennium, educational technology integration has become an obligation, particularly when the focus of teaching is purely fluency-based. EFL teachers believe that students cannot reach a good level of fluency unless they speak and write English with less difficulty and more spontaneity. For that purpose, instructors incessantly seek versatile ways and approaches to deepen and enrich the teaching of four language skills (mainly the productive ones). Online sources and internet outlets provide both students and instructors with various ranges of software applications and platforms to actively dive into different class activities. Through the agency of online applications and programs, EFL learners get to gradually embrace autonomous learning. In effect, students reach self-improvement in speaking and writing when they are continuously exposed to ICT assistance. Therefore, this paper aspires to pinpoint the aspects of productive skills of teaching via the implementation of ICT as a new trend in modern education. Needless to say, it ignites a deeper discussion on Moroccan teachers’ attitudes toward the use of ICT in the EFL classroom. The quantitative analysis by means of a questionnaire designated to Moroccan EFL teachers revealed a considerable amount of positivity and predilection toward the employment of ICTs in the EFL instruction

Identidad o patriotismo ¿cuál es la imagen de las mujeres en la caricatura argelina?

Este estudio intenta analizar la visión que se desprende sobre la mujer en las caricaturas argelinas, no sólo como tema de debate académico y mediático, sino también en la construcción de identidades. La propia ideología que subyace en esta visión, a veces inocente, extiende su sombra sobre muchos temas importantes en el país, en términos de derechos básicos del ciudadano y otros problemas sociales y económicos. La caricatura se ha constituido históricamente como una herramienta al servicio de una explotación interesada, bien de denuncia o bien de complicidad. En este artículo tratamos de abordar la idea de pertenencia y nacionalismo estudiando algunas caricaturas de dibujantes argelinos de diferentes períodos.This study tries to analyze the vision that emerges about women in Algerian cartoons, not only as a topic of academic and media debate, but also in the construction of identities. The ideology itself that underlies this vision, sometimes innocent, extends its shadow over many important issues in the country, in terms of citizen’s basic rights and other social and economic problems. The cartoon has historically been constituted as a tool at the service of an interested exploitation, either of denunciation or of complicity. In this article we try to address the idea of belonging and nationalism by studying some cartoons of Algerian cartoonists from different periods

NOUVELLES PRATIQUES ORGANISATIONNELLES POUR L’ACCOMPAGNEMENT ENTREPRENEURIAL : LE CAS DU COWORKING

Le Coworking représente une forme émergente d'organisation du travail, où des startups ou des travailleurs indépendants partagent des espaces de travail en mettant l'accent sur les notions de partage, de communauté, de productivité et d’innovation. Le phénomène a pris de l’ampleur après la crise économique de 2008. Il a permis de créer une forme hybride entre un travail standard dans un lieu de travail traditionnel, en l’occurrence une entreprise, et une vie professionnelle indépendante et automne assurée en isolement à partir du domicile. Le Coworking est devenu ainsi un symbole de l’économie du partage. L’entrepreneuriat a trouvé, de ce fait, un nouveau support adapté au développement d’activités entrepreneuriales dans un environnement partagé. Les espaces de Coworking rassemblent en effet plusieurs intervenants de l’écosystème entrepreneurial, notamment des fournisseurs, des utilisateurs potentiels, des financeurs de startups, etc. Le nombre de ce type d’espaces reste relativement faible eu égard aux opportunités qu’ils offrent en matière de création de richesse et d’emplois pour le pays. Le présent travail s’appuie sur l’étude de cas d’un espace de Coworking au sein de la ville de Rabat qui peut ouvrir des voies de recherche scientifique et d’action des pouvoirs publics et surtout de l’université marocaine pour soutenir l’entrepreneuria

Résolution des problèmes d'optimisation combinatoire avec une stratégie de retour-arrière basée sur l'apprentissage par renforcement

Les problèmes d’optimisation combinatoire (Constraint Optimization Problems – COP) sont souvent difficiles à résoudre et le choix de la stratégie de recherche a une influence importante sur la performance du solveur. Pour de résoudre un problème d’optimisation combinatoire en explorant un arbre de recherche, il faut choisir une heuristique de choix de variable (qui définit l’ordre dans lequel les variables vont être instanciées), une heuristique de choix de valeur (qui spécifie l’ordre dans lequel les valeurs seront essayées), et une stratégie de retour-arrière (qui détermine vers quel noeud effectuer les retours-arrière lorsqu’une feuille de l’arbre est rencontrée). Pour les stratégies de retour-arrière, il y a celles dont les retours-arrière sont totalement déterministes (e.g. Depth-First Search – DFS) et d’autres qui s’appuient sur des mécanismes d’évaluation de noeuds plus dynamiques (e.g. Best-First Search). Certaines (e.g. Limited Discrepancy Search – LDS) peuvent être implémentées soit comme un algorithme itératif déterministe ou un évaluateur de noeud. Une stratégie est dite adaptative quand elle s’adapte dynamiquement à la structure du problème et identifie les zones de l’espace de recherche qui contiennent les “bonnes” solutions. Dans ce contexte, des stratégies de branchement adaptatives ont été proposées (e.g. Impact-Based Search – IBS) ainsi qu’une stratégie de retour-arrière adaptative (e.g. Adaptive Discrepancy Search – ADS), proposée pour les problèmes d’optimisation distribués. À notre connaissance, aucune stratégie adaptative qui utilise l’apprentissage par renforcement (Reinforcement Learning – RL) pour supporter son mécanisme d’apprentissage n’a été proposée dans la littérature. Nous pensons que les techniques de RL permettront un apprentissage plus efficace et qu’une stratégie de retour-arrière munie de ces techniques aura le potentiel de résoudre les problèmes d’optimisation combinatoire plus rapidement. Dans ce mémoire, nous proposons un algorithme (RLBS) qui “apprend” à faire des retours-arrière de manière efficace lors de l’exploration d’arbres non-binaires. Plus précisément, il s’agit une stratégie de retour-arrière qui se base sur l’apprentissage automatique pour améliorer la performance du solveur. En fait, nous utilisons l’apprentissage par renforcement pour identifier les zones de l’espace de recherche qui contiennent les bonnes solutions. Cette approche a été développée pour les problèmes d’optimisation combinatoire dont l’espace de recherche est encodé dans un arbre non-binaire. Comme les arbres sont non-binaires, on a l’occasion d’effectuer plusieurs retours-arrière vers chaque noeud durant l’exploration. Ceci permet d’apprendre quels noeuds mènent vers les meilleures récompenses en général (c’est-à-dire, vers les feuilles les plus intéressantes). Le branchement est effectué en utilisant une stratégie de choix de variable/valeur quelconque. Toutefois, quand un retour-arrière est nécessaire, la sélection du noeud cible s’appuie sur l’apprentissage par renforcement. RLBS est évalué sur cinq instances industrielles du problème de la planification des opérations du rabotage du bois et a été comparé à ADS et à LDS sur cette même application. RLBS dépasse LDS et ADS, en termes de temps de calcul nécessaire à la résolution, sur chacune de ces instances-là et trouve la solution optimale plus rapidement. Les expérimentations ont montré que RLBS est en moyenne 4 fois plus rapide que ADS, et 6 fois plus rapide que LDS. RLBS a aussi été évalué sur une instance jouet du même problème et a été comparé à IBS. RLBS surpasse largement IBS. Il est capable de trouver une solution optimale en explorant beaucoup moins de noeuds que le nombre nécessaire à IBS pour trouver une telle solution.Combinatorial optimization problems are often very difficult to solve and the choice of a search strategy has a tremendous influence over the solver’s performance. To solve a problem using search, one needs to choose a variable selection strategy (defining the order in which variables will be instantiated), a value selection strategy (that specifies the sequence in which we will try the variable possible values) and a backtracking strategy (that determines to which node we should backtrack/backjump, when a leaf is reached or a dead-end is encountered). When it comes to backtracking strategies, there are some that are encoded into full deterministic algorithms (e.g. Depth-First Search – DFS), and others that rely on more dynamic node evaluator mechanisms (e.g. Best-First Search). Others (e.g. Limited Discrepancy Search – LDS) can be implemented as a deterministic iterative algorithm or as a node evaluator. A strategy is said to be adaptive when it dynamically adapts to the structure of the problem and identifies the areas of the search space that contain good solutions. Some have proposed adaptive branching strategies (e.g. Impact-based Search – IBS) or a backtracking strategy (e.g. Adaptive Discrepancy Search – ADS) proposed for distributed optimization problems. To our current knowledge, no adaptive backtracking strategy that relies on Reinforcement Learning (RL) has been proposed yet. We believe that RL techniques could allow a more efficient learning process and that, provided with these techniques, a backtracking strategy has a great potential of solving combinatorial optimization problems in a faster way. In this thesis, we introduce an algorithm (RLBS) that learns to efficiently backtrack when searching non-binary trees. We consider a machine learning approach which improves the performance of the solver. More specifically, we use reinforcement learning to identify the areas of the search space that contain good solutions. The approach was developed for optimization problems for which the search space is encoded as a non-binary tree. Since the trees are non-binary, we have the opportunity to backtrack multiple times to each node during the search. This allows learning which nodes generally lead to the best rewards (that is, to the most interesting leaves). Branching can be carried on using any variable/value selection strategy. However, when backtracking is needed, the selection of the target node involves reinforcement learning. RLBS is evaluated on five instances of the lumber planing problem using real idustrial data, and it is compared to LDS and ADS. It outperforms classic (non-adaptive) search strategies (DFS, LDS), an adaptive branching strategy (IBS), and an adaptive backtracking strategy (ADS) on every instance of this problem. Experiments have shown that RLBS is on average 4 times faster than ADS, and 6 times faster than LDS. RLBS is also evaluated on a toy instance of the lumber planing problem and compared to IBS. RLBS substantially outperforms IBS by solving the problem to optimality much faster