Gamified e-learning systems aim to enhance learning outcomes and foster learner's engagement by incorporating multiple game elements. These elements have varying influence on the learner's behavior, such as encouraging focus, competition, or exploratory attitudes. However, game elements are often implemented within the learning process in a uniform way that is not adaptable, with no available metadata about them, and without the teacher's involvement or choice. However, since game elements have a behavioral effect on the learners, the selection of relevant game elements should include the teachers' objectives for effective gamification. Therefore, this paper proposes an approach to facilitate understanding and formalizing gamification concepts for enhanced understanding from the teacher's side so that they can apply it and share it. The proposed approach begins with defining gamification and its associated properties and how it can be formalized in a semantic model. This ontological model is then populated through data collection and integration processes, which is then validated by means of SPARQL queries. This approach lays the foundation for future advancements, including the potential to recommend appropriate teachers to assist another in integrating gamification into e-learning processes.

In the contemporary educational context, teachers are confronted with the challenge of efficiently managing and utilizing a plethora of heterogeneous pedagogical resources across multiple digital platforms and sources, while simultaneously fostering collaboration in a dynamic educational collaborative environment. This challenge is further amplified by the increasing reliance on digital tools, which often operate in isolation, thereby limiting effective resource sharing and retrieval. To address these challenges, this paper explores the integration of a context-aware pedagogical resources recommender system for teachers within an educational collaborative environment. The paper begins with an identification of the necessity for an integrated approach that connects multiple information systems in order to support resource management and enhance collaborative practices. These are established as a foundation for integration within MEMORAe, a collaborative system of information systems, which employs ontologies for the organisation of heterogeneous resources from different systems and leverages collaborative knowledge sharing. Our integration approach employs the use of MEMORAe to address three pivotal challenges: the structuring of resources, the utilization of context information and the facilitation of collaboration.

Greenhouse systems are considered a part of sustainable agriculture, whose objective is food security and safety while taking into consideration the conservation of resources such as soil and water. To promote sustainable agriculture through greenhouses, it is important to develop an intelligent system that helps stakeholders in decision-making concerning the construction and management of greenhouses. This system must ensure farming activities and monitoring procedures. This work concentrates on the farming activities such as pest control, disease protection, crop cultivation, treatment, etc, and their representation in the system. Ontology is used as a technology to represent the structured information in terms of concepts and the establishment of semantic relations among them. While many existing ontologies focus on agriculture management, the greenhouse domain lack comprehensive coverage, particularly in the operational farming activities that are necessary to ensure the agriculture sustainability. Therefore, there is a need to develop a greenhouse ontology-based system that address the stakeholders’ inquiries related to greenhouse construction and essential farming activities for greenhouse management. This paper presents a synthesis analysis of the existing ontologies in the domain of agriculture and greenhouses as well as a novel modular ontology that covers the greenhouse farming module.

Gamification in e-learning systems implies integrating game elements in non-gaming context to attain the learner’s engagement through pre-defined engagement objectives. These objectives impact the selection of the to-be-applied game elements, which typically influences the learner’s behavior within the learning process. In turn, this behavior is expected to help the teachers in reaching their learning objectives. Therefore, involving teachers in the gamification process as they are in the learning process can ensure the coherence between the learning and engagement objectives. However, since teachers often lack familiarity with gamification, they are rarely involved with the gamification process. Accordingly, recommender systems can play a vital role in assisting teachers through gamification. Therefore, this paper investigates the existing recommender systems from teacher’s perspective to highlight the advancements proposed for assisting teachers and examines the utilization of game elements within gamified e-learning systems to identify their types and explore their practical applications. Based on our research results, this paper proposes a (1) game elements categorization based on their practical applications and (2) a layered recommendation process flow that incorporates the different game elements categories, to assist the teachers in gamifying the learning process.

International audience

The current recommender systems’ approaches favor item’s recommendation over peer’s recommendation. Such virtual information systems do not allow face-to-face communication for collaborative knowledge exchange between peers. However, the on-going worldwide situation affects the sentimental state and especially for a teacher who struggle to adapt his course’s contents according to current variables. These challenges can be mitigated through personalized peer recommendations for teachers. A more-experienced teacher can provide the required support for a less-experienced one in the form of knowledge sharing. This paper proposes a matching approach to provide peer recommendations for teachers in consonance with their context and sentimental state. The peer recommendation aids the teacher to collaborate with other teachers in the form of experience sharing and knowledge sharing. Furthermore, the paper highlights the similarity measurement criteria for contextual and sentimental matching algorithm in addition to predefined rules. At the end, the paper discusses the effectiveness of the algorithm application with a real-life scenario.

International audience

Most of the time, teachers have to search an enormous amount of unorganized resources in order to find the one that suits their cause. Thus, the process of providing innovative resources to support teachers, is becoming one of the essential keys to guarantee a successful learning process for students. Furthermore, this process of providing resources must consider multiple criteria including teacher's experience, students' level of education, cultural background, teaching style and various learning styles. As a result, we find ourselves in front of a more complex problem which needs standardization of resources' description. This unified description of resources can be achieved through a well-represented ontology that strengthens the knowledge-sharing value between teachers granting resources delivery for the intended teacher. This paper introduces a teacher context ontology (TCO) which can be used to organize the knowledge-sharing between teachers through an educational resources recommender system. The ontology contains multiple concepts; teacher profile, resource, targeted audience, and the context in which the teacher uses this resource. MEMORAe is a platform which provides knowledge organization in a collaborative environment. Therefore, TCO benefits from MEMORAe to organize the knowledge-sharing of experiences and resources between teachers.

Recommender systems in education improve the teacher’s working process by providing relevant resources to aid his course design in addition to learning new teaching methodologies. However, these systems have limited adaptability according to a global evaluation of teacher’s activities. This approach of user profiling is convenient, but not adequate for teacher’s context description. In our approach, it is assumed that the utilization of teacher’s emotions has an inevitable role to accomplish a full contextual description for teacher. Teacher context ontology (TCO) provides a representation for the teacher’s living and working contexts along with the main educational concepts. In this paper, we introduce a conceptual integration approach between Moodflow@doubleYou emotional data as a concept and TCO ontology. Furthermore, we intend to prove the importance of integrating such concept for sufficient teacher’s context description. The impact of utilization emotional data in educational recommender systems is discussed. Finally, this paper represents the conducted experiments’ results which show the advantage of such integration.