BROAD-RS: agent based architecture for educational context-aware recommendation

Educational resources have great potential to increase the design and composition of online classes. Educational recommendation system aims to identify student’s profile and context to suggest suitable resources to his/her preferences and enrich, flexibilize and dynamize class contents. This work presents XXXXXXX (XXXXX Recommendation System) architecture. It is capable of performing context-aware recommendation of Learning Objects, based on ontologies for modeling student profile and context in an e-learning environment. It was implemented in a multiagent system. The evaluation was performed in a real Software Engineering class, for students of higher education in Computing area. The main steps were: the teacher made the class plan and registered the Learning Objects, the student used the application in different contexts and the recommendation Learning Objects was executed at two different moments. Considering the case study the results pointed to the feasibility of the architecture.Educational resources have great potential to increase the design and composition of online classes. Educational recommendation system aims to identify student’s pro!le and context to suggest suitable resources to his/her preferences and enrich, "exibilize and dynamize class contents. #is work presents BROAD-RS (BROAD Recommendation System) architecture. It is capable of recommendation of Learning Objects, based on ontologies for modeling student pro!le and context in an e-learning environment. It was implemented in a multiagent system and the evaluation was performed in a real Software Engineering class, for students of higher education in Computing area. #e main steps were: the teacher made the class plan and registered the Learning Objects, the student used the application in di$erent contexts and the recommendation Learning Objects was executed at di$erent moments. Considering the case study the results pointed to the feasibility of the architecture