Bringing Underused Learning Objects to the Light: A Multi-agent Based Approach

Abstract

The digital learning transformation brings the extension of the traditional libraries to online repositories. Learning object repositories are employed to deliver several functionalities related to the learning object's lifecycle. However, these educational resources usually are not described effectively, lacking, for example, educational metadata and learning goals. Then, metadata incompleteness limits the quality of the services, such as search and recommendation, resulting in educational objects that do not have a proper role in teaching/learning environments. This work proposes to bring an active role to all educational resources, acting on the analysis generated from the usage statistics. To achieve this goal, we created a multi-agent architecture that complements the common repository's functionalities to improve learning and teaching experiences. We intend to use this architecture on a repository focused on ocean literacy learning objects. This paper presents some steps toward this goal by enhancing, when needed, the repository to adapt itself.

New perspective of learning objects in e-learning system

“…(Raj and Renumol, 2022). Additionally, Behr et al attempted to provide a schematization of existing approaches utilising a multi-agent system (Behr et al, 2022). LOs can be associated with content objects (Liu and Yu, 2022) in "Towards intelligent e-learning systems", educational objects (Shemy et al, 2021) in "Exploring the need of using Auto-Produced e-learning Objects (Generator) in Oman Schools", information objects and knowledge objects (Clemente et al, 2022) in "A proposal for an adaptive Recommender System based on competences and ontologies".…”