Recommending Metadata Contents for Learning Objects Through Linked Data

Behr, André; Mendes, Armando B.; Trigo, Paulo; Cascalho, José; Guerra, Hélia; Costa, Ana C.; Parente, Manuela I.; Botelho, Andrea Z.; Vicari, Rosa María

doi:10.1007/978-3-030-85710-3_10

Cited by 3 publications

References 16 publications

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

Behr

Cascalho

Mendes

et al. 2022

Lecture Notes in Computer Science

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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.

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