adaptive learning; recommender systems; social media; 21st century literacies; computer-based assessment
Résumé :
[en] The growing amount of available learning material nowadays requires a significant filtering effort by students for problem solving tasks. In addition, the choice of the appropriate type of learning material differs depending on the individual learner’s preferences. In this work, we suggest to move from a material-centered to a student- and task-centered approach by integrating and suggesting learning material based on the user’s literacy and the context of the task to be completed. Data from social networking platforms may both enrich the available learning material and give insights on the user’s preferences, to adequately match material and learner in the given context. Finally, computer-based assessment may give insights on the learner’s progress and the proposed study material.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
GREVISSE, Christian ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Adaptive Literacy-Aware Integration of Learning Material
Date de publication/diffusion :
2016
Nom de la manifestation :
24th Conference on User Modeling, Adaptation and Personalization
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