La cognification dans l'enseignement, l'apprentissage et la formation

Auteurs-es

DOI :

https://doi.org/10.21432/cjlt28261

Mots-clés :

Cognification , IA dans l'éducation , quatrième révolution industrielle , technologie éducative

Résumé

Au cours de la dernière décennie, les possibilités d'apprentissage en ligne ont augmenté de façon remarquable. Les apprenants du monde entier ont maintenant un accès numérique à un large éventail de formations d'entreprise, de certifications, de programmes universitaires complets et d'autres options d'éducation et de formation. Certaines organisations combinent les méthodes d'enseignement traditionnelles avec les technologies en ligne. L'apprentissage hybride génère d'importants volumes de données concernant à la fois le contenu (qualité et utilisation) et les apprenants (habitudes d'étude et résultats d'apprentissage). En conséquence, la nécessité de traiter correctement des données volumineuses, continues et souvent divergentes a entraîné l'avènement de la cognification. Les techniques de cognification conçoivent des modèles d'analyse de données complexes qui permettent à l'intelligence naturelle de mobiliser l'intelligence artificielle de manière à améliorer l'expérience d'apprentissage. La cognification est l'approche qui consiste à rendre quelque chose de plus en plus intelligent, de manière éthique et régulée. Cet article souligne comment les tendances émergentes en matière de cognification pourraient bouleverser l'enseignement en ligne.

Bibliographies de l'auteur-e

Vivekanandan Kumar, Athabasca University, Canada

Vivekanandan Kumar is Professor and Associate Dean of Research and Innovation in the Faculty of Science and Technology at Athabasca University in Canada. His research interests include artificial intelligence in education, cognification, fourth industrial revolution, and learning analytics.

Mohamed Ally, Athabasca University, Canada

Mohamed Ally is Professor in the Faculty of Humanities and Social Sciences at Athabasca University in Canada. His current areas of research include mobile learning and use of emerging learning technologies in education and training.

Avgoustos Tsinakos, International Hellenic University, Greece

Avgoustos Tsinakos is Professor in the Department of Computer Science of International Hellenic University in Greece. His research interests include mobile learning, technology-enhanced learning, intelligent tutoring systems and internet applications of AI.

Helmi Norman, Universiti Kebangsaan Malaysia

Helmi Norman is Associate Professor of the Faculty of Education, Universiti Kebangsaan Malaysia (UKM) or the National University of Malaysia. He is also the Deputy Director of Instructional Technologies of the Center for Teaching and Curriculum Development, UKM. He currently drives the e-learning transformation in the university. His research interests are in the field of digital and futuristic education.

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Publié-e

2022-11-29

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