Titre : Internet of Things for human learning 

Auteurs : Aymeric Bouchereau, Ioan Roxin,  

Revue : Internet of Things 

Numéro : Issue 1 

Volume : 2 

Date : 2018/02/26 

DOI : 10.21494/ISTE.OP.2018.0217 

ISSN : 2514-8273 

Résumé : The Internet of Things encompasses a multitude of connected devices with advanced functions for the
automation of tasks and assistance to individuals, raising technical, political, social and economic challenges. Learning is
linked to these challenges in several ways: the machine learning development contributes to the functioning of connected
devices, which in turn stimulate human learning by diversifying practices and tools. Learning methods can lean on recent
works in neuroscience that identify cognitive resources for learning, such as attention, engagement, feedback and
consolidation. In addition, learning has been modified by technological change: after printing, computing and
telecommunications, the Internet of Things is a new information medium for knowledge transmission. Based on three
dimensions (data, interfaces and pervasiveness), we propose a classification of possible articulations of the Internet of
Things to support learning. The study of this relationship shows that the Internet of Things promotes exploration and
experimentation, the setting up of authentic situations and the contextualization of learning. 

Éditeur : ISTE OpenScience