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Human system learning, who is in control ? - common innovation in e-learning, machine learning and h

Couverture du livre « Human system learning, who is in control ? - common innovation in e-learning, machine learning and h » de Colloque Internation aux éditions Europia
  • Date de parution :
  • Editeur : Europia
  • EAN : 9782909285337
  • Série : (-)
  • Support : Papier
Résumé:

The Information Society is burgeoning and new technology is shifting educational, learning and training paradigms. Virtual Universities, Cyber-Classrooms, e-Learning, Wireless Based Learning, Humanoid Robots, Data Mining, Text Mining, Web Semantic, etc. may be cryptic catch phrases now but will... Voir plus

The Information Society is burgeoning and new technology is shifting educational, learning and training paradigms. Virtual Universities, Cyber-Classrooms, e-Learning, Wireless Based Learning, Humanoid Robots, Data Mining, Text Mining, Web Semantic, etc. may be cryptic catch phrases now but will be within the main learning and teaching norm in a very near future. Mining tools have become the more popular Machine Learning issues. The fifth ICHSL observes that, Machine Learning, Humanoid (mainly Human Robot Interaction) and e-Learning system have proved the necessity of integrating high level interactive approaches. This means most validated information has to be retrieved, extracted and transferred within a Human Computer Collaborative approach in which both Human and Machine learn from each other. In every validated information production process roles between users and computers are continually exchanged. Sometimes decisions are owned and controlled by the machine and at other times by users. In summary, Interactive M.L. Humanoid Robot and e-Learning tools have to adopt a user driven design approach. They should learn from and about their users. Both E-learning systems and Humanoid Robots must embed some machine learning tools. Moreover, an efficient Interactive Machine Learning system (during the information construction or validation) has to consider very powerful pedagogical and sensitive approaches in order to be able to learn from their users. From this perspective we can observe that distances between Interactive Machine Learning, Humanoid Robot and e-Learning have become closer and closer.

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