AI in the Service of Education: Building a New Education Ecosystem Based On the International Approaches

Proceedings of ‏The 3rd International Conference on Academic Research in Science, Technology and Engineering

Year: 2020

DOI:

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AI in the Service of Education: Building a New Education Ecosystem Based On the International Approaches

BENABID Bilal,Iklafen Sanae, El Ouadi Abdelmajid

 

ABSTRACT: 

In the era of big data, robotics and automation, learning approaches diversity is becoming increasingly important and the education system must evolve and take into account the new emerging needs. The field of education represents major and even crucial challenges in the development of societies. Today, there is a strong need to review the education system and the teaching techniques at the global level and rethink it in the light of technological and scientific progress that the world is experiencing in order to remedy existing problems and imperfections with today’s solutions. Human knowledge, computerized, represented by artificial intelligence, can indeed help to solve problems related to education and to make it evolve by taking advantage of the different opportunities in the sector. Many learning methodologies could be improved thanks to artificial intelligence tools and algorithmic concept. Among these technologies are NLP, computer vision, and other smart tools, both collaborative and interactive.On the basis of a comparative study -taking France’s local system as a case study- on the different practices carried out by world pioneers to make the AI in the service of education, this work answers to the following questions:

– What are the main imperfections in the centuries-old classical education system?

– What impacts could AI have on this system to improve its profitability? Which methods are used by the AI leaders countries?

– What are the main efforts made to improve the French educational system through AI tools applied to learning and teaching methodologies?

Keywords::Artificial intelligence, Teaching, Personalized learning, Machine learning, Concept mapping.