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Benefits and Limitations of the Artificial with Respect to the Traditional Learning of Mathematics

1
Department of Applied Mathematics, Graduate Technological Educational Institute of Western Greece, 22334 Patras, Greece
2
Department of Computer Science, Faculty of Computer and Information Sciences, Ain Shams University, Abbasia, 11566 Cairo, Egypt
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Author to whom correspondence should be addressed.
Mathematics 2020, 8(4), 611; https://doi.org/10.3390/math8040611
Received: 7 March 2020 / Revised: 6 April 2020 / Accepted: 13 April 2020 / Published: 16 April 2020
The present article focuses on the role that the artificial teaching and learning of mathematics could play for education in the forthcoming era of a new industrial revolution that will be characterized by the development of an advanced Internet of things and energy, and by the cyber-physical systems controlled through it. Starting with a brief review of the traditional learning theories and methods of teaching mathematics, the article continues by studying the use of computers and of applications of artificial intelligence (AI) in mathematics education. The advantages and disadvantages of artificial with respect to traditional learning in the classroom are also discussed, and the article closes with the general conclusions and a few comments on the perspectives of future research on the subject. View Full-Text
Keywords: industrial revolutions (IR’s); internet of things and energy (IoT & E); learning theories; APOS/ACE instructional treatment of mathematics; flipped learning (FL); problem-solving (PS); computational thinking (CT); artificial intelligence (AI); e-learning; machine learning (ML); smart learning system (SLS); ontological engineering; case-based reasoning (CBR); social robots industrial revolutions (IR’s); internet of things and energy (IoT & E); learning theories; APOS/ACE instructional treatment of mathematics; flipped learning (FL); problem-solving (PS); computational thinking (CT); artificial intelligence (AI); e-learning; machine learning (ML); smart learning system (SLS); ontological engineering; case-based reasoning (CBR); social robots
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Voskoglou, M.G.; Salem, A.-B.M. Benefits and Limitations of the Artificial with Respect to the Traditional Learning of Mathematics. Mathematics 2020, 8, 611.

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