Accelerated Move for AI Education in China

Yang, Xiaozhe

doi:10.1177/2096531119878590

Cited by 54 publications

(22 citation statements)

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“…There are signs that some countries are responding to developments in artificial intelligence with curriculum initiatives. China has stated its intention of becoming a world leader in artificial intelligence by 2030 and is introducing artificial intelligence into curricula in primary and secondary schools (Jing 2018;Yang 2019). In its articulation of a new national curriculum, China identified the need to respond to the fact that artificial intelligence is replacing humans in many areas and this affects the kind of competences that humans should develop (Wang 2019).…”

Section: Learning About Machine Learningmentioning

confidence: 99%

“…In its articulation of a new national curriculum, China identified the need to respond to the fact that artificial intelligence is replacing humans in many areas and this affects the kind of competences that humans should develop (Wang 2019). China's approach to its curriculum for artificial intelligence is within an "environment of reflection on the relationship between artificial intelligence and human intelligence, the collaboration between man and machine, and shared development of the future" (Yang 2019). Within this environment, instead of focusing on computers and the Internet, the curriculum for artificial intelligence focuses on data, algorithms, information systems and the information society (ibid.).…”

Section: Learning About Machine Learningmentioning

confidence: 99%

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Machine learning for human learners: opportunities, issues, tensions and threats

Webb

Fluck

Magenheim

et al. 2020

Education Tech Research Dev

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Machine learning systems are infiltrating our lives and are beginning to become important in our education systems. This article, developed from a synthesis and analysis of previous research, examines the implications of recent developments in machine learning for human learners and learning. In this article we first compare deep learning in computers and humans to examine their similarities and differences. Deep learning is identified as a sub-set of machine learning, which is itself a component of artificial intelligence. Deep learning often depends on backwards propagation in weighted neural networks, so is non-deterministic—the system adapts and changes through practical experience or training. This adaptive behaviour predicates the need for explainability and accountability in such systems. Accountability is the reverse of explainability. Explainability flows through the system from inputs to output (decision) whereas accountability flows backwards, from a decision to the person taking responsibility for it. Both explainability and accountability should be incorporated in machine learning system design from the outset to meet social, ethical and legislative requirements. For students to be able to understand the nature of the systems that may be supporting their own learning as well as to act as responsible citizens in contemplating the ethical issues that machine learning raises, they need to understand key aspects of machine learning systems and have opportunities to adapt and create such systems. Therefore, some changes are needed to school curricula. The article concludes with recommendations about machine learning for teachers, students, policymakers, developers and researchers.

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Section: Learning About Machine Learningmentioning

confidence: 99%

Section: Learning About Machine Learningmentioning

confidence: 99%

Machine learning for human learners: opportunities, issues, tensions and threats

Webb

Fluck

Magenheim

et al. 2020

Education Tech Research Dev

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“…A grand experiment has started recently in China that could change the way that people learn (Yang, 2019). Squirrel is one of the first China's companies to pursue the concept of an AI tutor.…”

Section: Resultsmentioning

confidence: 99%

Machine learning techniques for teaching mathematics

Voskoglou¹,

Salem²

2020

FMO

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Formulation of the problem. Famous social thinkers of our times are speaking about a forthcoming 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. There is no doubt that our students should take full advantage of the potential that the new digital technologies can bring for improving their learning skills. Materials and methods. This treatise has a review character. The methods of analysis used are based on already reported researches. Results. The article focuses on the role that the artificial teaching and learning of mathematics could play for education in the forthcoming era of the new industrial revolution 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 in mathematics education. Conclusions. The advantages and disadvantages of artificial with respect to traditional learning are discussed as well as the perspectives for future research on the subject.

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“…A grand experiment has started recently in China that could change the way that people learn [40]. Squirrel is one of the first China's companies to pursue the concept of an AI tutor.…”

Section: Artificial Intelligence In Mathematics Teachingmentioning

confidence: 99%

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

Voskoglou

Salem

2020

Mathematics

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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.

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Accelerated Move for AI Education in China

Cited by 54 publications

References 1 publication

Machine learning for human learners: opportunities, issues, tensions and threats

Machine learning for human learners: opportunities, issues, tensions and threats

Machine learning techniques for teaching mathematics

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

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