Application and Cultivation on Mathematical Thinking in Artificial Intelligence

Shen, Jie; Wu, Qinglin

doi:10.1109/irce53649.2021.9570967

Cited by 1 publication

(1 citation statement)

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“…In Deo et al [ 18 ], the research calls for developing learning and teaching interventions and class medical checks to address concerns linked to graduation results and students ‘ learning qualities in university education. In Shen and Wu [ 19 ], the author followed with an explanation of the mathematical thinking cultivation approach. Lastly, the everyday use of mathematical thinking in artificial intelligence is thoroughly explained.…”

Section: Related Workmentioning

confidence: 99%

Effectiveness of Artificial Intelligence (AI) in Improving Pupils’ Deep Learning in Primary School Mathematics Teaching in Fujian Province

Ya-ping

Pan

Ishak

2022

Computational Intelligence and Neuroscience

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Several primary school students in Fujian Province have perceived studying mathematics as challenging. To deal with this issue, computer technology advancements, specifically artificial intelligence (AI), present an opportunity to evaluate individual students’ learning challenges and give individualized support to optimize their success in mathematics classes. It is also possible to use virtual reality (VR) to assist learners in acquiring complex mathematical and logical ideas and to lessen learners’ mistakes. As a result, researchers, particularly beginners, are missing out on a complete perspective of the study of AI in teaching mathematics. That is why we are exploring the role of AI in math education by developing a “fuzzy-based tweakable convolution neural network with a long short-term memory (FT-CNN-LSTM-AM)” method. For this investigation, the students’ datasets are taken and educated by mathematical teaching via the application of AI. The proposed method is utilized to predict the students’ performance in mathematical education. A grey wolf optimizer is employed to boost the effectiveness of the proposed method. Furthermore, the performance of the proposed method is analyzed and compared with existing approaches to gain the highest reliability.

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Section: Related Workmentioning

confidence: 99%