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Doya K, Friston K, Sugiyama M, Tenenbaum J. Neural Networks special issue on Artificial Intelligence and Brain Science. Neural Netw 2022; 155:328-329. [PMID: 36099665 DOI: 10.1016/j.neunet.2022.08.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Kenji Doya
- Okinawa Institute of Science and Technology Graduate University, Japan.
| | | | | | - Josh Tenenbaum
- Massachusetts Institute of Technology, United States of America
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Digital Media Teaching and Effectiveness Evaluation Integrating Big Data and Artificial Intelligence. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:1217846. [PMID: 36188689 PMCID: PMC9522489 DOI: 10.1155/2022/1217846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 08/26/2022] [Accepted: 09/06/2022] [Indexed: 11/17/2022]
Abstract
With the development of digital media technology, its application in teaching and learning is becoming more widespread. Digital media technology helps present information in transmitting knowledge or skills, reduces cognitive load, and promotes understanding of knowledge. Evaluation of the effectiveness of digital media teaching has also become important. A scientific and reasonable evaluation of digital media teaching effectiveness can help teachers select digital media technology and grasp the amount, degree, and timing of digital media use to change teaching effectiveness. This paper proposed using a combination of big data and artificial intelligence methods to evaluate the effectiveness of digital media teaching methods using the RBF neural network model. The digital media teaching effectiveness evaluation was used as the input variable of RBF, the degree of digital media effectiveness was the output variable and the neural network was trained through the collected sample data. The research results showed that the RBF neural network model proposed in this paper has a strong generalization and extension ability in evaluating digital media teaching effectiveness, providing a new way to evaluate digital media teaching effectiveness.
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