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International Journal of Multimedia Computing, 2021, 2(3); doi: 10.38007/IJMC.2021.020305.

Artificial Intelligence and Multimedia Technology in the Construction of Performance Courses

Author(s)

Ming Zhang

Corresponding Author:
Ming Zhang
Affiliation(s)

School of Economics and Management, Nanjing Agriculture University, Nanjing, Jiangsu 210095, China


Abstract

As computers and information technology evolve, multimedia technology has been perfect as a carrier for transmitting teaching information, multimedia presentation and related application technology. The fusion of media and various digital information has become an irresistible trend to promote the application and development of multimedia teaching demonstration in skill learning. Due to the diverse forms of performance classes, the traditional teaching methods can no longer satisfy the current teaching methods of the new curriculum standards. In this paper, artificial intelligence and multimedia technology (AI&MT) are introduced into the construction of performance courses at the same time, and the classroom becomes lively and interesting by using multimedia technology to improve teaching methods. At the same time, based on artificial intelligence, SAIES system, naive leaf Bays algorithm, random forest and other algorithms are used to evaluate students' academic performance and interest in learning, aiming to construct a reasonable curriculum construction and change the problems existing in traditional teaching methods. Experiments showed that by applying AI&MT to performance courses, students' interest in learning has improved, the completion rate of learning progress has increased by 7.9%, and the work efficiency of teachers has increased by 6.03% compared with the previous ones.

Keywords

Artificial Intelligence, Multimedia Technology, Performance Course, Naive Bayesian Algorithm

Cite This Paper

Ming Zhang. Artificial Intelligence and Multimedia Technology in the Construction of Performance Courses. International Journal of Multimedia Computing (2021), Vol. 2, Issue 3: 36-52. https://doi.org/10.38007/IJMC.2021.020305.

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