Evaluation of “Online and Offline” Integrated Teaching Model of Ideological and Political Courses in Colleges and Universities in the Era of Artificial Intelligence
Author(s) -
Lijun Wang
Publication year - 2022
Publication title -
wireless communications and mobile computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.42
H-Index - 64
eISSN - 1530-8677
pISSN - 1530-8669
DOI - 10.1155/2022/4750324
Subject(s) - curiosity , artificial neural network , computer science , artificial intelligence , ideology , process (computing) , mathematics education , multimedia , politics , mathematics , psychology , social psychology , political science , law , operating system
In recent years, the online mode of teaching and learning has been developing day by day. Educational organisations strive to achieve the goal of providing students with a good education. This curiosity resulted in the development of many tools and techniques. The teachers and students should also be trained to adapt to the new technology-based classes from the traditional model. In this research, an integrated model is designed to implement an artificial neural network (ANN) in the intelligent wireless neural network to provide timely delivery of the courses. The integrated model is the combined online and offline teaching and learning process framework. The system is trained with ANN to increase the teaching and learning performance, and the model is compared from various perspectives with existing models like K -means and hybrid K -means. The comparison is carried on for two student batches, and the results show that the proposed ANN model provides an accuracy of 96% and 98% for batch one and batch two of students, respectively.
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