An Improved Genetic Algorithm and Neural Network‐Based Evaluation Model of Classroom Teaching Quality in Colleges and Universities

Zhang, Huaying; Xiao, Bin; Li, Jinqiong; Hou, M.

doi:10.1155/2021/2602385

Cited by 13 publications

(5 citation statements)

References 27 publications

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“…Although substantial progress has been achieved in the investigation of methodologies for evaluating the quality of domestic classroom instruction, there are still certain issues. Reference [15] analyzed the characteristics of the tendency of the evaluation subject of the teaching quality of college teachers to be relatively single. Specifically, only students are allowed to participate in the 2…”

Section: Related Workmentioning

confidence: 99%

Application of Support Vector Machine Model Based on Machine Learning in Art Teaching

Hua

Yang

2022

Wireless Communications and Mobile Computing

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The purpose of the evaluation is to reflect on whether education provides a good environment and conditions for the development of students and to reflect on the effect of teaching and the practicability of the talents cultivated by teaching to the society. When art education is evaluated, a number of positive outcomes have been achieved in terms of the development of art education, including the improvement of art education as a whole, the development of art talent, and a stronger role for the educational and social communities concerned about the quality of art education. Machine learning-based support vector machine (SVM) can better tackle issues like nonlinearity, high dimensionality, and local minima, which have been effectively implemented in the area of teaching quality evaluation (TQE) with the fast growth of information technology and the Internet. The main work of this paper is as follows: (1) it briefly expounds the research progress of TQE and multiclassification algorithm based on SVM at home and abroad and introduces the relevant basic theories of these two aspects. (2) One-to-one combination method is used in this research, reducing training time to a certain degree. Tests prove the procedure to be objective and equitable. (3) This research claims that an art TQE approach based on SVM is suited for limited professional assessment sample data and provides a method for this purpose.

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Section: Related Workmentioning

confidence: 99%

Application of Support Vector Machine Model Based on Machine Learning in Art Teaching

Hua

Yang

2022

Wireless Communications and Mobile Computing

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“…Scholars have used AHP to evaluate the quality of physical education teaching based on the characteristics of physical education courses. In specific course evaluations, Zhang et al (2021) used the maximum frequency method to obtain the weight vector of major items and the weight matrix of sub-items. Stockinger et al (2021) used AHP to evaluate remote education and the fuzzy comprehensive evaluation method to reduce the impact of uncertain factors.…”

Section: Related Workmentioning

confidence: 99%

Research on Intelligent Improvement Method of Physical Education Teaching Quality in Universities Based on FAHP Model

Liu,

2024

International Journal of Web-Based Learning and Teaching Technologies

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With the development of the information age, the quality of physical education teaching in universities has become an important goal of teaching reform. Improving the quality of physical education and significantly improving students' physical fitness is one of the development goals of higher education. Therefore, this article proposes an intelligent improvement method by collecting and analyzing college sports data and using the FAHP model for qualitative and quantitative analysis. This model can evaluate the current situation of students' physical education and propose targeted strategies. By verifying the consistency of the model output, effective teaching strategies are identified to achieve the goal of continuously improving the quality of physical education in universities. Teachers' classroom teaching efficiency, teaching resources, and teaching methods must also meet higher requirements. The intelligent improvement method based on the FAHP model proposed in this article provides new ideas and methods for improving the quality of physical education teaching in universities.

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“…Excellent teaching output can, on the one hand, reflect the solid teaching foundation function of universities and attract excellent students. On the other hand, it can concentrate resources and attract social and government resources to flow into discipline construction and professional construction, forming a virtuous circle and enhancing the core competitiveness of universities [32]. According to the high-quality teaching resources ensemble of the Ministry of Education, teaching output should be subdivided into six indexes to evaluate high-level university construction in Jiangsu Province; these indexes are the number of provincial and ministerial teaching achievement awards, the number of high-quality courses of the Ministry of Education, the number of provincial and ministerial teaching projects, the number of provincial and ministerial teaching platforms, the number of provincial and ministerial teaching courses, and the number of provincial and ministerial teaching materials.…”

Section: Teaching Outputmentioning

confidence: 99%

A Fuzzy Comprehensive Evaluation Method on the Construction of High-Level Universities Based on Data from Jiangsu Province

Suo-ming

Wan

Chen

2022

Scientific Programming

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To respond to the call for the construction of a “double first-class university” in China and implement the “Focus on innovation, focus on enriching the people, and build a moderately prosperous society at a high level” development strategy. Jiangsu Province issued the first round of the “Jiangsu High-level University Construction Program” in 2016. Taking the deepening of the innovation-driven development strategy as the starting point, the main objective of promoting higher education is to strengthen its ability to support economic and social development. In this study, the fuzzy-ANP comprehensive evaluation model is used to create an index system for building high-level universities with Jiangsu Province features. Using this system, high-level university construction in Jiangsu Province is evaluated. The results of the study show that the first round of Jiangsu’s high-level university construction has reached an excellent level and is the most effective in improving the quality of research. In addition, the participating universities are better able to promote socioeconomic development. However, the resources and social reputation of the participating universities are close to the level of excellence. Furthermore, due to the problem of prioritizing research above teaching, the teaching and internationalization levels of the participating universities are rather low.

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An Improved Genetic Algorithm and Neural Network‐Based Evaluation Model of Classroom Teaching Quality in Colleges and Universities

Cited by 13 publications

References 27 publications

Application of Support Vector Machine Model Based on Machine Learning in Art Teaching

Application of Support Vector Machine Model Based on Machine Learning in Art Teaching

Research on Intelligent Improvement Method of Physical Education Teaching Quality in Universities Based on FAHP Model

A Fuzzy Comprehensive Evaluation Method on the Construction of High-Level Universities Based on Data from Jiangsu Province

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