Evaluation of English Teaching Quality in Higher Vocational Colleges Based on Artificial Intelligence Optimization Network

College English is the public foundation of vocational schools and colleges and an important course to cultivate students’ English oral communication ability. The study reforms the higher vocational English course under EGP+ESP, and on the basis of designing the index system of the reform effect of the English course, the game theory method is utilized to combine the BWM subjective empowerment method and the improved CRITIC method to calculate the comprehensive weights of the indexes. Taking higher vocational institution A as an example, the cloud model theory of data analysis is introduced into the evaluation. Then, the evaluation grade of the reform effect is calculated. The regression analysis model is used to further explore the degree of influence of factors on the reform effect of the higher vocational English course, and to explore the relevant teaching suggestions. The reform effect of the English curriculum in higher vocational college A is between “medium-high effect” and “high effect”, closer to “medium-high effect”, and the index scores are between (78, 94) and (80). The index scores are between (78 and 94). And the effect of reforming higher vocational English course (Z) = 0.155*course objective + 0.253*course content + 0.441*course implementation. College English teaching should be used to improve students’ English application and oral expression abilities and to strengthen students’ competitiveness in employment from the perspective of language communication.

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The Construction of Higher Vocational English Classroom Teaching Quality Assessment System under the Background of Intelligent Educational Technology

Tan

2024

Applied Mathematics and Nonlinear Sciences

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This paper introduces the application and development of intelligent education technology. The algorithm of adaptive mutation, which is based on the traditional genetic algorithm, is proposed, and various mutation probabilities are employed during the calculation process at the right time. The genetic algorithm of adaptive mutation is used to optimize the initial weights and thresholds of the BP neural network. Then, the data-based entropy value method is introduced. The a priori guidance samples are obtained through the entropy value method. Then the adaptive mutation genetic algorithm is used to optimize the BP neural network model to learn the knowledge of the a priori samples. The teaching quality evaluation model based on the combination of the three algorithms is established, which completes the improvement of the existing English teaching quality evaluation system for a certain higher-level job. The English classroom teaching quality assessment system in this paper resembles the expert assessment scores. The implementation also prompted teachers to participate in learning seminars to learn advanced teaching concepts. It shows that the assessment results of the teaching quality assessment system proposed in this paper are reliable and can motivate teachers to work towards the goal of improving teaching quality.

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Evaluation of English Teaching Quality in Higher Vocational Colleges Based on Artificial Intelligence Optimization Network

Cited by 3 publications

References 9 publications

An Evaluation Model of Higher Vocational English Teaching Effect Based on Particle Swarm Optimization and Support Vector Machine

An Evaluation Model of Higher Vocational English Teaching Effect Based on Particle Swarm Optimization and Support Vector Machine

A Study on Evaluating the Effectiveness of Higher Vocational English Curriculum Reform and Teaching Suggestions Based on Data Analysis

The Construction of Higher Vocational English Classroom Teaching Quality Assessment System under the Background of Intelligent Educational Technology

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