Abstract

Abstract This paper first introduces the SERVQUAL model and establishes generalized indicators, including four aspects of moral character, integrity quality, work ability and work attitude. Subsequently, an information sampling model was constructed to obtain information on the job competence constraint parameters, which provided the necessary data support for the assessment. On the basis of information fusion and time series analysis, a quantitative recursive assessment of English education job competence was carried out using the gray model to obtain the feature extraction results of the job competence assessment and finally to determine the probability density generalized function of English teaching job competence. The assessment results show that the accuracy of the SERVQUAL model is up to 98%, and the combination weight value of interaction ability is the highest, reaching 0.1266. The correlation coefficient of teaching job competence reaches 0.925, and the overall importance evaluation of teachers’ teaching competence is the highest at 93 points, which highlights the high efficiency and accuracy of the assessment system.

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