Personalized assessment of English instructors’ instruction quality is one of the key initiatives to improve the quality of English teaching. This paper proposes an EM-AGA-BP model for English teachers to assess instruction quality. The entropy value method is used for the initial evaluation of English teachers’ teaching quality. The BP neural network is optimized for evaluation learning based on the genetic algorithm of adaptive mutation so as to put forward a more comprehensive and scientific English teachers’ assessment of instruction quality model. At the same time, the English teachers’ instruction quality evaluation index system is constructed. In the empirical analysis, English teachers in colleges and universities are taken as the research object to verify that the assessment of the instruction quality index system by English teachers has better reliability and validity. In the assessment of teaching evaluation quality, English teachers’ evaluation skills are high, with the largest mean value of 4.12, followed by evaluation attitude and evaluation awareness, with mean values of 3.8 and 3.71, respectively, and the overall evaluation score of English teachers’ personalized teaching quality is 3.02, with the evaluation grade level of “medium,” and the evaluation scores of the five evaluation criteria levels are all in the same range. The evaluation scores of the five evaluation criteria layers are all within the score range, and the evaluation level is also “medium.”