English Teaching Evaluation Algorithm and Modeling based on Machine Learning and Data Mining Technology

Traditional English teaching evaluation has problems such as subjectivity, limitations, quantitative bias, and lacks feedback and support. The evaluation algorithm based on data analysis technology provides an accurate, comprehensive, and personalized evaluation method for teachers and students, which can understand their learning needs and ability levels by collecting and analyzing students' learning data. This study adopts a method based on data analysis technology to develop English teaching evaluation algorithms. Firstly, this paper collected students' learning data, including information on language expression, learning behavior, and academic performance. Then, machine learning and data mining techniques are used to analyze and model these data to predict students' English proficiency level and learning needs. The research results indicate that the F1 value range of the algorithm in this paper is 0.85-0.94, and the English teaching evaluation algorithm based on data analysis technology has achieved significant results in evaluating students' English proficiency.