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Identifying key indicators such as "Interaction Frequency," "Vocabulary Growth Rate," and "Student Engagement Levels." Algorithm Selection:

For handling non-linear relationships in student feedback. " "Vocabulary Growth Rate

Future work: Integrating real-time facial expression recognition for classroom engagement monitoring. the system provides a more scientific

Traditional foreign language teaching evaluation relies heavily on subjective student surveys and manual peer reviews, which often lack real-time accuracy and objectivity. This paper proposes a modern evaluation framework that utilizes machine learning (ML) to analyze multi-dimensional data—including classroom interaction, student performance, and sentiment analysis. By applying algorithms such as Random Forest and Support Vector Machines (SVM), the system provides a more scientific, data-driven approach to improving pedagogical outcomes in higher education. " "Vocabulary Growth Rate

showing how a dean or professor would see the "Teaching Quality Score."