Test scores, attendance rates, and online platform login frequency.
Student feedback (text), classroom video analysis (feature extraction).
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. Test scores, attendance rates, and online platform login
Abstract
To design an automated evaluation model that predicts teaching effectiveness and identifies areas for improvement. 2. Literature Review Evolution of Teaching Quality Assurance (TQA) in China. Application of Big Data and AI in educational technology. This paper proposes a modern evaluation framework that
Subjectivity and lag-time in traditional evaluation methods.
The digitalization of higher education and the increasing need for standardized yet flexible foreign language assessment. the system provides a more scientific
For handling non-linear relationships in student feedback.
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Test scores, attendance rates, and online platform login frequency.
Student feedback (text), classroom video analysis (feature extraction).
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.
Abstract
To design an automated evaluation model that predicts teaching effectiveness and identifies areas for improvement. 2. Literature Review Evolution of Teaching Quality Assurance (TQA) in China. Application of Big Data and AI in educational technology.
Subjectivity and lag-time in traditional evaluation methods.
The digitalization of higher education and the increasing need for standardized yet flexible foreign language assessment.
For handling non-linear relationships in student feedback.
