An Enhanced Evaluation of English Teaching Quality based on Explainable Artificial Intelligence Techniques

Preserving the quality of English instruction remains a foundation for fostering good language learning and pedagogical superiority in contemporary schools. Nonetheless, current assessment systems tend to be plagued with severe shortcomings, including overdependence on personal judgment, delayed written feedback, low scalability, and low responsiveness to changing teaching environments. These traditional methods are not able to provide real-time feedback, comprehensive assessment, or evidence-based assistance for instructors and administrators, resulting in inconsistent evaluation of teaching and diminished academic achievements. To resolve these issues, this research suggests an innovative Deep Neural Network (DNN)-based smart evaluation system that can automatically handle intricate, high-dimensional educational data to generate precise and comprehensible evaluations of instructional performance. The system architecture suggested includes structured data pre-processing, feature extraction of feedback metrics, academic grades, instructor engagement levels, and behavioral interactions, and then a DNN classifier for prediction. In addition, Explainable AI (XAI) modules such as SHAP (Shaply Additive Explanations) are integrated to visualize and interpret the effect of the important features on the final quality scores, facilitating transparent and actionable feedback. Experimental validation was performed on actual educational datasets, and the model revealed notable improvement in predictability, precision, and stability over conventional evaluation models. The suggested system recorded 98.5% accuracy, 98.3% precision, 98.3% recall, and 98.5% F1-score, indicating its high generalizability and applicability in institutions. This intelligent system provides a robust, data-driven solution to transform English teaching assessment and sets the stage for continued optimization through generative and adaptive models of learning.