A fuzzy evaluation of AI-assisted English teaching quality based on random forest regression algorithm

Key Points

• The central aim is to evaluate the quality of AI-assisted English teaching using a fuzzy approach and machine learning techniques.
• Utilized a fuzzy evaluation framework to assess teaching quality.
• Applied a random forest regression algorithm for data analysis.
• Evaluated multiple factors influencing teaching effectiveness.
• Identified key components that impact teaching quality in AI settings.
• Demonstrated the effectiveness of the random forest regression for performance prediction.
• Provided actionable insights for enhancing AI-assisted teaching methodologies.