Dynamic diagnosis of students state in English classes based on feature decoupling and improved active learning algorithm

Key Points

• The central aim is to evaluate student states in English classes using innovative diagnostic methods.
• Implemented feature decoupling techniques to assess student performance.
• Utilized an improved active learning algorithm for dynamic diagnosis.
• Conducted analyses based on student assessments during classes.
• Improved diagnostic accuracy in assessing student needs during English classes.
• Enhanced learning outcomes linked to the active learning algorithm implementation.