Research on optimization of human-computer interaction experience and intelligent feedback algorithm in English teaching driven by educational robot

This study focuses on English teaching driven by educational robot, optimizing human-computer interaction experience and designing effective intelligent feedback algorithm to improve teaching effect and learning experience. By optimizing the design of human-computer interaction interface, following the principles of intuition and ease of use, and making personalized adaptation for English teaching scenes, the interaction process is simplified, and the participation of learners is enhanced by adopting intelligent course selection and diversified content presentation methods. Intelligent feedback algorithm framework integrates multi-modal data, evaluates multi-dimensional learning performance such as pronunciation and grammar in real time, and provides personalized feedback by using dynamic weight adjustment and real-time error correction model. The experiment takes 120 middle school English learners as the object, and compares the traditional teaching, basic education robot and the optimized system. The results show that the optimized system is significantly superior to the control group in learning effect, interaction frequency, grammar correction accuracy and user satisfaction, which shows that it has significant advantages in improving English teaching effect and user experience, and provides new ideas and methods for the application of educational technology in English teaching.