A language learning evaluation method and system based on large language model feedback
Patent Information
- Application Number
- CN202411001912.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-25
- Publication Date
- 2025-03-18
- Estimated Expiration
- 2044-07-25
AI Technical Summary
The existing language learning evaluation method based on large language models lacks comprehensive analysis and feedback on the content of the writing text, cannot comprehensively and accurately evaluate the user's language learning effect, and lacks sentiment analysis of learning behavior patterns and user learning processes, resulting in language learning evaluation being too single, affecting the accuracy of the analysis.
It provides a language learning evaluation method based on feedback from large language model. By obtaining and preprocessing the content data of language writing text, using large language model to perform multiple writing content analysis feedback, generating reflection log information and feedback record information, combining matrix encoding for learning behavior pattern analysis, and using dual-channel attention mechanism for emotion analysis, and finally conducting comprehensive evaluation of language learning.
By analyzing the content of language writing texts in multiple dimensions, users can understand their own language learning and writing problems more comprehensively and accurately, and promote self-learning. Learning behavior patterns and emotion analysis improves the accuracy of language learning impact analysis, avoids the one-sidedness of evaluation, effectively improves the quality of users' language learning, and makes the evaluation effect more ideal.