LearnLens: LLM-Enabled Personalised, Curriculum-Grounded Feedback with Educators in the Loop
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866917010444648448 |
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| author | Zhao, Runcong Bobrov, Artem Li, Jiazheng Aloisi, Cesare He, Yulan |
| author_facet | Zhao, Runcong Bobrov, Artem Li, Jiazheng Aloisi, Cesare He, Yulan |
| contents | Effective feedback is essential for student learning but is time-intensive for teachers. We present LearnLens, a modular, LLM-based system that generates personalised, curriculum-aligned feedback in science education. LearnLens comprises three components: (1) an error-aware assessment module that captures nuanced reasoning errors; (2) a curriculum-grounded generation module that uses a structured, topic-linked memory chain rather than traditional similarity-based retrieval, improving relevance and reducing noise; and (3) an educator-in-the-loop interface for customisation and oversight. LearnLens addresses key challenges in existing systems, offering scalable, high-quality feedback that empowers both teachers and students. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_04295 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | LearnLens: LLM-Enabled Personalised, Curriculum-Grounded Feedback with Educators in the Loop Zhao, Runcong Bobrov, Artem Li, Jiazheng Aloisi, Cesare He, Yulan Computers and Society Artificial Intelligence Computation and Language Human-Computer Interaction Effective feedback is essential for student learning but is time-intensive for teachers. We present LearnLens, a modular, LLM-based system that generates personalised, curriculum-aligned feedback in science education. LearnLens comprises three components: (1) an error-aware assessment module that captures nuanced reasoning errors; (2) a curriculum-grounded generation module that uses a structured, topic-linked memory chain rather than traditional similarity-based retrieval, improving relevance and reducing noise; and (3) an educator-in-the-loop interface for customisation and oversight. LearnLens addresses key challenges in existing systems, offering scalable, high-quality feedback that empowers both teachers and students. |
| title | LearnLens: LLM-Enabled Personalised, Curriculum-Grounded Feedback with Educators in the Loop |
| topic | Computers and Society Artificial Intelligence Computation and Language Human-Computer Interaction |
| url | https://arxiv.org/abs/2507.04295 |