| | --- |
| | license: cc-by-4.0 |
| | language: |
| | - zh |
| | --- |
| | # LLM Evaluation Benchmark for Chinese Language Teaching (CLTE) |
| |
|
| | A comprehensive benchmark for evaluating large language models' capabilities as Chinese language teachers, consisting of three core evaluation dimensions. |
| |
|
| |
|
| | ## Evaluation Framework |
| | **GitHub URL:** [https://github.com/Line-Kite/CLTE](https://github.com/Line-Kite/CLTE) |
| |
|
| | ## Task Overview |
| |
|
| | ### Task 1: Basic Knowledge Evaluation |
| | - **Objective:** Assess foundational knowledge essential for international Chinese education |
| | - **Coverage:** 32 sub-topics across 5 major categories: |
| | - Linguistics (307 questions) |
| | - Chinese Culture (321 questions) |
| | - Pedagogy (163 questions) |
| | - World Culture (192 questions) |
| | - Cross-cultural Communication (217 questions) |
| | - **Total:** 1,200 questions evaluating fundamental knowledge base |
| |
|
| | ### Task 2: International Teacher Examination |
| | - **Objective:** Evaluate comprehensive teaching literacy using authentic certification materials |
| | - **Data Source:** Real-world test questions from official International Chinese Language Teacher Certification exams |
| | - **Format:** Instructional passages accompanied by 2-10 single-choice questions (1,044 total questions) |
| | - **Focus:** Integrated linguistic and pedagogical reasoning in practical teaching scenarios |
| |
|
| | ### Task 3: Teaching Practice Evaluation |
| | - **Objective:** Measure instructional effectiveness through simulated teaching interactions |
| | - **Methodology:** |
| | - Teacher models generate educational content from 120 teaching materials and guidelines |
| | - Student models are tested before and after receiving instruction |
| | - Effectiveness measured by performance improvement (120 assessment questions) |
| |
|
| | ## Citation |
| | Please cite our paper if the work helps you. |
| |
|
| | ``` |
| | @inproceedings{xu2025can, |
| | title={Can Large Language Models Be Good Language Teachers?}, |
| | author={Xu, LiQing and Li, Qiwei and Peng, Tianshuo and Li, Zuchao and Zhao, Hai and Wang, Ping}, |
| | booktitle={Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing}, |
| | pages={23968--23982}, |
| | year={2025} |
| | } |
| | ``` |
| |
|
| | --- |
| | license: cc-by-4.0 |
| | --- |
