|
|
--- |
|
|
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 |
|
|
--- |
