Edu-Values: Towards Evaluating the Chinese Education Values of Large Language Models

• URL: http://arxiv.org/abs/2409.12739v2
• Date: Thu, 10 Oct 2024 06:58:35 GMT
• Title: Edu-Values: Towards Evaluating the Chinese Education Values of Large Language Models
• Authors: Peiyi Zhang, Yazhou Zhang, Bo Wang, Lu Rong, Jing Qin,
• Abstract summary: We present Edu-Values, the first Chinese education values evaluation benchmark designed to measure large language models' alignment ability. We meticulously design and compile 1,418 questions, including multiple-choice, multi-modal question answering, subjective analysis, adversarial prompts, and questions on traditional Chinese culture. Due to differences in educational culture, Chinese LLMs significantly outperform English LLMs, with Qwen 2 ranking the first with a score of 81.37.
• Score: 9.761584874383873
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: With the recent evolution of large language models (LLMs), concerns about aligning such models with human values have grown. Previous research has primarily focused on assessing LLMs' performance in terms of the Helpful, Honest, Harmless (3H) basic principles, while often overlooking their alignment with educational values in the Chinese context. To fill this gap, we present Edu-Values, the first Chinese education values evaluation benchmark designed to measure LLMs' alignment ability across seven dimensions: professional ideology, cultural literacy, educational knowledge and skills, education laws and regulations, teachers' professional ethics, basic competencies, and subject knowledge. We meticulously design and compile 1,418 questions, including multiple-choice, multi-modal question answering, subjective analysis, adversarial prompts, and questions on traditional Chinese culture. We conduct both human evaluation and automatic evaluation over 11 state-of-the-art (SoTA) LLMs, and highlight three main findings: (1) due to differences in educational culture, Chinese LLMs significantly outperform English LLMs, with Qwen 2 ranking the first with a score of 81.37; (2) LLMs perform well in subject knowledge and teaching skills but struggle with teachers' professional ethics and basic competencies; (3) LLMs excel at multiple-choice questions but perform poorly on subjective analysis and multi-modal tasks. This demonstrates the effectiveness and potential of the proposed benchmark. Our dataset is available at https://github.com/zhangpeii/Edu-Values.git.

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