"There Is No Such Thing as a Dumb Question," But There Are Good Ones
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866915287941513216 |
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| author | Shin, Minjung Kim, Donghyun Ryu, Jeh-Kwang |
| author_facet | Shin, Minjung Kim, Donghyun Ryu, Jeh-Kwang |
| contents | Questioning has become increasingly crucial for both humans and artificial intelligence, yet there remains limited research comprehensively assessing question quality. In response, this study defines good questions and presents a systematic evaluation framework. We propose two key evaluation dimensions: appropriateness (sociolinguistic competence in context) and effectiveness (strategic competence in goal achievement). Based on these foundational dimensions, a rubric-based scoring system was developed. By incorporating dynamic contextual variables, our evaluation framework achieves structure and flexibility through semi-adaptive criteria. The methodology was validated using the CAUS and SQUARE datasets, demonstrating the ability of the framework to access both well-formed and problematic questions while adapting to varied contexts. As we establish a flexible and comprehensive framework for question evaluation, this study takes a significant step toward integrating questioning behavior with structured analytical methods grounded in the intrinsic nature of questioning. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2505_09923 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | "There Is No Such Thing as a Dumb Question," But There Are Good Ones Shin, Minjung Kim, Donghyun Ryu, Jeh-Kwang Artificial Intelligence Questioning has become increasingly crucial for both humans and artificial intelligence, yet there remains limited research comprehensively assessing question quality. In response, this study defines good questions and presents a systematic evaluation framework. We propose two key evaluation dimensions: appropriateness (sociolinguistic competence in context) and effectiveness (strategic competence in goal achievement). Based on these foundational dimensions, a rubric-based scoring system was developed. By incorporating dynamic contextual variables, our evaluation framework achieves structure and flexibility through semi-adaptive criteria. The methodology was validated using the CAUS and SQUARE datasets, demonstrating the ability of the framework to access both well-formed and problematic questions while adapting to varied contexts. As we establish a flexible and comprehensive framework for question evaluation, this study takes a significant step toward integrating questioning behavior with structured analytical methods grounded in the intrinsic nature of questioning. |
| title | "There Is No Such Thing as a Dumb Question," But There Are Good Ones |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2505.09923 |