Question Generation for Assessing Early Literacy Reading Comprehension
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909712179527680 |
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| author | Yang, Xiaocheng Shashidhar, Sumuk Hakkani-Tur, Dilek |
| author_facet | Yang, Xiaocheng Shashidhar, Sumuk Hakkani-Tur, Dilek |
| contents | Assessment of reading comprehension through content-based interactions plays an important role in the reading acquisition process. In this paper, we propose a novel approach for generating comprehension questions geared to K-2 English learners. Our method ensures complete coverage of the underlying material and adaptation to the learner's specific proficiencies, and can generate a large diversity of question types at various difficulty levels to ensure a thorough evaluation. We evaluate the performance of various language models in this framework using the FairytaleQA dataset as the source material. Eventually, the proposed approach has the potential to become an important part of autonomous AI-driven English instructors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_22410 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Question Generation for Assessing Early Literacy Reading Comprehension Yang, Xiaocheng Shashidhar, Sumuk Hakkani-Tur, Dilek Computation and Language Artificial Intelligence Assessment of reading comprehension through content-based interactions plays an important role in the reading acquisition process. In this paper, we propose a novel approach for generating comprehension questions geared to K-2 English learners. Our method ensures complete coverage of the underlying material and adaptation to the learner's specific proficiencies, and can generate a large diversity of question types at various difficulty levels to ensure a thorough evaluation. We evaluate the performance of various language models in this framework using the FairytaleQA dataset as the source material. Eventually, the proposed approach has the potential to become an important part of autonomous AI-driven English instructors. |
| title | Question Generation for Assessing Early Literacy Reading Comprehension |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2507.22410 |