为低年级英语学习者生成多类型、适配水平的阅读理解题
Question Generation for Assessing Early Literacy Reading Comprehension
- 基于内容生成覆盖全篇的提问，适配不同学习者水平
- 在FairytaleQA数据集上验证，支持多种难度和题型
- 适合构建自动英语教学助手，提升个性化评估能力
通过基于内容的互动评估阅读理解，在阅读习得过程中至关重要。本文提出一种针对K-2年级英语学习者的新型阅读理解问题生成方法。该方法确保对原文内容的完整覆盖，并可根据学习者具体能力进行适配，能生成大量多样化的题型与不同难度的问题，实现全面评估。我们使用FairytaleQA数据集作为素材，评估了多种语言模型在此框架下的表现。所提方法有望成为自主AI英语教师的重要组成部分。
原文摘要 · Abstract (English)
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.
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