When caregivers ask open--ended questions to motivate dialogue with children, it facilitates the child's reading comprehension skills.Although there is scope for use of technological tools, referred here as "intelligent tutoring systems", to scaffold this process, it is currently unclear whether existing intelligent systems that generate human--language like questions is beneficial. Additionally, training data used in the development of these automated question generation systems is typically sourced without attention to demographics, but people with different cultural backgrounds may ask different questions. As a part of a broader project to design an intelligent reading support app for Latinx children, we crowdsourced questions from Latinx caregivers and noncaregivers as well as caregivers and noncaregivers from other demographics. We examine variations in question--asking within this dataset mediated by individual, cultural, and contextual factors. We then design a system that automatically extracts templates from this data to generate open--ended questions that are representative of those asked by Latinx caregivers.

翻译：当照护者提出开放式问题以激发与儿童的对话时，这有助于提升儿童的阅读理解能力。尽管存在利用技术工具（本文中称为“智能辅导系统”）来辅助这一过程的可能性，但当前尚不明确现有智能系统生成的类人类语言问题是否具有实际益处。此外，这些自动化问题生成系统开发所用的训练数据通常在未关注人口统计学特征的情况下获取，但不同文化背景的人群可能会提出不同的问题。作为为拉丁裔儿童设计智能阅读支持应用这一更广泛项目的一部分，我们通过众包方式征集了拉丁裔照护者与非照护者，以及其他人口统计学背景的照护者与非照护者所提出的问题。我们考察了该数据集中由个体、文化与情境因素介导的问题提问差异，并设计了一个系统，能从这些数据中自动提取模板，以生成能够代表拉丁裔照护者所提问题的开放式问题。