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：摘要：当照护者通过提出开放式问题来促进与儿童的对话时，这一做法有助于提升儿童阅读理解能力。尽管存在运用技术工具（本文称为"智能辅导系统"）来辅助这一过程的可能，但目前尚不清楚现有能够生成类人语言问题的智能系统是否具有实际效益。此外，这些自动化问题生成系统开发所用的训练数据通常未考虑人口统计学特征，但不同文化背景的人群可能提出不同的问题。作为旨在为拉丁裔儿童设计智能阅读支持应用的更广泛项目的一部分，我们通过众包方式收集了来自拉丁裔照护者与非照护者，以及其他人口统计学特征的照护者与非照护者提出的问题。我们分析了该数据集中由个体、文化和情境因素调节的提问方式差异，进而设计了一个能从这些数据中自动提取模板的系统，以生成能够代表拉丁裔照护者提问特征的开放式问题。