arXiv:2305.16809

GenQ: Automated Question Generation to Support Caregivers While Reading Stories with Children

Arun Balajiee Lekshmi Narayanan, Ligia E. Gomez, Martha Michelle Soto Fernandez, Tri Nguyen, Chris Blais, M. Adelaida Restrepo, Art Glenberg

제출 2023-05-26

원문 초록

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.

함께 살펴볼 논문

공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.

arXiv:2405.13006공통 태그 Question Generation, Question-Generation, Reading Comprehension

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