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Cited by 29Reading and Literacy DevelopmentChild Development and Digital TechnologyIntelligent Tutoring Systems and Adaptive Learning

ContextQ: Generated Questions to Support Meaningful Parent-Child Dialogue While Co-Reading

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Dietz Smith, Griffin, Prasad, Siddhartha, Davidson, Matt J., Findlater, Leah, Shapiro, R. Benjamin·2024·Proceedings of the 23rd Annual ACM Interaction Design and Children Conference
DOI 10.1145/3628516.3655809
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Abstract

Much of early literacy education happens at home with caretakers reading books to young children. Prior research demonstrates how having dialogue with children during co-reading can develop critical reading readiness skills, but most adult readers are unsure if and how to lead effective conversations. We present ContextQ, a tablet-based reading application to unobtrusively present auto-generated dialogic questions to caretakers to support this dialogic reading practice. An ablation study demonstrates how our method of encoding educator expertise into the question generation pipeline can produce high-quality output; and through a user study with 12 parent-child dyads (child age: 4–6), we demonstrate that this system can serve as a guide for parents in leading contextually meaningful dialogue, leading to significantly more conversational turns from both the parent and the child and deeper conversations with connections to the child’s everyday life.

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  • AI adjusts the specificity, depth, and difficulty of feedback based on students' abilities and prior performance, enabling tailored prompts and tiered guidance.

    “AI adjusts the specificity, depth, and difficulty of feedback based on students' abilities and prior performance, enabling tailored prompts and tiered guidance.”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [89]

    The Introduction (p. 2) and Question Generation Module (p. 5) describe feedback used to revise generated questions through prompt adjustment. That feedback assesses question suitability, not students’ abilities or prior performance. Future Work (p. 11) proposes adapting questions to an individual child’s age or familiarity with a book, rather than reporting it as a current feature; the paper does not establish tiered guidance for students. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • AI strengthens the social dimension of practice by facilitating peer collaboration and parent-child dialogue.

    “Finally, AI strengthens the social dimension of practice by facilitating peer collaboration [103,112] and parent-child dialogue [71,89].”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [89]

  • Existing studies have primarily focused on addressing child-centric needs, overlooking parental roles.

    “Yet, existing studies have primarily focused on addressing child-centric needs, overlooking parental roles.”

    From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [13]

  • ContextQ presented auto-generated dialogic questions to caregivers for dialogic reading, but primarily considered situations where parents are actively involved, not scenarios where parents cannot participate fully.

    “Similarly, ContextQ [13] presented auto-generated dialogic questions to caregivers for dialogic reading, but primarily considered situations where parents are actively involved, not scenarios where parents cannot participate fully.”

    From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [13]

  • Some educational robots, such as Miko, are now priced similarly to smartphones, improving feasibility for families.

    “In addition, while cost remains a common accessibility limitation, some educational robots, such as Miko, 13 are now priced similarly to smartphones, improving feasibility for families.”

    From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [13]

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Research works printed but not linked: 24

  1. [1][1] Heidi Goodrich Andrade. 2000. Using rubrics to promote thinking and learning. Educational leadership 57, 5 (2000), 13-19. -
  2. [2][2] David H Arnold, Christopher J Lonigan, Grover J Whitehurst, and Jeffery N Epstein. 1994. Accelerating language development through picture book reading: replication and extension to a videotape training format. Journal of educational psychology 86, 2 (1994), 235. -
  3. [3][3] Isabel L Beck and Margaret G McKeown. 2001. Text talk: Capturing the benefits of read-aloud experiences for young children. The reading teacher 55, 1 (2001), 10-20. -
  4. [7][7] Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative research in psychology 3, 2 (2006), 77-101. -
  5. [8][8] Milan Češka, Christian Hensel, Sebastian Junges, and Joost-Pieter Katoen. 2019. Counterexample-Driven Synthesis for Probabilistic Program Sketches. In Formal Methods - The Next 30 Years , Maurice H. ter Beek, Annabelle McIver, and José N. Oliveira (Eds.). Springer International Publishing, Cham, 101-120. -
  6. [12][12] Sérgio Curto, Ana Cristina Mendes, and Luísa Coheur. 2011. Exploring linguistically-rich patterns for question generation. In Proceedings of the UCNLG+ eval: Language Generation and Evaluation Workshop . 33-38. -
  7. [14][14] Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon. 2019. Unified language model pretraining for natural language understanding and generation. Advances in neural information processing systems 32 (2019). -
  8. [17][17] Elisabeth Duursma, Marilyn Augustyn, and Barry Zuckerman. 2008. Reading aloud to children: the evidence. Archives of disease in childhood 93, 7 (2008), 554-557. -
  9. [19][19] David J Francis, Sally E Shaywitz, Karla K Stuebing, Bennett A Shaywitz, and Jack M Fletcher. 1996. Developmental lag versus deficit models of reading disability: A longitudinal, individual growth curves analysis. Journal of Educational psychology 88, 1 (1996), 3. -
  10. [24][24] Connie Juel. 1988. Learning to read and write: A longitudinal study of 54 children from first through fourth grades. Journal of educational Psychology 80, 4 (1988), 437. -
  11. [30][30] Kathryn Leech, Ran Wei, Jeffrey R Harring, and Meredith L Rowe. 2018. A brief parent-focused intervention to improve preschoolers' conversational skills and school readiness. Developmental psychology 54, 1 (2018), 15. -
  12. [35][35] Suzanne E Mol, Adriana G Bus, Maria T De Jong, and Daisy JH Smeets. 2008. Added value of dialogic parent-child book readings: A meta-analysis. Early education and development 19, 1 (2008), 7-26. -
  13. [36][36] Martin Nystrand. 1997. Opening dialogue: Understanding the dynamics of language and learning in the English classroom . Teachers College Press. -
  14. [37][37] Martin Nystrand, Lawrence L Wu, Adam Gamoran, Susie Zeiser, and Daniel A Long. 2003. Questions in time: Investigating the structure and dynamics of unfolding classroom discourse. Discourse processes 35, 2 (2003), 135-198. -
  15. [40][40] Caroline Schaffalitzky. 2022. What makes authentic questions authentic? Dialogic Pedagogy: An International Online Journal (2022). -
  16. [43][43] Gabrielle A Strouse, Katherine O'Doherty, and Georgene L Troseth. 2013. Effective coviewing: Preschoolers' learning from video after a dialogic questioning intervention. Developmental psychology 49, 12 (2013), 2368. -
  17. [44][44] Zachary D Stuckelman, Gabrielle A Strouse, and Georgene L Troseth. 2021. Value added: Digital modeling of dialogic questioning promotes positive parenting during shared reading. Journal of Family Psychology (2021). -
  18. [45][45] Todd H Sundeen. 2014. Instructional rubrics: Effects of presentation options on writing quality. Assessing writing 21 (2014), 74-88. -
  19. [47][47] Joseph K Torgesen and Stephen R Burgess. 1998. Consistency of reading-related phonological processes throughout early childhood: Evidence from longitudinalcorrelational and instructional studies. Word recognition in beginning literacy 161 (1998), 188. -
  20. [48][48] Georgene L Troseth, Gabrielle A Strouse, Israel Flores, Zachary D Stuckelman, and Colleen Russo Johnson. 2020. An enhanced eBook facilitates parent-child talk during shared reading by families of low socioeconomic status. Early childhood research quarterly 50 (2020), 45-58. -
  21. [49][49] Marta C Valdez-Menchaca and Grover J Whitehurst. 1992. Accelerating language development through picture book reading: A systematic extension to Mexican day care. Developmental psychology 28, 6 (1992), 1106. -
  22. [51][51] Grover J Whitehurst, Jeffrey N Epstein, Andrea L Angell, Adam C Payne, Deanne A Crone, and Janet E Fischel. 1994. Outcomes of an emergent literacy intervention in Head Start. Journal of Educational Psychology 86, 4 (1994), 542. -
  23. [57][57] Andrea A Zevenbergen and Grover J Whitehurst. 2003. Dialogic reading: A shared picture book reading intervention for preschoolers. On reading books to children: Parents and teachers 177 (2003), 200. -
  24. [58][58] Zheng Zhang, Ying Xu, Yanhao Wang, Bingsheng Yao, Daniel Ritchie, Tongshuang Wu, Mo Yu, Dakuo Wang, and Toby Jia-Jun Li. 2022. StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement. In CHI Conference on Human Factors in Computing Systems . 1-21.

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Authors
Dietz Smith, G., Prasad, S., Davidson, M. J., Findlater, L., & Shapiro, R. B.
Affiliations
  • Apple, United States
  • Brown University (US)
  • Apple (United States) (US)
ORCID
Venue
Proceedings of the 23rd Annual ACM Interaction Design and Children Conference
Publisher
ACM
Published
2024-06-17
Pages
408-423
DOI
10.1145/3628516.3655809
OpenAlex
W4396813786
Cited by
29
References
25
Citations by year
2026: 15 · 2025: 12 · 2024: 2
FWCI
44.64
Type
conference paper
Language
en
Open access
Licence
Locations
  • ACM International Conference on Interaction Design and Children (IDC) (publishedVersion, cc-by)
  • arXiv (Cornell University) (submittedVersion, cc-by)
  • arXiv (Cornell University) (cc-by)
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
  • Social Sciences › Education › Child Development and Digital Technology
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords
dialogic reading, shared reading, parent-child dialogue, question generation, early literacy, reading readiness, conversational turns, young children

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