Teachers, Parents, and Students' perspectives on Integrating Generative AI into Elementary Literacy Education
Ariel Han, Xiaofei Zhou, Zhenyao Cai, Shenshen Han, Richard Ko, Seth Corrigan, Kylie A. Peppler
Abstract
The viral launch of new generative AI (GAI) systems, such as Chat-GPT and Text-to-Image (TTL) generators, sparked questions about how they can be efectively incorporated into writing education. However, it is still unclear how teachers, parents, and students perceive and suspect GAI systems in elementary school settings. We conducted a workshop with twelve families (parent-child dyads) with children ages 8-12 and interviewed sixteen teachers in order to understand each stakeholder's perspectives and opinions on GAI systems for learning and teaching writing. We found that the GAI systems could be benefcial in generating adaptable teaching materials for teachers, enhancing ideation, and providing students with personalized, timely feedback. However, there are concerns over authorship, students' agency in learning, and uncertainty concerning bias and misinformation. In this article, we discuss design strategies to mitigate these constraints by implementing an adults-oversight system, balancing AI-role allocation, and facilitating customization to enhance students' agency over writing projects.
• Human-centered computing → Empirical studies in HCI.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 434a1202-99ee-4e54-b84f-88b22b5f0f65Cited by top-tier papers20
- "Don't Forget the Teachers": Towards an Educator-Centered Understanding of Harms from Large Language Models in EducationEmma Harvey, Allison Koenecke, René F. KizilcecCHI 2025 · 63 citations
- Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature ReviewRock Yuren Pang, Hope Schroeder, Kynnedy Simone Smith, Solon Barocas et al.CHI 2025 · 51 citations
- How CO2STLY Is CHI? The Carbon Footprint of Generative AI in HCI Research and What We Should Do About ItNanna Inie, Jeanette Falk, Raghavendra SelvanCHI 2025 · 33 citations
- Exploring Collaboration Patterns and Strategies in Human-AI Co-creation through the Lens of Agency: A Scoping Review of the Top-tier HCI LiteratureShuning Zhang, Hui Wang, Xin YiCSCW 2025 · 31 citations
- PAIGE: Examining Learning Outcomes and Experiences with Personalized AI-Generated Educational PodcastsTiffany D. Do, Usama Bin Shafqat, Elsie Ling, Nikhil SardaCHI 2025 · 28 citations
Builds on17
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah et al.NeurIPS 2020 · 64,255 citations
- Extracting Training Data from Large Language ModelsNicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski et al.USENIX Security 2021 · 2,866 citations
- Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to DesignQian Yang, Aaron Steinfeld, Carolyn P. Rosé, John ZimmermanCHI 2020 · 604 citations
- Design Guidelines for Prompt Engineering Text-to-Image Generative ModelsVivian Liu, Lydia B. ChiltonCHI 2022 · 586 citations
- AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model PromptsTongshuang Wu, Michael Terry, Carrie Jun CaiCHI 2022 · 465 citations
Related papers
- Testing, Socializing, Exploring: Characterizing Middle Schoolers' Approaches to and Conceptions of ChatGPTYasmine Belghith, Atefeh Mahdavi Goloujeh, Brian Magerko, Duri Long et al.CHI 2024 · 30 citations
- Generative AI in Children's Creative Collaboration: Impact, Perception, and Design GuidelinesDaeun Yoo, Michele Newman, Caroline Pitt, Kevin Huu Vo et al.CHI 2026 · 1 citation
- How Do Programming Students Use Generative AI?Christian Rahe, Walid MaalejFSE 2025 · 12 citations
- An Empirical Study to Understand How Students Use ChatGPT for Writing EssaysAndrew Jelson, Daniel Manesh, Alice Jang, Daniel Dunlap et al.CHI 2026 · 3 citations
- Understanding Parents' Desires in Moderating Children's Interactions with GenAI Chatbots through LLM-Generated ProbesJohn Driscoll, Yulin Chen, Viki Shi, Izak Vucharatavintara et al.CHI 2026 · 2 citations
