The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.
Teachers, Parents, and Students' perspectives on Integrating Generative AI into Elementary Literacy Education
Open accessAbstract
The viral launch of new generative AI (GAI) systems, such as ChatGPT and Text-to-Image (TTL) generators, sparked questions about how they can be effectively 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 beneficial 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.
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In the citing paper
“Teachers and parents are likewise introducing conversational AI into classrooms and homes-to generate teaching materials, orchestrate chained questioning, co-author stories, and automate grading [8,9].”
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 [9]
In the citing paper
“Furthermore, GenAI facilitates intercultural competence by incorporating diverse cultural contents into language learning.”
From Generative AI in Language Education: Bridging Divide and Fostering Inclusivity (2025) · cites this paper as Han et al., 2024
In the citing paper
“Cultural understanding and the reduction of biases in language learning, highlighted in studies by Han et al. (2024) and Lee et al. (2024), suggest that GenAI can serve as culturally intelligent tools.”
From Generative AI in Language Education: Bridging Divide and Fostering Inclusivity (2025) · cites this paper as Han et al., 2024
In the citing paper
“A parent mentioned using GenAI to generate content about traditional Asian dragons to teach her child about their cultural heritage.”
From Generative AI in Language Education: Bridging Divide and Fostering Inclusivity (2025) · cites this paper as Han et al., 2024
In the citing paper
“The findings pinpoint that GenAI can provide culturally relevant examples and feedback.”
From Generative AI in Language Education: Bridging Divide and Fostering Inclusivity (2025) · cites this paper as Han et al., 2024
In the citing paper
“Also, GenAI can create culturally salient stories, like fables, which resonate with a learner's heritage.”
From Generative AI in Language Education: Bridging Divide and Fostering Inclusivity (2025) · cites this paper as Han et al., 2024
In the citing paper
“In the reviewed papers, two studies [10,24] explicitly suggest that when AI systems are allowed to freely generate content, students may rely on AI for the entire output, completing their work with minimal engagement in the creative process.”
From Child-AI Co-Creation: A Review of the Current Research Landscape and a Proposal for Six Design Considerations (2025) · cites this paper as [24]
In the citing paper
“Other papers [10,24,37,61] discussed how misinformation or biased content can emerge unpredictably, especially when children rely heavily on generative models without understanding their underlying data sources.”
From Child-AI Co-Creation: A Review of the Current Research Landscape and a Proposal for Six Design Considerations (2025) · cites this paper as [24]
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Metadata
- Authors
- Han, A., Zhou, X., Cai, Z., Han, S., Ko, R., Corrigan, S., & Peppler, K. A.
- Affiliations
- University of California, Irvine (US)
- University of Rochester (US)
- UC Irvine, United States
- Venue
- Proceedings of the CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2024-05-11
- Pages
- 1-17
- OpenAlex
- W4396832735
- Semantic Scholar
- 58c21b7488ec9d5cdf51507c740277acacf10f3d
- Cited by
- 114
- References
- 80
- Citations by year
- 2026: 50 · 2025: 54 · 2024: 10
- FWCI
- 43.31
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion, cc-by)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Education › Education and Technology Integration
- Keywords
- generative AI, writing instruction, teacher perceptions, parental attitudes, student perceptions, ChatGPT, authorship, student agency, personalized feedback, idea generation
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