Cited by 213Artificial Intelligence in EducationEFL/ESL Teaching and LearningArtificial Intelligence in Healthcare and Education

Exploring students’ generative AI-assisted writing processes: Perceptions and experiences from native and nonnative English speakers

Open access
Wang, Chaoran·2025·Technology Knowledge and Learning

Abstract

Abstract Generative artificial intelligence (AI) can create sophisticated textual and multimodal content readily available to students. Writing intensive courses and disciplines that use writing as a major form of assessment are significantly impacted by advancements in generative AI, as the technology has the potential to revolutionize how students write and how they perceive writing as a fundamental literacy skill. However, educators are still at the beginning stage of understanding students’ integration of generative AI in their actual writing process. This study addresses the urgent need to uncover how students engage with ChatGPT throughout different components of their writing processes and their perceptions of the opportunities and challenges of generative AI. Adopting a phenomenological research design, the study explored the writing practices of six students, including both native and nonnative English speakers, in a first-year writing class at a higher education institution in the US. Thematic analysis of students’ written products, self-reflections, and interviews suggests that students utilized ChatGPT for brainstorming and organizing ideas as well as assisting with both global (e.g., argument, structure, coherence) and local issues of writing (e.g., syntax, diction, grammar), while they also had various ethical and practical concerns about the use of ChatGPT. The study brought to front two dilemmas encountered by students in their generative AI-assisted writing: (1) the challenging balance between incorporating AI to enhance writing and maintaining their authentic voice, and (2) the dilemma of weighing the potential loss of learning experiences against the emergence of new learning opportunities accompanying AI integration. These dilemmas highlight the need to rethink learning in an increasingly AI-mediated educational context, emphasizing the importance of fostering students’ critical AI literacy to promote their authorial voice and learning in AI-human collaboration.

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  • Emerging frameworks emphasize process-oriented assessment that documents iterative revision, reflective decision-making, and AI integration strategies rather than solely evaluating final products.

    “Emerging frameworks emphasize process-oriented assessment that documents iterative revision, reflective decision-making, and AI integration strategies rather than solely evaluating final products (Engeness and Gamlem, 2025; Tseng and Lin, 2024; Wang, 2024).”

    From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024

    The Conclusion (section 7; page unavailable) calls for writing assessment to consider the learning journey and decisions made during AI-assisted writing, not just final products. The Discussion (section 6; page unavailable) also emphasizes self-reflection and students’ strategies for using AI. The paper does not specifically propose documenting iterative revision as an assessment practice. (LLM, conf=0.85)

    Experimental — accuracy not yet measured
  • Students, particularly those facing language barriers or socioeconomic pressures, conceptualize AI as an equalizing tool that democratizes access to high-quality writing support.

    “Students, particularly those facing language barriers or socioeconomic pressures, conceptualize AI as an equalizing tool that democratizes access to high-quality writing support (Wang, 2024).”

    From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024

    The Discussion (section 6; page unavailable) reports that L2 students experienced AI as helping them overcome language barriers and express their ideas. The cited passages do not show students facing socioeconomic pressures or describe AI as democratizing access to high-quality writing support; those parts of the claim go beyond the study’s findings. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • LLMs dominate the planning phase for idea generation and outlining and continue supporting drafting for content expansion, while AWE tools are reserved primarily for revision and editing.

    “LLMs dominate the planning phase for idea generation and outlining, continue supporting the drafting phase for content expansion, while AWE tools are reserved primarily for revision and editing (Wang, 2024; Zhao and Dang, 2026).”

    From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024

    The Findings (§5.1; page unavailable) report students using ChatGPT to brainstorm ideas and organize outlines, supporting its role in planning. They also report ChatGPT use in revision and editing, but do not establish that LLMs dominate planning or support drafting through content expansion. The Literature Review (§2.1; page unavailable) describes AWE as aiding writing, revision, and self-learning, not as reserved primarily for revision and editing. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • Explicit instruction in prompt engineering and critical AI literacy positions AI as a legitimate skill development object rather than taboo.

    “Explicit instruction in prompt engineering and critical AI literacy positions AI as legitimate skill development object rather than taboo (Talandis and Muller, 2025; Wang, 2024).”

    From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Wang, 2024

    The Conclusion (section 7) recommends critical digital pedagogy, reflection on AI literacy, and an inclusive rather than “policing” environment that treats AI as a resource for learning. The Discussion (section 6) also calls students’ AI-related decision-making a teaching opportunity. These passages support the critical AI literacy and non-taboo framing, but they do not specifically advocate explicit instruction in prompt engineering. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • Studies examining AI-assisted writing tasks report that students often produce more fluent and well-structured text, while improvements in argument quality or conceptual reasoning remain limited.

    “For example, studies examining AI-assisted writing tasks report that students often produce more fluent and well-structured text, while improvements in argument quality or conceptual reasoning remain limited [10][11][12].”

    From Fluency Illusion: A Review on Influence of ChatGPT in Classroom Settings (2026) · cites this paper as [11]

    In 5 Findings (page unavailable), a student says ChatGPT made her language more fluent, and students describe using it to improve organization and structure. The same section reports that students found its responses generalized and lacking depth on questions requiring critical thinking. The study reports students’ experiences, however, rather than measuring text quality or showing that improvements in argument quality or conceptual reasoning were limited. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Authors
Wang, C.
Affiliations
Colby College (US)
Corresponding author
Wang, Chaoran
Venue
Technology Knowledge and Learning
Published
2024-05-30
Volume
30
Issue
3
Pages
1825-1846
ISSN
  • 2211-1662 (ISSN-L)
  • 2211-1670
OpenAlex
W4399182459
Cited by
212
References
72
Citations by year
2026: 119 · 2025: 81 · 2024: 12
FWCI
79.71
Type
journal article
Language
en
Open access
Locations
Technology Knowledge and Learning (publishedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
generative AI in writing, ChatGPT, writing process, student perceptions, first-year composition, authorial voice, critical AI literacy, human-AI collaboration, ethics of writing

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