ai-assisted-writing
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- PaperLanguage Teaching Research22 Jul 2026
AI-Assisted Digital Storytelling in EFL Teacher Education: A Qualitative Case Study of Digital and Multimodal Literacy Development
Bessie Mitsikopoulou
A qualitative case study of 69 reflective papers from EFL student teachers using generative AI for digital storytelling found that algorithmic limitations fostered critical multimodal design skills, while human input remained essential for emotional coherence.
Original abstract
This qualitative case study explores how English as a foreign language (EFL) student teachers engaged with generative artificial intelligence (GAI) in the collaborative design of digital stories within an advanced undergraduate course in 2024. During the semester, participants critically evaluated and applied various AI applications, such as text-to-image generators, automated video editors and speech synthesis tools, to support different stages of multimodal story production, including script drafting, visual design, audio narration and video editing. Drawing on a corpus of 69 reflective papers (approximately 75,000 words), the study examines how student teachers integrated visual, auditory and textual elements to achieve multimodal cohesion and narrative coherence. The analysis focuses on participants’ practices and strategies for aligning modes, maintaining consistency across media, and adapting to the constraints of AI-generated content. Findings indicate that the project’s primary pedagogical significance lay not in technical efficiency but in the productive ‘friction’ generated by algorithmic limitations, which led participants to move beyond passive tool use and become critical designers of meaning, demonstrating sophisticated multimodal awareness. While AI supported rapid content generation, the human element remained the narrative’s essential ‘emotional glue’, ensuring affective resonance and coherence. Overall, the study suggests that experiential engagement with AI-assisted composition may enable future educators to move beyond functional skills and develop into critically reflective architects of digital narratives.
- PaperTESOL Journal21 Jul 2026
Purpose, Audience, Context, and Culture: A Framework for AI ‐Assisted Writing in ELT Classrooms
Flora D. Floris, Willy A. Renandya
Proposes the PACC framework (Purpose, Audience, Context, Culture) for AI-assisted writing in ELT, based on Systemic Functional Linguistics and Genre Theory. The framework guides students in designing AI prompts and evaluating AI-generated texts to ensure they meet communicative needs. It offers practical strategies for integrating AI into writing instruction.
Original abstract
Artificial intelligence (AI) tools can help students draft and revise texts more efficiently. However, AI‐generated texts may sound fluent but still fail to meet the needs of readers. This article proposes the PACC framework as a conceptual model for AI‐assisted writing in ELT. Informed by Systemic Functional Linguistics and Genre Theory, PACC focuses on four elements: purpose, audience, context, and culture. Students use these elements to design AI prompts and to evaluate and revise the AI‐generated text. This article explains the theoretical basis of the framework, shows how it can be applied in writing lessons, presents an integrated classroom example, and discusses possible implementation challenges. The PACC framework contributes to ELT writing instruction by giving teachers and students a practical and meaningful way when preparing AI prompts and when reviewing AI‐generated texts.
- PaperAssessing Writing15 Jun 2026
Young L2 students’ use of an AI-assisted writing assessment and feedback tool: An exploratory study in multiple settings
Mikyung Kim Wolf, Michael Suhan, Paul Deane, Lorraine Sova et al.
An exploratory study examines how young second language learners interact with an AI-assisted writing assessment and feedback tool across different educational settings.
- PaperLanguage Learning & Technology1 Jan 2026
Distributed agency in AI-assisted L2 writing
Pin-Hsi Patrick Chen, Yichun Liu
A longitudinal qualitative study of Taiwanese university students found that distributed agency between human writers and generative AI shapes L2 writing across intentionality, forethought, self-reactiveness, and self-reflectiveness, both supporting and constraining learner engagement depending on how it is exercised.
Original abstract
This longitudinal qualitative study examines distributed agency between human writers and generative AI in the context of L2 writing. Grounded in Bandura’s theory of agency, the study analyzes students’ written texts, reflective accounts, and AI interaction logs collected from Taiwanese university students. The findings indicate that human-AI distributed agency shapes the enactment of L2 writing across intentionality, forethought, self-reactiveness, and self-reflectiveness. Moreover, distributed agency both supports and constrains learners’ engagement, depending on how it is exercised.