Perspective Article
Textual Typologies for AI-Assisted Writing: Integrating New Literacy Studies and Language Assessment Practices
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This paper integrates the discussion of current digital innovations, their uses for academic writing instruction, and its implication for language assessment. Using the revisited New Literacy Studies (NLS) framework (Pegrum et al., 2018, 2022), I suggest considering a structural organization to guide practices of academic writing and their assessment: A typology of AI-Assisted Writing that includes Original, Augmented, and Synthetic texts. By connecting digital literacy studies to seminal work on textual typology (Reiss, 1970, 1989), this reflection calls for interdisciplinary discussion and the use cross-curricular approaches to align educational policies for AI-assisted writing in language assessment practices. The suggested frames serve as pedagogical anchors to ignite ideas on meaningful classroom design environments, but also as points of departure for the construction of professional development plans and teacher language assessment literacy programs that address current skills and principles when LLM-based writing steps as a disruptive tool in academic writing. The paper closes with a conclusion in the line of promoting studies that embedded digitally mediated strategic academic literacy informed by empirical evidence from diverse classrooms and across stages of Language Assessment Literacy that stakeholders may have.
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Keywords
Digitally Assisted Writing; Generative Artificial Intelligence; Language Assessment Literacy; New Literacy Studies; LLM-Based Assessment
Author(s) Information
Publisher’s Note
The claims, arguments, and counter-arguments made in this article are exclusively those of the contributing authors. Hence, they do not necessarily represent the viewpoints of the authors’ affiliated institutions, or EUROKD as the publisher, the editors and the reviewers of the article.
Acknowledgements
This reflection is the result of the varied conversations held with my students and their concerns about the writing of their thesis. Without their concerns it would not have been possible to come up with insights and the connections established for this paper. Deep gratitude with Dr. Hernán Gil and Dr. Rosa Maria Guilleumas who trusted my competence to guide these students in their master’s writing journey. Finally, special thanks to Ying Luo who read the initial version of the manuscript and prompted interesting insights to make this a deeper reflection on the field.
Funding
This project received no external funding.
CRediT Authorship Contribution Statement
Daniel Murcia: Conceptualization, Methodology, Investigation, Data Curation, Writing – Original Draft, Writing – Review & Editing
Generative AI Use Disclosure Statement
During the editing phase of this work, the author used the legacy model GPT-4o with Notion to proofread and improve the readability and language. After using these tools, the author reviewed and edited the content as needed and takes full responsibility for the content of the publication.
Ethics Declarations
World Medical Association (WMA) Declaration of Helsinki–Ethical Principles for Medical Research Involving Human Participants
This study was conducted in accordance with the ethical principles of the World Medical Association Declaration of Helsinki. Perception data belongs to the data collected in Murcia et al. (2025). All participants provided informed written consent prior to participation, and participation was voluntary.
Competing Interests
The author declares that there are no competing interests.
Data Availability
The data used for this study are textual accounts found in Murcia et al. (2025).