Single Paper Session 19

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ChatGPT as a writing coach: A mixed-methods study in higher education

Keywords
academic writing;AI writing;education;feedback
Domain
Higher Education

Abstract

The role of ChatGPT in education has been a widely discussed topic, considering its ability to provide immediate feedback and personalised guidance to users (Lo, 2023). This mixed-methods study investigates ChatGPT’s role in enhancing text quality through feedback in higher education, focusing on its potential to support argumentative writing. The research comprises two within-participant design studies (N=16) and a qualitative analysis of student interactions with ChatGPT.Study 1 examined the impact of structured, task-level ChatGPT feedback on text revisions, with participants revising their drafts without direct interaction with the chatbot. Study 2 allowed free interaction with ChatGPT, supplemented by stimulated recall interviews to explore students’ perceptions of its utility. In both studies, text quality was assessed across organization, understanding, argument quality, and mechanics, while qualitative data, including chatbot interactions and revisions, were analyzed using Strobl et al.’s (2024) adapted framework and inductive coding.Results revealed significant improvements in text quality in both studies (Study 1: t(7)=-3.69, p

Unpacking Academic Writing as a multidimensional concept through a systematic literature review

Keywords
academic writing;research methodology;writing models;writing theory
Domain
Higher Education

Abstract

(see file)The rise of generative AI highlights the need for a clear conceptualization of writing and its role in knowledge development, particularly within university contexts. The concept of academic writing often remains implicit and poorly understood. Students associate academic writing primarily with formal language and disciplinary jargon, whereas teachers place greater emphasis on knowledge construction, textual organization, and integration of sources. Given that academic writing functions as a key indicator of students’ progress, clarification of the concept academic writing is necessary. Given its complex, implicit, and multidimensional nature, academic writing can be approached from multiple perspectives, conceptualized through four interrelated dimensions: product, process, person, and practice. Academic writing as a product emphasizes textual features of a ‘good’ academic texts.[1] The process dimension frames academic writing as a goal-directed, and cognitively demanding activity that goes beyond producing text, involving planning, revising, source-synthesis and knowledge crafting.[2] This complex process is shaped by writers’ personal characteristics, including motivation and affect. Writing also occurs within specific social contexts[3], such as disciplinary- or institutional communities[4]. This review addresses the conceptualization of academic writing from these four dimensions of academic writing. This review was conducted using Scopus, ERIC, and Web of Science. After screening and quality assessment, 651 studies were included, which were thematically coded. The results underscore academic writing as a multidimensional and transformative practice. Studies adopting a product perspective emphasize precision, conciseness, and writer–reader relationships, particularly through discipline-specific language, stance, and Voice. Process-oriented studies conceptualize academic writing as recursive and complex, emphasizing source integration. Person-focused research foregrounds writer identity and writing beliefs, while practice-oriented studies stress the role of disciplinary and institutional contexts in defining “good writing.” Concomitantly, the review reveals systematic biases, including the predominance of writing in English. In the context of generative AI, this underscores the need to reconceptualize academic writing in universities, with greater emphasis on creativity and knowledge-crafting rather than formulaic text production. [1] Aull & Lancaster, 2014; Biber et al., 2020; Staples et al., 2016 [2] Badley, 2009; Bereiter & Scardamalia, 1987; Chau et al., 2022; Kellogg, 2008. [3] Canagarajah, 2002; Graham, 2018 [4] Durrant, 2015; Hyland, 2008

“Writing in Spanish: Research, Practice, and the Generative AI Challenge”

Presenting author
Galan, Rosa M , ITAM, Mexico
Keywords
academic writing;education;evaluation and assessment of writing competence;professional writing
Domain
Higher Education

Abstract

What happens when thirty years of teaching writing in Spanish meet the disruptive force of generative AI?The relationship between research and teaching in an institutional writing program in the disciplines — serving hundreds of students — is undeniable. On the one hand, the program’s design and its specific interventions are expected to be grounded in theory and evidence. On the other hand, students’ texts, opinions, and evaluations constitute a valuable source of research. However, this relationship does not remain static: it evolves over time, shaped by generational and technological changes, by new research, and, most notably, by the emergence of generative artificial intelligence since 2022.This presentation will share the 30-year experience of Instituto Tecnológico Autónomo de México (ITAM), a Mexican university, in teaching academic and professional writing. Mainly, it will describe Es ITAM, a tiered scaffolding institutional writing program at the undergraduate level spanning 14 disciplines and based on research, in which all students participate from entry to graduation. Its main purpose is to help university students develop solid written communication skills, both in the academic and professional fields.The program consists of four moments of systematic intervention distributed in semesters 1, 3, 5 and 7, in which writing in traditional and digital formats is worked on. The program is based on three main functions: writing to learn, writing to argue and writing to disseminate specialized knowledge. In 2025, Es ITAM comprises a total of 34 subjects, 32 of which are taken together with other curricular subjects, taught by professors with specific training in 16 different university disciplines, such as Economics, Applied Mathematics, Political Science, Law, Data Science and various engineering disciplines, among others. The theoretical frameworks that informed its design and those currently under review will be discussed. Furthermore, the presentation will reflect on moments of disruption and uncertainty the program has faced and will outline the research it has generated.