University students’ reflections on academic writing with genAI

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University students’ reflections on academic writing with genAI

Type
Symposium
Keywords
academic writing;AI writing;Generative AI;writing tools and writing technology
Domain
Higher Education

Abstract

The aim of this symposium is to address and discuss undergraduate students’ reflections on academic writing with generative artificial intelligence (GenAI). Academic writing is central to studies in higher education, and since OpenAI’s launch of ChatGPT in November 2022, the possible potentials and challenges of using generative artificial intelligence (GenAI) technologies in writing have been increasingly discussed and explored across scientific fields (e.g., Khalifa & Albadawy, 2024; Nguyen, 2024). Previous research has shown that GenAI has been described in different ways; in addition to a text generator, also as an assistant, tutor, teacher, and conversation partner, which makes a difference for students’ performance and constitutes an affective support (Kim et al., 2025; Ou et al., 2024). Several studies have explored undergraduate students’ perceptions on GenAI in writing, soliciting responses through interviews and surveys (e.g., Kim et al., 2025; Ou et al., 2024). Adding to this body of work, the presentations in this symposium offer other perspectives on undergraduate students’ academic writing with GenAI, using various theoretical perspectives, research designs, and methods. First, focus lies on students’ peer-reflections on academic writing, where they discussed GenAI as part of their academic writing without being specifically asked about GenAI. Second, focus lies on students’ reflections on engaging in academic writing tasks using GenAI, more specifically, self-feedback scaffolding through GenAI in online writing tasks and GenAI as a tool for cognition when writing argumentative texts. Thus, the symposium adds to ongoing discussions of potentials, challenges, and dilemmas that GenAI technologies present for academic writing in higher education. ReferencesKhalifa, M., & Albadawy, M. (2024). Using artificial intelligence in academic writing and research: An essential productivity tool. Computer Methods and Programs in Biomedicine Update, 5, 100145. https://doi.org/10.1016/j.cmpbup.2024.100145Kim, J., Yu, S., Detrick, R., & Li, N. (2025). Exploring students’ perspectives on Generative AI-assisted academic writing. Education and Information Technologies, 30(1), 1265–1300. https://doi.org/10.1007/s10639-024-12878-7Nguyen, A., Hong, Y., Dang, B., & Huang, X. (2024). Human-AI collaboration patterns in AI-assisted academic writing. Studies in Higher Education, 49(5), 847–864. https://doi.org/10.1080/03075079.2024.2323593Ou, A. W., Stöhr, C., & Malmström, H. (2024). Academic communication with AI-powered language tools in higher education: From a post-humanist perspective. System, 121, 103225. https://doi.org/10.1016/j.system.2024.103225

Self-feedback scaffolding through AI in online writing tasks

Keywords
academic writing;feedback;Generative AI;writing tools and writing technology
Domain
Higher Education

Abstract

Students need to critically assess AI-generated feedback to avoid superficial learning (Bearman et al., 2024), particularly in writing processes where writing plays an epistemic role. A promising solution to enhance feedback practices with AI is to promote self-feedback processes. This is a process of cognitive change in which students generate new knowledge through comparing their current understanding or performance with external references, and its effectiveness relies on structured activities and scaffolding (Nicol, 2021). This study explores to what extent AI-supported self-feedback can effectively scaffold students’ writing in asynchronous environments. A total of 107 online students participated in a quasi-experiment. Students first completed an assignment. Immediately after submission, they accessed a timed online space. Following a reflective scaffolded process, students generated self-feedback while revising their initial assignment with AI insights. The quantitative analysis showed a significant improvement in students' scores from the first to the second submission (Z = -6.804; p < .001). Qualitative analyses of both students' interviews and writing reflections during the scaffolded process show that GenAI-mediated self-feedback is enacted through a set of recurrent actions. The reported self-feedback actions by students were: students primarily use GenAI to identify areas for improvement, revisit their understanding of key concepts, detect aspects they had overlooked, and connect their revisions to new knowledge. Interviews additionally reveal emergent topics that help to explain how students use GenAI. These include experimenting with prompting strategies to obtain more relevant feedback; directing corrections purposefully depending on their objectives; questioning GenAI’s reliability; experiencing uncertainty; and showing different levels of GenAI literacy. These results offer insights into the concrete mechanisms through which teachers can scaffold self-feedback process with GenIA in academic writing and contribute to the ongoing discussion on the potentials and dilemmas of GenAI in higher education. Bibliography Bearman, M., Tai, J., Dawson, P., Boud, D., & Ajjawi, R. (2024). Developing evaluative judgement for a time of generative artificial intelligence. Assessment & Evaluation in Higher Education, 49(6), 893–905. https://doi.org/10.1080/02602938.2024.2335321 Nicol, D. (2021). The power of internal feedback: Exploiting natural comparison processes. Assessment & Evaluation in higher education, 46(5), 756-778. https://doi.org/10.1080/02602938.2020.1823314

Students' reflections on using GenAI as a tool for cognition when writing an argumentative text

Keywords
academic writing;AI writing;Generative AI;writing tools and writing technology
Domain
Higher Education

Abstract

This study aimed to analyze undergraduate students’ perceptions of the usefulness of Copilot as a tool for cognition (Fuertes-Alpiste, 2024) when writing argumentative texts. From this perspective, students are encouraged to use it as a mediational tool that supports problem solving in writing, to find new ideas, reviewing their texts in terms of content and language conventions, or helping them check citation formats when writing an argumentative text based on sources.A total of 152 undergraduate students from two education-related degree programs participated in a didactic sequence that included reading multiple texts, whole-group discussions, and the use of instructional guides with examples on how to write an argumentative text and how to employ different prompts with Copilot for this purpose. Students completed a questionnaire both before and after the didactic sequence.In the final questionnaire, students responded to Likert-scale items addressing the perceived usefulness and limitations of Copilot in supporting task completion, as well as items related to potential technical issues encountered when using the tool. Students were also asked open-ended questions about how using Copilot influenced their writing process, including ways in which it was helpful, unhelpful, or may have affected their autonomy, and were invited to provide examples.Preliminary results indicate that students value Copilot primarily as a tool for identifying ideas, revising their written texts, and including references. However, they also acknowledge the risk of becoming overly dependent on the tool when producing written documents, which they perceive as a potential threat to their creativity. These results can shed light on how generative AI tools can afford writing processes when used as tools for cognition and not as a substitute of students' cognition, eliciting their writing affordances and associated critical thinking skills. ReferenceFuertes-Alpiste, M. (2024). Framing Generative AI applications as tools for cognition in education. Pixel-Bit. Revista De Medios Y Educación, 71, 42–57. https://doi.org/10.12795/pixelbit.107697

Students’ reflections on academic writing in higher education: GenAI as sociomaterial actor

Keywords
academic writing;AI writing;Generative AI;writing tools and writing technology
Domain
Higher Education

Abstract

This presentation addresses undergraduate students’ reflections on GenAI technologies and their role(s) in their academic writing, drawing from data from workshops with undergraduate students across scientific disciplines at a university in Finland. The study aims to explore how students conceptualize their academic writing in relation to GenAI technologies, drawing theoretically on sociomaterial frameworks using, for example, actor-network theory to understand writing as a process in which both human and non-human actors participate in shaping it (e.g., Clarke, 2002; Gourlay, 2015). The data encompasses audio-recorded conversations and mindmaps from four workshops (2,5 h each) with a total of 30 students in educational sciences, political science, and caring sciences. During the workshops, the students were tasked with mapping and discussing what they use in their academic writing, how, when, and why. No question was asked explicitly about GenAI. Nevertheless, the students discussed GenAI technologies in all workshops, sharing that they use various AI technologies, such as ChatGPT, co-pilot, and Gemini. Preliminary analyses indicate that the students use them, for example, as support when their writing processes become stalled, when needing to expand the amount of text or generate new perspectives, and to orient themselves in relevant literature. A prominent use of GenAI technologies is that they, in similar manners as for example dictionaries and thesauruses, can be used in the writing to adapt the text to the linguistic and stylistic norms that apply within their disciplines. As such, GenAI technologies often have, according to the students, other, more central functions than merely a text generator. This presentation will unfold the results of the study and discuss implications for writing with GenAI in higher education. ReferencesClarke, J. (2002). A new kind of symmetry: Actor-network theories and the new literacy studies. Studies in the Education of Adults, 34(2), 107–122. https://doi.org/10.1080/02660830.2002.11661465Gourlay, L. (2015). Posthuman texts: Nonhuman actors, mediators and the digital university. Social Semiotics, 25(4), 484–500. https://doi.org/10.1080/10350330.2015.1059578