Artificial intelligence (AI) has led to numerous changes and to a growing interest for its application in education and in the university setting (Rose, 2023). More specifically, there has been an increased attention to generative AI models, such as GPT-4, to support academic writing, which is considered a key skill to enable students to exercise their critical thinking skills and demonstrate their knowledge (Kim et al., 2024).
As a matter of fact, the integration of generative AI enables to improve written production as it provides feedback and suggestions for improvements and enhance the clarity of the content by rephrasing sentences and phrases. Moreover, it supports metacognitive skills and self-assessment, encouraging students to reflect on their writing process (Nguyen et al., 2024). However, it also raises significant concerns on its impact on students' creativity and originality, especially as the writing process is unique to each individual and it is influenced by their own characteristics, background and prior knowledge. These factors are essential to produce good-quality texts (Beauvais, Olive, and Passerault 2011). Thus, the challenge is to integrate AI as a support rather than a substitute for creativity and critical thinking (Castiglione, 2023).
To address this matter, this study examines the impact of the integration of AI into a university course by analyzing the students' writing processes in two phases: initially, the students are required to produce different types of academic texts using exclusively their own knowledge and receiving peer-to-peer and teacher feedback; afterwards, they will have access to advanced AI tools to complete their assignments. Productions from the two phases will be compared to assess improvements in the quality of the texts and efficient revision strategies and writing strategies according to coherence, clarity and analytical depth.
Data collection will include questionnaires and interviews on the students' writing experience, focusing on their perceptions on the strengths and weaknesses of AI tools and their acceptance of AI. Special attention will be paid to the production strategies adopted, analyzing how they may evolve with the AI support. The results of this study aims to contribute to a better understanding of the impact of AI on academic writing, highlighting the progresses in text quality and the development of metacognitive skills and different production strategies.
In conclusion, this talk aims to promote the integration of this groundbreaking technology into practice by investigating its potential in improving academic writing and exploring how it can affect the students' writing processes.
References:
Beauvais, C., Olive, T., & Passerault, J. (2011). Why are some texts good and others not? Relationship between text quality and management of the writing processes. Journal of Educational Psychology, 103(2), 415–428. https://doi.org/10.1037/a0022545
Castiglione, A. (2023). Per una Pedagogia della Singolarità: intelligenze artificiali e tecnologie digitali a supporto dell'educazione alla scrittura, un quasi-esperimento con il modello linguistico GPT-3. Graphos. Rivista internazionale di pedagogia e didattica della scrittura, 3, 87-105.
Kim, J., Yu, S., Detrick, R., & Li, N. (2024). Exploring students' perspectives on Generative AI-assisted academic writing. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12878-7
Nguyen, A., Hong, Y., Dang, B., & Huang, X. (2024). Human-AI collaboration patterns in AI-assisted academic writing. Studies in Higher Education, 0(0), 1–18. https://doi.org/10.1080/03075079.2024.2323593
Rose, R. (2023), ChatGpt in Higher Education, University of North Florida Digital Pressbooks.
| Type : | : | Communication |
| Thématiques | : | Axe 2 : La place de l’IA dans les activités humaines |
| PDF version | : |  PDF version |
