The impact of generative AI on academic reading and writing: a synthesis of recent evidence (2023-2025)

Aránzazu Sanz Tejeda^1*Juana Celia Domínguez-Oller²Josep Maria Baldaquí-Escandell³Raquel Gómez-Díaz⁴Araceli García-Rodríguez⁴

• ¹University of Castilla-La Mancha, Ciudad Real, Spain
• ²Universidad de Almeria, Almería, Spain
• ³Universitat d'Alacant, Sant Vicent del Raspeig, Spain
• ⁴Universidad de Salamanca, Salamanca, Spain

Introduction: The aim of this systematic review is to examine the scientific literature published on digital reading and writing in higher education within the field of social sciences, assisted by generative artificial intelligence. Method: The PRISMA methodology and the SALSA Framework were applied, based on a bibliographic search conducted in the Scopus and Web of Science databases. Journal articles that explicitly addressed the established topic, published between 1 January 2023 and 7 March 2025, in open access, in Spanish or English, and within the field of Social Sciences, were included. After a rigorous screening and selection process, a final sample of 136 articles was compiled and used as the basis for the study. Results: The findings indicate that the reviewed research employs a range of methodologies, encompassing quantitative (surveys, experimental studies, psychometric evaluations), qualitative (case studies, semi-structured interviews, thematic analysis), and mixed-method approaches. The results also reveal a clear trend towards the integration of artificial intelligence tools –particularly ChatGPT– into academic writing processes. A significant improvement is observed in the quality of students' texts, especially regarding coherence, discursive organisation, lexical richness, and argumentation. Furthermore, the role of AI in formative feedback, idea generation, paraphrasing, and fostering student autonomy in self-editing their texts is highlighted. The research also identifies key challenges, such as students' overreliance on AI, diminished metacognitive engagement, and ethical dilemmas related to plagiarism and authorship. Discussion: The emergence of AI in higher education is transforming teaching and learning processes, creating opportunities for personalisation and enhanced support in academic writing. However, the scientific literature also exposes tensions between its potential benefits and associated risks, such as student dependency, loss of critical thinking, and ethical concerns regarding authorship and plagiarism. These findings call for a rethinking of pedagogical, assessment, and institutional practices, as well as the development of critical and digital literacy skills among both teachers and students.