Application of Retrieval-Augmented Generation (RAG) Systems in Software Engineering Education: An Approach Based on Generative AI and DevOps
Year: 2025
Type: article
Study design: Systematic Review
Abstract: This paper presents a systematic literature review of the application of retrieval-augmented generation (RAG) systems in educational settings, with a focus on teaching software engineering and related computing disciplines. Drawing on case studies, academic experiments, and surveys of teachers and students, it provides an overview of the current landscape, highlighting perceptions, reported effectiveness, and the technology’s impact in academia. Based on an analysis of 71 selected scientific papers, the review synthesises evidence on the extent to which RAG systems mitigate hallucinations and improve human–AI interaction. In addition, it suggests that many approaches discussed across studies could be strategically aligned with the integration of DevOps practices and RAG, enhancing their use through automation, continuous improvement, and the agile adoption of technologies within educational processes.
Authors: Yazmin Valeria Valeria Morales, Blanca Dina Valenzuela Robles, René Santaolaya Salgado, Juan Gabriel González Serna, Noé Alejandro Castro Sánchez, Mirna Ariadna Muñoz Mata
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4415089320