Generative Language Models and their Influence on Undergraduate Education. A Systematic Review of the Literature

Abstract

In recent years, generative language models such as ChatGPT, Bing Chat, Gemini, Claude and Monica have been integrated into the academic environment of universities. These technologies are commonly used in academic writing, text writing and data exploration. Their constant presence in coursework has raised concerns about their true effect on fostering autonomous learning. This skill, which allows students to manage knowledge autonomously and issue their own criteria, is crucial in university education. However, whether these tools favor or hinder this process remains a matter of debate. Faced with this gap, this study suggests an exhaustive analysis that gathers the most relevant advances in this area. To achieve this, a systematic search method is suggested that relies on recognized academic databases and precise selection criteria. In addition to collecting existing information, the main goal is to examine it in depth in order to understand the ways in which the scientific community discusses this topic. This research, in addition to establishing a solid foundation for future research, seeks to guide educators and institutional leaders who are determining the most effective way to employ. By better understanding how these tools influence student autonomy, it will be possible to propose more responsible and effective ways of integrating them into the educational process. This review will make it possible to recognize the true scope of generative models in university education and to propose strategies that strengthen autonomy without relying exclusively on these technological tools.