Exploring the Role of Generative <scp>AI</scp> in Developing Student Skills in Higher Education: A Systematic Literature Review

Abstract

ABSTRACT The emergence of generative AI (GenAI) has accelerated pedagogical innovation and reshaped pathways for student skills development in higher education. Among them, ChatGPT has gained widespread adoption, yet the mechanism through which GenAI contributes to student skills formation remains insufficiently understood. To address this gap, this study employs a systematic literature review of 99 empirical studies published between November 2022 and March 2025 across four major English‐language databases: Scopus, Web of Science, ERIC, and IEEE Xplore. The review follows PRISMA guidelines and aims to clarify methodology trends, thematic categories, and skills development. The findings reveal that current research on GenAI in education is primarily concentrated in China and the United States and primarily adopts experimental or mixed‐method designs. GenAI is conceptualised in six roles, namely, thinking mentor, writing assistant, learning companion, development coach, programming assistant, and creative generator. The research is mainly concentrated on four themes: cognitive skills and thinking skills development, academic writing and language performance enhancement, self‐regulated learning and pedagogical innovation, and the development of composite competencies and future readiness. This study uses the three‐stage coding method of grounded theory to systematically analyse the pathways through which GenAI interventions affect students' skills development in empirical studies. It then proposes a theoretical framework for students' skills development centred on the mechanisms of pedagogical innovation, learning support, and feedback regulation. The three subsystems in the framework work together to focus on developing four core skills: digital technology application skills, higher‐order thinking skills, and AI ethical and self‐directed learning skills. This study not only enriches the theoretical understanding of GenAI in educational contexts but also offers practical insights for reforming higher education systems toward skills‐oriented teaching.

Ähnliche Arbeiten