AI in Service-Learning: Addressing Challenges and Unlocking Opportunities in Vietnamese Higher Education

The integration of Artificial Intelligence (AI) into service-learning represents a significant transformation in higher education, offering innovative ways to enhance student engagement, experiential learning, and instructional efficiency. While AI has been increasingly utilized in various educational contexts, its application within service-learning frameworks remains underexplored, particularly in Vietnam. This study conducts a systematic literature review (SLR) to analyze existing research on the opportunities and challenges of AI-driven service-learning, focusing on its implications for Vietnamese higher education institutions. Adopting a structured SLR methodology, this research examines peer-reviewed studies published between 2014 and 2024, sourced from Scopus, Web of Science, IEEE, Springer, and Taylor & Francis. The selected literature is categorized based on key themes, including AI applications in service learning, institutional barriers to AI adoption, faculty readiness, and policy considerations. Through a critical synthesis of existing studies, this review identifies both the transformative potential and the persistent challenges associated with AI integration in community-based learning environments. The findings indicate that AI can facilitate personalized learning experiences, automate assessment processes, and improve real-time feedback mechanisms, thereby enriching the service-learning experience. However, institutional inertia, digital infrastructure limitations, and faculty skepticism present significant barriers to AI adoption. Additionally, the absence of standardized frameworks for implementing AI in service-learning programs hinders its widespread integration into university curricula. This study concludes that for AI to be effectively incorporated into service-learning in Vietnam, universities must develop comprehensive institutional policies, invest in faculty development, and establish adaptable pedagogical frameworks. By synthesizing current research, this study contributes to a deeper understanding of AI’s role in service-learning, providing practical insights for policymakers and educators seeking to navigate digital transformation in higher education.