Innovative management and educational models for college student veterans: a case study on intelligent technology integration in higher education

Abstract

This study takes the Nanning campus of Guilin University of Technology as an example to explore the application of intelligent learning technologies (e.g., AI-driven personalized recommendation systems, VR simulation training, and learning analytics) in the education and management of student veterans—a special group in higher education. By constructing personalized learning paths and adaptive teaching environments, this research aims to address the challenges of academic adaptation, social integration, and identity transition faced by student veterans, thereby enhancing their sense of belonging, learning motivation, and academic performance. Based on the Technology Acceptance Model (TAM) and Self-Determination Theory (SDT) as the core theoretical frameworks, this study verifies the facilitating effect of blended learning (integrating online intelligent platforms with offline military theory courses) on the academic adaptation and career development of veteran college students. Quantitative results showed that after implementing the intelligent learning model, the course completion rate of student veterans increased by 30% (from 65% to 85%), and the average GPA rose by 0.7 (from 2.8 to 3.5); 85% of participants reported improved learning efficiency, and 76% acknowledged enhanced interest in professional courses via VR military simulation. This study contributes to the field of Educational Technology Integration and Inclusive Education for Special Groups in higher education by providing a replicable framework for leveraging intelligent technologies to support the development of student veterans. The findings also offer insights for addressing the educational needs of other non-traditional student groups (e.g., adult returning students, cross-major learners), thereby promoting educational equity and quality improvement in diverse higher education contexts.