Beyond Performance: AI Psychological Empowerment in Cross-Cultural Education

Abstract

This study investigates artificial intelligence (AI) psychological empowerment in education, examining how AI tools enhance students' sense of competence, autonomy, and engagement beyond the effects of material empowerment (e.g., task performance improvements). Using a quasi-experimental design, we compared Chinese domestic students in China and Chinese international students in Australia to assess whether AI psychological empowerment is both tangible and more impactful than material empowerment. We highlight several nuanced ways AI fosters personal growth and self-perception. Our findings reveal that, while AI material empowerment is beneficial, psychological empowerment has a stronger influence on motivation and self-perception, particularly for international students compared to local students, despite both groups completing the same English writing task. These results suggest that AI's role in education extends beyond traditional material support, offering transformative psychological empowerment that enhances students' confidence in academic contexts. This empowerment reasonably translates into greater personal adaptability and, ultimately, personal growth. The study contributes to the growing literature on AI in education, providing insights for scholars, educators, and policymakers seeking to leverage AI for holistic student development. Notably, generative AI (GAI) emerges as a critical tool for cultural and linguistic adaptation, particularly for immigrant students navigating foreign academic systems. Furthermore, the psychological empowerment effects of GAI appear to be context-dependent, with stronger impacts observed in students facing greater cultural or linguistic barriers. These findings emphasize AI's potential to foster personal growth and resilience across diverse learning contexts. Finally, we recommend that educational policies and practices be tailored to leverage GAI for immigrant populations, paving the way for more equitable educational opportunities.

Received: 7 November 2024 | Revised: 28 February 2025| Accepted: 4 June 2025

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

The data that support this work are available upon reasonable request to the 

corresponding author.

Author Contribution Statement

Yingnan Shi: Conceptualization, Methodology, Formal analysis, Investigation, Writing - original draft, Writing - review & editing, Visualization. Astrid Tong Xu: Validation, Data curation, Writing - review & editing, Visualization.