Finding meaning in the AI era: How AI self-efficacy shapes doctoral persistence
Bigraf Triangga, I. Wayan Edi ArsawanPurpose
Finding meaning in the artificial intelligence (AI) era is no longer a philosophical exercise – it is a survival strategy for doctoral students. This study examines how AI self-efficacy shapes doctoral persistence through the mediating role of doctoral meaning.
Design/methodology/approach
Grounded in social cognitive career theory, meaning theory and persistence theory, this study examined four AI self-efficacy dimensions alongside search for meaning, presence of meaning and doctoral persistence. Survey data from 372 doctoral students in East Java were analyzed using partial least squares structural equation modeling. Multi-group analysis tested invariance across gender, discipline and doctoral stage.
Findings
Both search for meaning and presence of meaning predicted doctoral persistence more strongly than any AI self-efficacy dimension. Among the four dimensions, only psychological comfort with AI-shaped persistence, operating entirely through presence of meaning (indirect-only mediation), while perceived AI usefulness exerted a negative direct effect on persistence. Multi-group analysis showed comfort fostered meaning-seeking among male students but slightly inhibited it among female students, while the mechanism held across discipline and stage.
Research limitations/implications
The cross-sectional design limits causal inference, and data relied on self-reported measures without the adviser's perspective. Small R2 values for the meaning constructs indicate that doctoral meaning is shaped by multiple determinants beyond AI self-efficacy. Future research should incorporate longitudinal designs, multi-informant approaches and cross-cultural validation to strengthen the meaning-mediated persistence framework.
Practical implications
Doctoral programs should cultivate students' psychological comfort with AI, not just technical skill, since comfort predicts the presence of meaning that sustains persistence. Institutions should embed reflective practices, purpose-oriented mentoring and responsible AI use into doctoral education.
Originality/value
This study advances doctoral persistence research by conceptualizing doctoral meaning as the mechanism that transforms AI self-efficacy into persistence. It introduces meaning-mediated persistence, showing that technological capability sustains doctoral completion only when it is converted into personal meaning.