The Relationship between Career Anxiety and Digital Competence with Students' Self-Efficacy in the Era of Automation and Artificial Intelligence - Isna Winarni; Erwanto Erwanto; Ira Hidayati (MASI Mandiri Edukasi, 2026)
The rapid development of automation and artificial intelligence has reshaped workplace demands, requiring final-year students to develop strong psychological readiness and digital competence. These changes can lead to career anxiety, which may undermine students’ self-efficacy. This study aimed to examine the relationships among career anxiety, digital competence, and students’ self-efficacy in the era of automation and AI. Using a quantitative correlational design with purposive sampling, 100 final-year students in Bandar Lampung participated in the study. Data were collected using three 4-point Likert scales: the Self-Efficacy Scale, the Career Anxiety Scale, and the Digital Competence Scale, with Cronbach’s alpha coefficients of 0.82, 0.79, and 0.84, respectively. Data analysis employed Pearson correlation and multiple linear regression using SPSS. The findings showed that career anxiety was significantly related to self-efficacy (r = 0.432, p < 0.001), while digital competence demonstrated a stronger correlation (r = 0.649, p < 0.001). Regression results indicated that both variables jointly influenced self-efficacy (F = 43.813, p < 0.001), contributing 47.5% to its variance, with digital competence being the most dominant predictor (β = 0.569). These findings support Social Cognitive Career Theory, which highlights that both psychological and technical factors Influence self-efficacy development. Therefore, universities should implement integrated strategies to strengthen students’ digital competence while mitigating career anxiety, thereby enhancing their confidence and readiness for future work environments.