The Influence of Artificial Intelligence Utilization, Self-Efficacy, and Learning Innovation on University Students’ Work Productivity

Abstract

The development of digital technology has encouraged students to employ Artificial Intelligence (AI) to support their academic activities. However, differences in individuals’ technological management skills, self-efficacy levels, and learning creativity lead to variations in students’ academic work productivity. This study aims to analyze the influence of AI utilization, self-efficacy, and learning innovation on students’ academic work productivity. The research problem focuses on the extent to which these three variables contribute, either partially or simultaneously, to enhancing students’ academic work productivity in the digital era. This study employed a quantitative survey approach with a sample of 201 university students, approximately 96.5% of whom are enrolled in Islamic higher education institutions, selected through purposive sampling. Data were collected using a five-point Likert-scale questionnaire and analyzed using multiple linear regression. The findings indicate that AI utilization (sig.=0.024), self-efficacy (sig.=0.000), and learning innovation (sig.=0.000) have a significant partial influence on students’ productivity, with learning innovation being the most dominant variable. Simultaneously, the three variables exert a significant influence (F=94.425; sig.=0.000) and explain 59% of the variance in work productivity (R²=0.590). These findings provide novel empirical evidence that learning innovation exerts a more dominant influence than AI utilization alone, underscoring the importance of integrating technological adoption with self-efficacy and innovative learning practices to enhance university students’ academic work productivity, particularly within Islamic higher education contexts.