Shaping learning performance through artificial intelligence capability: Do cognitive competence, self-efficacy, creativity, and self-learning competence mediate the relationship?

Over the last few years, discussion among academicians and policymakers on the role of artificial intelligence (AI) technologies in shaping students’ learning performance (LP) has significantly increased. Hence, the study aims to examine the influence of artificial intelligence capability (AIC) on LP. Additionally, the study investigates the mediating role of cognitive competence (CC), self-efficacy (SE), creativity (CR), and self-learning competence (SLC) in the relationship between AIC and LP. A survey method was employed to collect primary data from 416 students of higher education in the Delhi-NCR region. Furthermore, partial least square structural equation modeling (PLS-SEM) was used to test the study’s hypotheses. The study reveals that SLC has a strongest impact on LP, followed by CC, AIC, SE, and CR. Furthermore, the study’s outcomes delineate that CC, SE, CR, and SLC establish complementary partial mediation in a relationship between AIC and LP. The study offers valuable insights to students, educators, higher education institutions, and policymakers and enhances their knowledge base on the determinants of students’ LP. Additionally, the study suggests policy interventions for various stakeholders to improve students’ LP. The study is an inaugural attempt to investigate the influence of AIC on higher education students’ LP in an emerging economy India. Moreover, the study is the first of its kind to investigate the impact of AIC on LP in the presence of CC, SE, CR, and SLC.