Bridging the AI Usage-Application Gap: Empowering Higher Education Lecturer Performance Through Dynamic Digital Capabilities

Sugeng Widodo; Arif Tirtana

doi:10.62775/edukasia.v7i2.2201

Authors

Sugeng Widodo Universitas Bhinneka Nusantara
Arif Tirtana Universitas Bhinneka Nusantara https://orcid.org/0000-0002-4289-3535

DOI:

https://doi.org/10.62775/edukasia.v7i2.2201

Keywords:

AI Usage, Knowledge Acquisition, Knowledge Application, Lecturer Performance

Abstract

Although knowledge acquisition is widely assumed to translate directly into knowledge application, prior research has rarely examined why this transfer often fails in AI-supported academic settings, leaving a theoretical gap regarding the mechanisms that connect the two processes. This study aims to analyze the influence of artificial intelligence (AI) usage on lecturer performance, considering the roles of knowledge acquisition, knowledge application, and the moderating effect of AI literacy. A quantitative approach was employed using Structural Equation Modeling (SEM) based on Partial Least Squares (PLS). The respondents consisted of 351 lecturers from private universities in Malang City, selected using the Slovin formula. The results show that AI usage has a significant positive effect on knowledge acquisition, knowledge application, and lecturer performance. Furthermore, AI literacy significantly moderates the relationship between AI usage and both knowledge-related variables, indicating that AI literacy plays a critical role in optimizing the use of AI in academic settings. However, knowledge acquisition does not have a direct effect on knowledge application, suggesting a gap between gaining and applying knowledge; this unexpected result implies that the acquisition-application transfer is not automatic and instead depends on enabling conditions such as practical training, institutional support, and lecturers' confidence in translating AI-derived knowledge into practice. On the other hand, both knowledge acquisition and knowledge application significantly influence lecturer performance. These findings highlight the importance of enhancing AI literacy and adopting integrative strategies to support digital transformation in higher education.

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