RESEARCH ON THE INTEGRATION OF ARTIFICIAL INTELLIGENCE IN MBA LITERATURE SEARCH COURSE INSTRUCTION - Xiaofeng Zhang; Siqi Zhang (Acta Informatica Malaysia)
This paper examines the current state and challenges of integrating artificial intelligence (AI) in the instruction of MBA literature search courses. The analysis identifies the low degree of technology integration, varying acceptability among faculty and students, and difficulties in teaching quality assessment as the primary issues. The low integration is attributed to insufficient technological maturity, while the differences in acceptability are due to outdated concepts and an inadequate training system. The challenges in assessing teaching quality stem from an imperfect management mechanism. The paper proposes strategies to enhance technology integration and customization, improve cognitive understanding and training levels among faculty and students, and refine the teaching quality assessment system. These strategies aim to improve the compatibility of technological tools with the educational environment, strengthen the ability of faculty and students to understand and apply new technologies, and establish an effective evaluation system to measure teaching effectiveness. Implementing these strategies can promote the application of AI in MBA literature search courses, enhancing teaching quality and the student learning experience.