TITLE:
Leveraging Artificial Intelligence in Outcome-Based Education: A Case Study of Undergraduate Auditing Curriculum
AUTHORS:
Yuanyuan Cao, Yitao Liu, Jinwen Lai
KEYWORDS:
Artificial Intelligence, OBE Concept, Undergraduate Auditing Curriculum
JOURNAL NAME:
Advances in Applied Sociology,
Vol.15 No.2,
February
24,
2025
ABSTRACT: This study explores the integration of Artificial Intelligence (AI) within the Outcome-Based Education (OBE) framework in undergraduate auditing courses. AI plays a pivotal role in responding to the evolving needs of the auditing profession by processing data from various sources, including recruitment platforms and industry reports. This data-driven approach facilitates the development of precise, measurable learning outcomes and course objectives, aligned with core competencies in financial auditing, IT auditing, risk management, and global auditing standards. In the curriculum design process, AI contributes to creating a holistic educational framework that incorporates knowledge, skills, and values, ensuring students not only gain theoretical insights but also practical expertise and ethical awareness. AI enhances the teaching and learning experience by supporting personalized pre-class preparation, fostering active in-class participation, and enabling timely, constructive post-class feedback. Through dynamic case generation and individualized learning pathways, AI cultivates a student-centered learning environment. Additionally, AI plays a crucial role in assessing learning outcomes and optimizing feedback mechanisms. By automating exam question generation, grading, and offering personalized learning suggestions, AI empowers instructors to adjust their teaching strategies based on real-time data, fostering continuous improvement and student progress. The findings suggest that the AI-enhanced OBE model significantly outperforms traditional OBE approaches, particularly in improving student performance and increasing the proportion of high-achieving students. This highlights AI’s potential to enhance both teaching quality and academic outcomes. The study advocates for the widespread adoption of AI technologies in higher education, particularly in specialized fields like auditing, to create intelligent, personalized learning environments that better meet market demands and optimize educational outcomes.