Design and Case Analysis of AI Liberal Arts Curriculum by Level with Engaged Learning : With a Focus on AI and Machine Learning

With the advent of the Fourth Industrial Revolution, artificial intelligence (AI) is heralding significant changes in industries and the economy. These changes transcend specific academic disciplines, positioning AI as essential knowledge for everyone. Consequently, the importance of formulating AI-related policies and education is increasingly emphasized worldwide. Additionally, as the significance of data-driven decision-making grows, the demand for skills such as data analysis, machine learning, and deep learning is rising. Universities should teach these skills to students to equip them with practical abilities. However, most universities only distinguish between IT majors and non-majors, offering the same curriculum to both groups. This approach does not adequately consider students' diverse learning backgrounds and levels, leading to various problems and difficulties in course content and teaching methods. To address these issues, it is crucial to consider students' diversity and provide them with the autonomy to choose courses that match their levels and interests. This selective, level-based learning approach is expected to result in high satisfaction with AI-related courses, regardless of prior AI learning experience. In this study, we proposed a revised AI liberal arts curriculum comprising three detailed courses: AI and Data Foundations, AI and Machine Learning, and AI Development and Practice. This redesigned curriculum allows students to choose personalized learning pathways and implements an Engaged Learning (EL) model. The study analyzed satisfaction levels regarding course content, evaluation methods, and the EL model by dividing students into two groups based on their prior AI learning experience. The findings confirmed that allowing students to select courses aligned with their levels and interests is more important than their prior AI knowledge. Additionally, implementing the Engaged Learning model proved effective for course delivery. This level-based AI liberal arts curriculum is expected to be extended and applied to other academic subjects as well.