2025 ASEE Annual Conference & Exposition

Artificial intelligence (AI) literacy has become increasingly essential across academic disciplines as AI technologies continue to advance rapidly. However, there is little literature on the impact of different educational approaches on AI literacy among female undergraduate students. This study assessed AI literacy among 16 female undergraduate students from various academic backgrounds in Singapore and compared the effectiveness of two learning approaches: a technical skills course focused on programming and algorithms, and a concept-driven course that emphasizes real-world applications and ethical considerations. Participants from the engineering, business, and humanities disciplines were recruited from multiple university departments and randomly assigned to either of the courses. Using qualitative data from semi-structured interviews, the study investigated the unique strengths and challenges that these students faced from AI-driven education. The results suggest that the concept-driven course supports non-technical students, by enhancing their understanding and engagement, while the technical course was more effective for those with prior technical experience. These findings highlight the need for inclusive, tailored AI education strategies to support the diverse learning needs of female students in Singapore. The impact of different educational approaches on AI literacy, particularly among undergraduate students from diverse gender and academic backgrounds, remains underexplored.