A phenomenographic approach to students’ conceptions of learning artificial intelligence (AI) in secondary schools
Abstract
AI education for K-12 students is an emerging necessity, and considering students’ perspectives when developing effective AI education curricula in K-12 settings is essential. Few studies investigated secondary students’ conceptions of learning AI. Phenomenography is an empirical research method widely used to understand students’ conceptions of learning new phenomena. Therefore, we investigated students’ conceptions of learning AI using a phenomenographic approach. 88 secondary school students in Hong Kong were invited to participate in an interview after implementing an AI curriculum in two batches. Six categories of students’ conceptions were identified: (1) gaining awareness, (2) acquiring knowledge, (3) satisfying interest, (4) considering social impacts, (5) improving self-competency, and (6) seeing in a new way. The hierarchical relationships of the concepts were organized as an outcome space. The space shows a range of reproductive to constructivist conceptions and offers an understanding of how students perceive AI education through their learning experience. Theoretical, empirical, and practical implications are suggested for future AI education, providing insights for educators and policymakers to enhance curriculum alignment with students’ goals and promote general AI education for K-12 students.
Authors: Tianle Dong, King Woon Yau, Ching Sing Chai, Thomas K. F. Chiu, Helen Meng, Irwin King, Savio W.H. Wong, Yeung Yam
Published in: Education and Information Technologies (2025)