Learning Chemistry with Generative Artificial Intelligence: A Phenomenological Study of Secondary School Students’ Experiences in Bayelsa State, Nigeria

Generative artificial intelligence offers new opportunities for supporting Chemistry learning, but accessible explanations may not translate into independent conceptual understanding. This paper examined experiences of understanding Chemistry concepts, perceptions of usefulness and challenges associated with generative artificial intelligence within a secondary school context in Bayelsa State, Nigeria. A qualitative analysis informed by an interpretative phenomenological approach was undertaken using ten participants. Analysis involved examining individual accounts, identifying experiential meanings and comparing patterns across cases. The accounts portrayed conceptual understanding as developing through manageable explanations, recognition of errors, comparison with other resources, and independent practice. However, apparent clarity sometimes coexisted with difficulties applying knowledge to unfamiliar problems. Perceived usefulness centred on repeated clarification without embarrassment, support outside classroom instruction, revision activities and alternative explanations. Challenges included shared devices, data costs, unreliable connectivity, unfamiliar terminology, uncertainty about response accuracy, difficulty formulating questions and the temptation to copy solutions. The analysis suggests that generative artificial intelligence may serve as a supplementary resource when combined with teacher guidance, textbooks, practical demonstrations, and independent problem-solving. Faculty of Education, Niger Delta University, Wilberforce Island, Bayelsa State