Identifying Secondary School Students' Patterns in Prompting Generative Artificial Intelligence in Ai Education
Abstract
This study explores the components of prompts generated by secondary school students when interacting with Generative AI (GenAI) chatbots in an AI education context. By analyzing the interaction logs between students and GenAI chatbots, this study identified and examined 6 components in students' prompts, separately “Focus”, “Verb”, “Persona”, “Context”, “Audience”, and “Constraints”. The results reveal students predominantly emphasized the components of “Focus” and “Verb” while displaying comparatively less attention to the other components. Through cluster analysis, the study categorizes students' prompts into five patterns, each reflecting different component strategies in prompt engineering. These findings enhance the understanding of students' interaction with GenAI chatbots and provide support for designing GenAIassisted education curricula, helping educators better comprehend students' epistemic and behavioral characteristics when interacting with GenAI, thereby optimizing teaching methods and course content.
Authors: Tianle DONG, King Woon Yau, Ching Sing Chai, Thomas K. F. Chiu, Helen M. L. Meng, Irwin King, Savio W.H. Wong, Yeung YAM
Published in: International Symposium on Educational Technology (2025)