Understanding User Prompting Behavior in Generative AI: A Component Analysis

ABSTRACT Generative AI (GenAI), as exemplified by ChatGPT, is transforming the way people seek information and interact with information systems and resources. This study investigates users' prompt formulation behavior through a longitudinal observation of experienced ChatGPT users. Extending prior research on prompt engineering, this study introduces the IIOC (Input‐Instruction‐Output‐Context) framework, delineating four core components: input, instruction, output, and context. The findings reveal that users have a strong preference for simple and direct prompt, with Single‐Component prompts accounting for 43.8% of all prompts. Dual‐Component combinations constitute 38.2%, with Input + Instruction (20.2%) being the most frequent pattern. Only 18.0% of prompts involve Multi‐Component combinations, indicating that complex prompt formulations are infrequent in typical user interactions. The findings also offer practical insights for user‐centered AI design by emphasizing the instruction, input, and output components that address users' core needs.