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Generative AI, such as ChatGPT, produces personalized and contextually relevant content based on user prompts (inputs provided by users). These prompts act as the primary form of interaction between users and AI models, making their quality essential for generating the most relevant outputs. The process of writing, refining, and optimizing prompts, known as prompt engineering, is key to obtaining high-quality desired outputs from generative AI. For educators, proficiency in prompt engineering is crucial for effective interaction with AI as it enhances efficiency and produces the most relevant information. In this paper, we introduce practical strategies for prompt engineering for educators: (a) include essential components, including Persona, Aim, Recipients, Theme, and Structure (PARTS); (b) develop prompts using Concise, Logical, Explicit, Adaptive, and Restrictive (CLEAR) languages; (c) evaluate output and refine prompts: Rephrase key words, Experiment with context and examples, Feedback loop, Inquiry questions, Navigate by iterations, Evaluate and verify outputs (REFINE); and (d) apply with accountability. Examples for special educators and online resources are included.
Park et al. (Thu,) studied this question.