ChatGPT Prompting the Basics 

During interactions over the past year with language instructors in various venues, I have observed a trend with educators’ generative chat usage.  Instructors are aware of generative chat technologies such as ChatGPT and Microsoft Edge Copilot through mainstream media, social media, relatives, students, or their peers. However, few have gone beyond sampling these tools a few times with basic prompts out of personal curiosity or to commence using prompts for lesson preparation.  

Attempts at generating resources with a generative chat tool do not always result in usable content because instructors often give up after a few prompts.   They do not understand that creating suitable content is an iterative process that involves structure, a defined target, skill, and imagination.  In this post, I offer guidance for language educators trying to create content for instructional purposes through prompting generative chat tools.  

Achieving desired results with prompting 

To prompt generative chat tools to achieve desired results, understanding prompting basics is necessary. In this blog post, I will be referring to ChatGPT or Copilot as examples. Basic prompting elements include: 

  • a prompt, 
  • prompt attributes, and 
  • the response to a prompt 


The prompt is the main input provided by the user to ChatGPT or Copilot. It could be a query, a request for information, or a statement that requires a response. It can also be referred to as the question, request or statement.   

Prompt Attribute  

A prompt can be simple or complex.  Prompt complexity is crafted by combining prompt attributes with the simple prompt question. Prompt attributes refine the prompt, allowing ChatGPT or Copilot to include precision to ensure that enough detail is provided to create a relevant response. Prompt attributes may include the following and more: 

  • Context provides additional information about the topic, setting or any previous conversation that has taken place during the prompting session (see iterative prompting below). 
  • The tone and style of the prompt tailors the response to match your requirements, for example: formal, informal, inspirational, conversational, humorous, technical, persuasive, or intimate to name a few.   
  • Keywords can help generative chat tools to better understand a topic and improve the relevance of a response with enhanced precision, trigger specific knowledge, and respond to complex inquiries.  
  • Being precise and specifying a desired outcome of the conversation helps ChatGPT and Copilot give a response that meets the prompter’s expectations with less ambiguity which leads to fewer prompt exchanges, thus increasing session efficiency. 
  • Indicating an actor or role in your prompt substantially impacts a response by providing a specific expertise or perspective from which to generate content.  
  • Informing ChatGPT of the intended audience can profoundly alter the prompt response. 
  • Diversify prompts with a variety of specific question types.  Consider starting with an open-ended question followed by clarifying, more specific, comparative questions.  Scenario based or problem -solving questions can produce more detailed results.  In addition, prompts can be shaped to generate examples, models, and different perspectives. 

Prompt Response 

The response or answer to a prompt is the output based on the prompt and ChatGPT or Copilot’s understanding of the prompt. Prompts are questions or statements that guide generative chat tools to generate a response. The way a prompt is worded can greatly influence the type and quality of the response. A well-crafted prompt leads to a more accurate, relevant, and useful response.

Iterative Prompting 

Interactions with ChatGPT and Copilot can and in many cases should be iterative. Based on a response received, the next prompt can be refined to explore a topic more deeply or request clarification or further information.  This process can enhance the quality of the overall interaction, helping the generative chat tool produce a more relevant response, leading to a satisfactory result. 

Prompt Precision 

Ensure that your prompts are specific and clear This improves the generative chat tool’s comprehension of a prompt request. Vagueness or excessively broad questions may lead to ambiguous or off-target responses. Consider using plain language when prompting. 

Final thoughts 

This is not a comprehensive list of good prompting practices, but language educators can consider the tips in this post to improve their generative chat sessions to produce better learning resources and activities.  Do you have other tips or questions? Please respond below. 

Hi—I'm John Allan. I am an educator who works in the technology enhanced language learning field. I create online learning opportunities and mentor instructors on the Avenue project. I have experience teaching ESL and EFL in Canada and the Middle East. I hold an MSC in Computer Assisted Language learning, a M.Ed. in Distance Education, TESL B. Ed., a B.Ed. (OCT), and a variety of TESL relevant certifications from TESL Canada, TESL Ontario and the Ontario Ministry of Education. For more articles, learning objects, projects and blog links see


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