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POLS 3700: Research Methods in Criminal Justice: Prompt Engineering

Prompt Engineering

What is prompt engineering?

"Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs)... Prompt engineering is the process of structuring text using tactics to get better results. Knowing the capabilities and limitations of a tool can help you receive more accurate and relevant responses."

Source: Prompt Engineering Guide (DAIR.AI):

Microsoft CoPilot. UGA has a campus-wide license for Microsoft CoPilot, which provides some great tips on the "art of prompts." Microsoft suggests including four elements in your prompts: the goal, context, expectations, and source.

Recommended Resources

CLEAR Framework for Prompt Engineering

The CLEAR Framework provides guidance for creating effective prompts. The following tips and examples are excerpted from the following article:  

Article Citation:  Lo, L. S. (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering. Journal of Academic Librarianship49(4), Article 102720. https://doi.org/10.1016/j.acalib.2023.102720.

Concise: brevity and clarity in prompts

Examples

  • Use a more concise and explicit prompt such as “Explain the process of photosynthesis and its significance” instead of “Can you provide me with a detailed explanation of the process of photosynthesis and its significance?”
  • Instead of requesting, “Please provide me with an extensive discussion on the factors that contributed to the economic growth of China during the last few decades”, use a concise prompt like, “Identify factors behind China's recent economic growth.”

Logical: structured and coherent prompts

Examples

  • “List the steps to write a research paper, beginning with selecting a topic and ending with proofreading the final draft” is a logically structured question.
  • A logically structured prompt could be, “Describe the steps in the scientific method, starting with forming a hypothesis and ending with drawing conclusions.”

Explicit:  clear output specifications

Examples

  • Instead of, “Tell me about the French Revolution,” an explicit prompt would be, “Provide a concise overview of the French Revolution, emphasizing its causes, major events, and consequences.”
  • Rather than prompting, “What are some renewable energy sources?”, opt for a more explicit version like, “Identify five renewable energy sources and explain how each works.”

Adaptive flexibility and customization in prompts

Examples

  • If an initial prompt such as “Discuss the impact of social media on mental health” elicits responses that are too general, consider a more focused and adaptable prompt such as “Examine the relationship between social media usage and anxiety in adolescents.”
  • If asking, “What are some ways to conserve water?” leads to generic responses, try a more targeted and adaptive prompt like, “List household practices for conserving water and their potential impact.”
  • If a prompt such as, “Describe the history of computers” yields too much information, use a more specific and adaptive prompt like, “Explain the development of personal computers from the 1970s to the 1990s.”

Reflective: continuous evaluation and improvement of prompts

Examples

  • After receiving AI-generated content on the benefits of a plant-based diet, evaluate the response's accuracy, relevance, and completeness. Use insights from the evaluation to refine future prompts, such as asking for more specific benefits or focusing on certain aspects of a plant-based diet.
  • After acquiring an AI-generated list of strategies for effective time management, evaluate the relevance and applicability of each strategy. Consider the target audience's needs, and use this information to tailor future prompts to generate content that better addresses specific challenges or contexts.