Whether we realize it or not, artificial intelligence has become part of our everyday lives. Tools such as ChatGPT, Google Gemini, Claude, Perplexity, and many others, are helping us save time, solve problems, and enhance our creativity. As with any other tool, the more skilled we are at using A.I. effectively, the better our results will be. The acronyms below will help you craft more useful prompts and choose the A.I. tools best suited to your needs.
Remember! It's essential to verify and think critically about A.I. generated results. For help with this, see Acronyms for Evaluating Information.
For a wealth of additional information on artificial intelligence, visit Keeping Up With A.I.: Assorted Resources for College Educators and A.I. for Students.
Click each acronym to see a more detailed explanation.
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| Professor Leo S. Lo explains his CLEAR technique for prompt engineering in this detailed video: CLEARer Dialogues with AI: Unpacking Prompt Engineering for Librarians. For a handy guide to the CLEAR acronym, see Georgetown University's How To Craft Prompts |
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| Professor Adrian J. Wallbank recommends TAP & TASTE, a two step approach to prompt engineering for ChatGPT. Step one, TAP, guides your input to ensure an effective prompt. Step two, TASTE, helps you to evaluate the output and fine-tune your results. | |
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| Data scientist Sheila Teo won Singapore's GPT-4 Prompt Engineering competition with her COSTAR acronym. For a simplified explanation, see Unlocking the Power of COSTAR Prompt Engineering |
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| RAG is a framework that enhances the quality of AI-generated outputs by incorporating factual information from external sources rather than relying solely on pre-trained internal knowledge. For this reason, a tool that employs RAG may be a better choice when using AI for research purposes. To learn more, see Considering RAG When Evaluating Generative AI Tools. |
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