Using Generative AI Effectively

To learn to use Generative AI effectively, you must learn to prompt it effectively. An ineffective prompt costs just as much energy as an effective one.

To prompt effectively, consider using the CLEAR framework (Lo, 2023). The CLEAR framework can be a “scaffold for devising effective prompts for AI language models, combining precision and creativity, science, and art” (Lo, 2023, p. 208).

CLEAR stands for:

• Concise
• Logical
• Explicit
• Adaptive
• Reflective

Concise

Clear and precise prompts guide the AI model’s understanding, leading to a more relevant response.

Note: Limiting each prompt to one request or question is recommended to not overwhelm the tool. Remember, it is still just a machine!

Logical

Providing context within prompts helps the AI model create meaningful generated output.

Note: To provide context, try defining the role you would like the AI tool to assume or describe your role or level of knowledge. For example:

• You are a first-year computer science student.
• Act as an expert in programming languages.
• Assume I am 10 years old.
• Explain the concept of loops in programming languages.

Explicit

Including a specific structure or style in your prompt may assist the AI model in meeting user expectations in terms of the format and length of the generated responses.

Note: To help you get more accurate results, consider specifying the following in your prompts:

• Background information related to the topic (what AI can base its response on)
• Length of response (number of sentences, paragraphs, words, or characters)
• Format (a list, paragraph, chart)
• Structure (essay, blog post, poem)
• Style (formal or informal)
• Target audience (who this is intended for)
• Examples (provide an example of what you are looking for)

Westling (2023) sums up these details into the following AI prompt formula:

[Deliverable specifics] + [Voice] + [Objective] + [Ideal format]

Adaptive

Experiment with general and then more specific questions or statements to assist the Al model in generating a response that matches the desired output.

Reflective

Evaluate and improve the accuracy, coherence, and utility of the generated responses. For example, after receiving a final set of responses, tally how many, what kind, and how the prompts were adapted to achieve the desired result.

Note: Use the “chain of thought” technique to increase response accuracy, e.g. by using prompts like “Work on this problem step-by-step” or “Are you sure?” (Chen et al., 2023).

Meta-Prompting

Another technique to improve your prompt writing is using meta-prompting techniques, which can help students determine what they need to learn when they are not sure.

For example: “I want to learn about computer programming, but I don’t know where to start. Can you ask some questions to help you figure out where I need to start and what questions I need to ask first?”

Additional Resources

Vanderbilt University offers a free Coursera course on prompt engineering called “Prompt Engineering for ChatGPT.”

References

Chen, J., Chen, L., Huang, H., & Zhou, T. (2023). When do you need chain-of-thought prompting for ChatGPT? arXiv. https://doi.org/10.48550/arxiv.2304.03262

Lo, L. S. (2023). The art and science of prompt engineering: A new literacy in the information age. Internet Reference Services Quarterly, 27(4), 203-210. https://doi.org/10.1080/10875301.2023.2227621

Westling, M. (2023). 5 strategies for teaching AI literacy to students. Course Hero. https://facultyclub.coursehero.com/teaching-with-technology/5-strategies-for-teaching-ai-literacy-to-students/

Attributions

“Using Generative AI Effectively” by Nancy Bray, Introduction to Academic Writing, University of Alberta, is licensed under CC BY-NC 4.0 and was adapted from the following source:

• “Maximizing learning with effective GenAI prompt writing” by Pletnyova, A., PhD, Anselmo, L., MEd, and Keyhani, M., PhD, University of Calgary. Taylor Institute for Teaching and Learning is licensed under CC BY-NC-SA 4.0