How to Write Prompts for AI: A College Student’s Guide

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Time to Read: 10 minutes

Did you know that how you talk to AI matters a lot? It’s not as simple as just asking it a question – at least not if you want high quality responses.

This guide is designed specifically for college students, offering clear, simple instructions on how to craft prompts that will give you consistently useful responses from AI. Let’s dive into the essentials, simplifying the process with practical tips and the structured ACTOR framework developed by GradSimple.

Basics of Writing AI Prompts

Crafting effective prompts for AI is both an art and a science. You’ll need to learn how to communicate your needs clearly and concisely to get the best possible output from AI tools like ChatGPT. Here’s how to approach writing AI prompts:

Understanding Your AI Companion

Before diving into prompt writing, recognize that AI models process information and generate responses based on patterns learned from vast datasets. Your goal is to guide the AI with clear, direct prompts.

Approaching AI interactions conversationally, rather than as mere transactions, transforms the dynamic from simply asking and receiving to engaging in a meaningful dialogue. This conversational approach mirrors human learning interactions—rich with questions, clarifications, and explorations—that naturally foster a deeper understanding. Even ChatGPT thinks so!

PRO TIP: Many users make the mistake of treating AI purely as a Q&A machine. It’s far more effective to approach your interactions in a conversational way, much like you would with another human. 

Clarity is Key

Start with clear, straightforward language. Ambiguity can lead to unexpected results, so specify exactly what you’re asking for. If you’re seeking an explanation on a topic, instead of saying “Tell me about quantum physics,” try “Explain the basic principles of quantum physics in simple terms.”

Be Specific

The more specific your prompt, the more tailored the AI’s response will be. For research-related prompts, instead of a broad request like “How do I write a research paper?”, specify the subject, “What are the steps to write a research paper on renewable energy technologies?”

AI Prompt Examples for Beginners

Prompt for Summarizing Information: “Summarize the key points of the latest IPCC report on climate change, focusing on impacts on global temperatures and sea levels.”

Prompt for Generating Ideas: “Generate a list of five innovative project ideas for a final year computer science student, focusing on sustainable technologies.”

Prompt for Explaining Concepts: “Explain the concept of machine learning to someone unfamiliar with computer science, using analogies and simple language.”

Tips for Improvement

Letting AI “Think” in Prompt Engineering

When we talk about letting AI like ChatGPT “think out loud,” it’s not about AI thinking in the human sense but rather about making its processing steps explicit in its response.

An easy way to let AI “think” out loud is to get it to “reflect” on its answers. In doing so, you encourage a level of self-assessment that can reveal the reasoning behind its conclusions. This practice is proven to lead to better quality responses.

Getting ChatGPT to “reflect” on its answers lead to a 14.58% increase in the accuracy of its responses when tasked with answering complex reasoning questions.

Geng et al. 2023

For instance, after receiving an initial explanation, prompting the AI with, “Reflect on why this solution is optimal,” or “Can you explain how you got to this conclusion and what makes it better than other alternatives?” can lead to richer, more nuanced insights. This step is especially important for academic prompts where understanding the ‘how’ and ‘why’ is as important as the answer itself, fostering a deeper engagement with the material.

Iterate and Refine

Don’t expect perfection on the first try. Use the AI’s responses to refine your prompts, adding more detail or adjusting the focus as needed. View each interaction as part of an ongoing conversation. If an AI’s response opens new points of interest or raises further questions, don’t hesitate to inquire about them in subsequent prompts. This iterative process mimics the natural way we deepen our understanding through discussion.

Use Feedback Loops

After receiving a response, if something isn’t clear or you think the AI can provide more information, it is good practice to ask follow-up questions. For instance, “Based on your previous response, can you dive deeper into the implications of rising sea levels on coastal cities?” Feedback for AI is important because it helps in refining the accuracy and relevance of its responses, ensuring they meet the users’ needs more effectively.

PRO TIP: You can ask ChatGPT for feedback on your prompts by explicitly requesting insights on how to improve them for clearer, more effective communication, or how to better structure your questions to receive the most relevant and accurate responses.

Explore Different Phrasings

Sometimes, rephrasing a question can lead to better responses. If the initial prompt doesn’t yield the desired result, try approaching the question from a different angle. It’s similar to how you would ask for clarification when in conversation with a human. 

Prompt Engineering Framework: ACTOR

The ACTOR framework is a structured approach for how to write prompts for AI, designed by GradSimple for college students. It ensures clarity, context, and purpose in your interactions. Each component—Assume, Context, Task, Objective, Result—plays a critical role in crafting effective prompts that yield relevant and actionable AI responses. Let’s delve into what each alphabet represents and its importance, using the context of a college student seeking help from an AI math tutor.

Assume (A) – Define the Role

Importance: Specifying a role for the AI sets the tone and direction of the response. It helps the AI adopt a specific perspective or expertise, aligning its responses with the expected knowledge base or skill set.

Example: “Assume you’re my math tutor.” This instruction cues the AI to adopt the role of a tutor, focusing its responses on teaching and explaining math concepts rather than merely providing information.

Context (C) – Provide Background

Importance: Context enriches the prompt with relevant background information, enabling the AI to tailor its responses more accurately to the user’s situation. It includes details about the user’s current understanding, specific challenges, and any relevant circumstances.

Example: “I’m struggling with understanding integrals in Calculus II, particularly with techniques such as substitution and integration by parts.” This context gives the AI a clear understanding of the student’s current level and specific areas of difficulty, allowing for a more focused and helpful response.

Task (T) – Specify the Action

Importance: Defining the task directs the AI on what exactly needs to be done. It transforms the context and role into actionable items, specifying the type of assistance or information required.

Example: “Explain the fundamental principles of integration and provide step-by-step examples of each technique.” Here, the task is clear—educate on integration principles with practical examples, guiding the AI’s output towards educational support.

Objective (O) – State the Purpose

Importance: Articulating the objective clarifies the purpose behind the prompt, guiding the AI to understand the ultimate goal of the task. It ensures the response is not just accurate but also aligned with the user’s needs.

Example: “The objective is to enhance my comprehension of these concepts to prepare for my upcoming midterm exam.” This statement informs the AI of the need for a comprehensive understanding that aids exam preparation, focusing the response on effective learning outcomes.

Result (R) – Describe the Desired Outcome

Importance: Detailing the desired outcome in terms of format, structure, or content ensures that the AI’s response meets the user’s expectations. It adds a layer of specificity regarding how the information should be presented.

Example: “Provide a structured study guide with examples and practice problems, organized from basic to more complex applications.” This request makes it clear that the student is looking for a well-organized educational resource, specifying the form and structure of the AI’s output.

Challenges and Solutions in Prompt Engineering

Challenge: Difficulty in Formulating Effective Prompts

Crafting prompts that yield the desired AI response often involves trial and error. New users may find it challenging to balance specificity with clarity, leading to outputs that don’t fully meet their needs.

Solution: Embrace the iterative nature of prompt engineering. Start with any prompt and refine it based on AI’s responses. For instance, if an initial prompt about “the history of the internet” generates too broad an overview, narrow it down with, “Focus on the development of internet protocols in the 1980s.” This process of adjustment helps hone your prompt-crafting skills over time.

Challenge: Vague or Broad Responses

Sometimes, AI might provide responses that are too general or broad, lacking the depth or specificity needed for academic work.

Solution: Enhance prompt specificity by including detailed questions and context. For example, instead of asking, “What are renewable energy sources?” specify, “List renewable energy sources suitable for urban environments and discuss their efficiency and implementation challenges.”

Challenge: AI “Hallucinations” or Misinformation

AI models, including ChatGPT, can sometimes “hallucinate” information—producing plausible but incorrect or misleading data.

AI models generate responses based on statistical likelihoods—patterns learned from vast datasets, rather than accessing real-time, verified facts.

Solution: Combat this by cross-referencing AI responses with credible sources. For research-intensive tasks, follow up with, “Provide sources or evidence to support your claims on the impact of climate change on polar bear populations.”

Challenge: Misalignment with Academic Standards

AI-generated answers might not always adhere to the specific standards or depth required for college assignments.

Solution: Explicitly incorporate academic guidelines into your prompts. For a literature review, instead of a vague request, specify, “Summarize key findings on behavioral economics from articles published in the last five years, adhering to Chicago style formatting.” This directs the AI to produce content that aligns with academic conventions.

Additional Example: When requesting help with essay writing, instruct, “Construct an argumentative essay outline on ‘The Role of Technology in Education,’ ensuring each point is supported by evidence from scholarly articles, formatted according to MLA guidelines.” This prompt ensures that the AI structures its response within an academic framework.

Challenge: AI Getting “Distracted” or Derailed

Sometimes, certain elements within a prompt can lead AI down an unintended path, producing responses that veer off-topic or focus on less relevant aspects.

Solution: Be mindful of the specificity and focus of your prompts. If an initial request for information about “sustainable practices in urban planning” leads to a generalized discussion on sustainability, refine the prompt to “Identify specific sustainable practices in urban planning that reduce carbon footprint, focusing on case studies from European cities.” This directs the AI to remain focused on the core topic and avoid tangential content.

How to Write Prompts for AI: Concluding Thoughts

Using our ACTOR framework is a good starting point for crafting effective prompts that produce good responses. By employing clear, specific, and engaging dialogue with AI, you can unlock a dynamic educational tool, transforming your academic research, project ideation, and complex concept learning.

For more AI insights, tips, and job search guidance, subscribe to GradSimple. Be the first to receive our latest resources and updates, tailored to help you level up.

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