Four Methods I Enhanced my AI Command Composition
In the realm of education, the art of writing AI prompts has become increasingly important. With the help of AI-in-education expert, Graham Clay, I've learned to approach the task with a fresh perspective - starting with the assumption that the problem lies with the prompt, not the AI model.
This newfound understanding has opened up a world of possibilities. By applying the CRE framework (Concise, Relevant, and Explicit), I've been able to guide AI responses precisely and purposefully, tailored to educational goals.
The CRE framework encourages prompts to be concise, relevant, and explicit, reducing ambiguity and guiding the AI clearly toward the task. Iterative prompt refinement is essential, starting with a general prompt and progressively narrowing focus or adding details to improve relevance and depth.
I've found the final part of the prompt writing process, experimentation and iteration, to be crucial. If a prompt doesn't work at first, it may require adjustments, tweaks, or the use of existing prompt templates for better outputs.
Learning from others’ prompts and frameworks, like CLEAR (Concise, Logical, Explicit, Adaptive, Reflective) or PREP, has also played a significant role in developing better prompt engineering skills.
Advanced techniques include chain-of-thought prompting, meta-prompting, and layering context over multiple steps to deepen the AI’s output. Using examples or few-shot prompting (providing model examples within the prompt) guides tone and content style.
To save time, I've turned to resources like the Common Sense Media course and the AI For Education website, which offer libraries of AI prompts for various education needs. A helpful prompt for creating a rubric, for instance, is: "You are an expert teacher and curriculum writer, skilled in creating assessments and evaluating student work. Your task is to create a rubric for my [GRADE LEVEL AND SUBJECT] class studying [TOPIC]. My students are completing [ASSIGNMENT TITLE], in which they [ASSIGNMENT DESCRIPTION]. Format the rubric as a chart and include a 5-point scale."
Embracing the iterative part of the process has helped me get more out of AI for specific tasks and better understand its strengths, weaknesses, and limitations. By assuming the prompt needs work and continuously refining it, I've been able to improve my AI prompt writing skills, resulting in more effective AI outputs.
In conclusion, effective prompt writing for education relies on clear, specific instructions, iterative improvement, leveraging teaching expertise to scaffold content, and learning frameworks and strategies developed within the AI and education community. This journey of understanding AI prompt writing is not only fascinating but also crucial in mentoring students in using AI effectively and giving a sense of how students might use AI to cheat.
- The process of creating AI prompts can significantly benefit education, as shown when applying frameworks like CRE to guide responses accurately towards educational goals.
- Iterative prompt refinement is essential to improve the quality of AI outputs, starting with a general prompt and progressively narrowing focus or adding details to increase relevance and depth.
- Learning from other prompts and frameworks, such as CLEAR or PREP, can enhance prompt engineering skills, helping to create more effective AI outputs in education.
- Effective prompt writing in education should include clear, specific instructions, leveraging teaching expertise to scaffold content, iterative improvement, and a sense of how students might use AI to both learn and cheat, making it a crucial skill for both education and self-development.
