Activity Designer

Use this tool to create a customized prompt for designing AI-integrated activities aligned with Bloom's Taxonomy and AI literacy competencies. Fill out the form below, and we'll generate a comprehensive prompt you can use with any generative AI tool to create pedagogically sound activities for your specific teaching context.

Before You Start

The more you share, the better the result. Only fields marked with * are required, but completing optional fields produces a sharper, more tailored prompt. Plan for 5–10 minutes in one sitting.
Don't include identifiable information about students. The prompt you generate will be pasted into an external AI tool of your choice. Avoid student names, ID numbers, specific grades, or any other identifiable details. Describe your students in general terms ("a class of 25 first-year students with mixed prior research experience") rather than specifics.
Your responses don't save automatically. If you close this tab or hit "back" before generating, you'll need to start over. After you generate, you can copy, download, or email the prompt to yourself.

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Course Information

This section establishes the teaching context — your discipline, your students, and how your course works — so AI can calibrate its suggestions to your actual classroom. Formal course numbers mean wildly different things at different institutions, so we lean on your qualitative description of what students can handle. The more specifically you describe who you're teaching, the better the generated activity will fit.

Instructional Context* What kind of teaching is this activity for? This helps shape what counts as realistic for time, assessment, and student preparation.

Discipline / Field* The broad academic area of your course.

Department or Program Optional, but useful for interdisciplinary programs, pre-professional tracks, or departments with distinctive approaches.

Course Name* The specific course you're teaching.

Course Description Optional, but this is where AI learns your teaching style.

Student Readiness & Context* Describe your students qualitatively: their academic maturity, what they can handle independently, typical workload expectations, class size, and anything distinctive (diverse backgrounds, specific learning needs, prior knowledge). This matters more than course numbers — it's what helps AI calibrate complexity, scaffolding, and length.

Course Level (quick reference) A rough category as a secondary reference point. Your qualitative description above matters more.

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Activity Details

This section defines what students will actually do. The more concretely you describe the assignment — its topic, format, length, and what you want students to walk away having learned — the better AI can propose an activity that fits. Just as important: tell AI which parts of the thinking must stay with the student. That's how you keep the human at the center of the learning.

Specific Topic or Unit* What specific topic, unit, or content area will this activity address?

Learning Goals* What should students know, be able to do, or think differently about after completing this activity? Formal learning objectives are welcome, but a list of target skills, concepts, and habits of mind works just as well.

Assignment Format & Specifications What will students produce? Include the format (paper, presentation, project, discussion, portfolio, etc.), length or scope, and any research or source requirements.

Time Available How much time — both in-class and out-of-class — is available for this activity?

Technology Access & Constraints What technology can students access? Any tools required, provided, or off-limits?

Protected Student Work (what must students do without AI?) Which parts of the thinking, writing, or decision-making must stay with the student? Naming this up front helps ensure AI enhances the learning rather than replacing it.

Assessment Preferences How would you like to assess student work? Include any grading approaches, rubrics, or reflection components you're considering.

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Activity Purpose

There's a meaningful difference between using AI as a tool to learn course content, making AI itself the subject of study, and asking students to critically examine how AI works. This choice shapes the entire activity — so pick the primary purpose, even if your activity touches more than one.

What is the primary purpose of AI in this activity?* Select the option that best describes AI's role. The generated prompt will help you think through whether and how secondary purposes fit in.

Learning course content with AI AI as a tool to support learning the course subject

Students use AI to help them understand, apply, or engage with course content. The focus stays on the discipline (biology, history, marketing, etc.), and AI is a means to that end.

Example: In a history course, students use AI to role-play a conversation with a historical figure, then critique the historical accuracy of the responses using primary sources.

Learning about AI AI literacy itself is the learning goal

Students build foundational understanding of how AI tools work, what they're good at, where they fail, and how to use them skillfully. The focus is on developing AI literacy as a transferable competency.

Example: Students test the same prompt across three different AI tools, document the variations in output, and develop a set of principles for when each tool is most useful.

Critically examining AI AI as the object of critical inquiry

Students investigate AI from a critical perspective — its biases, ethical dimensions, environmental impact, labor practices, or effects on society and the professions. The focus is on interrogating AI rather than using it.

Example: Students audit an AI image generator for demographic bias by running a standardized set of prompts, then write an analysis connecting their findings to course readings on algorithmic fairness.

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AI Literacy Framework

AI literacy isn't one skill — it's a cluster of competencies, from knowing which tool to use, to evaluating output, to understanding ethical and environmental implications. This section uses our adapted AI Literacy Framework (a revision of Dr. Kara Kennedy's 2023 framework) to help you pinpoint which competencies your activity should build. Choose one primary competency (the main one you want students to develop) and up to two secondary competencies that your activity will also touch. Focusing your choice makes the generated activity sharper than trying to address everything at once.

Which AI literacy competencies should this activity develop?* Select one Primary competency (required) and up to two Secondary competencies (optional). Click "Show details" on any competency to see what it includes.

1. Hardware & Software Choosing the right AI tool and understanding how it works

• Picking the right AI tool for the task
• Knowing how to access and use AI tools on your preferred device
• Understanding how Large Language Models (LLMs) work

2. Information & Data Literacy Retrieving, evaluating, and verifying AI-generated information

• Using AI to retrieve, analyze, and organize information
• Evaluating, verifying, and identifying AI output
• Understanding the current circumstances of the datasets used to train AI tools

3. Communication & Collaboration Working with AI thoughtfully and acknowledging its use

• Approaching prompt engineering as conversation
• Managing and sharing AI content responsibly
• Practicing transparency when using AI
• Using and talking about AI with others

4. Content Creation Creating, adapting, and questioning AI-generated content

• Using AI to create, curate, and adapt content
• Leveraging AI for multimedia content creation
• Staying aware of discourses about AI-generated content and human creativity

5. Safety & Ethics Risks, legal questions, wellbeing, and environmental impact

• Knowing the risks and liabilities of AI tools
• Understanding legal and ethical issues involving AI
• Protecting your wellbeing when using AI
• Assessing technology's environmental impact

6. Critical Thinking & Agency Managing the human-AI relationship and adapting as AI evolves

• Managing the AI-human relationship
• Evaluating how AI tools can perpetuate biases
• Solving problems using AI
• Adapting as AI tools evolve

7. Career Competencies Applying AI within a specific professional field

• Staying aware of emerging best practices and tools for AI in a specific field
• Understanding, evaluating, and creating AI content in a specific field
• Combining content competencies with AI literacy skills

Your Generated Prompt

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