As faculty that teach technical disciplines, you are in a unique position. You aren’t just figuring out how to use Generative AI; you are teaching the students who will build, deploy, and critically evaluate these tools for years to come.
The challenge is twofold:
How can you leverage AI to improve your own teaching (e.g., create coding examples, debug assignments, or design better projects)?
How can you effectively integrate AI into your curriculum as a core competency (e.g., teach prompt engineering, model limitations, and AI ethics)?
The internet is flooded with AI resources, and it’s impossible to sift through them all. This post is a practical, curated guide to help you find the most useful resources for your courses without the noise.
Start with IU: Key Local Resources
Before diving into the wider web, start with the excellent resources available directly from IU. These provide the foundational context and policies for our community.
Generative AI 101 Faculty Resources
Description: An overview of the GenAI 101 Course available to all at IU. Also includes a syllabus insert that can be used to promote the course to students.
Kelley School of Business “AI Playbook”
Description: A “living guide” developed by the Kelley School for faculty on the use of generative AI in teaching, grading, and research. It outlines shared values and emphasizes that faculty expertise remains central.
When to use: When you want faculty-facing guidance on when and how to use generative AI in assessments, course design, and feedback workflows.
A Quick Starting Point: Three Actionable Resources
If you want to branch out, here are three high-value resources to review in 10 minutes or less.
For Your Curriculum: Teach CS with AI: Resource Hub for Computer Science Educators
What it is: A hub specifically for integrating AI into CS courses. It includes lesson plans, project ideas, and pedagogical strategies for teaching AI in computing.
When to use: When you’re not just using AI, but actively teaching AI concepts, ethics, or applications within a CS or Informatics course.
For Your Pedagogy: Harvard University:“Teaching with Gen-AI” resources
What it is: High-level guidance from Harvard on course design, with excellent case studies and strategies for handling risks like hallucinations and superficial reasoning.
When to use: Use this before the semester starts. It’s perfect for designing your syllabus, setting AI policies, and building responsible use guidelines into your course from day one.
For Your Students (and You): AI for Education: “Effective Prompting for Educators”
What it is: A focused guide on how to write better prompts. It includes frameworks (like the “5 S Framework”) that are perfect for teaching students a structured approach to “prompt engineering.”
When to use: When you want to move students beyond simple “ask-and-receive” and teach them how to partner with AI to get better, more reliable, and more complex results.
The Deep Dive: A Curated Resource Library
For those with more time, here is a more comprehensive list organized by task.
1. How to Use AI in Your Classroom (Pedagogy & Assignments)
Derek Bok Center for Teaching and Learning (Harvard) : “Teaching in the Age of AI”
Description: A collection highlighting definitions, pedagogical questions, and course design implications.
When to use: When you want concrete assignment ideas or sample activities to see how others have used AI in their teaching.
One Useful Thing: Blog post “15 Times to Use AI and 5 Not To”
Description: Easy-to-digest guidance on where AI is helpful in learning (quantity-based tasks, translation) and where it isn’t (deep learning, high-accuracy needs).
When to use: When you are deciding which parts of your course are appropriate for AI and which should remain human-only.
Syllabi Policies for AI Generative Tools:
Description: A collection of sample policies from other educators to help you develop your own.
When to use: When you are writing your syllabus and need clear language about how AI tools are (or aren’t) allowed in student work.
2. Helping Students (and You) Get Better at Prompting
AI for Education: Prompt Library
Description: A comprehensive, searchable collection of ready-to-use prompts and templates specifically for educators.
When to use: When you need quick, plug-and-play prompt templates for lesson plans, student tasks, or administrative work.
More Useful Things — Prompt Repository for Educators
Description: A repository of prompts for instructor aids and student exercises, curated by researchers Ethan and Lilach Mollick.
When to use: When you want tested, inspiring prompt sets, especially for idea generation or in-class activities.
Description: Anthropic’s (maker of Claude) public library of optimized prompts for business, creative, and general tasks.
When to use: When you want to show students (or yourself) “what good prompting looks like” from an industry leader.
3. How to Teach AI in Your CS/InF Courses (Curriculum & Literacy)
Teach CS with AI: Resource Hub for Computer Science Educators
Description: A hub dedicated to integrating AI topics, tools, and teaching strategies in CS courses.
When to use: Use when teaching a CS course and you want to integrate AI content (topics, labs, projects) directly.
metaLAB at Harvard: The AI Pedagogy Project / AI Guide
Description: A curated site with assignments and projects to integrate AI in pedagogical practice, focused on critical thinking.
When to use: When you are designing a module on AI literacy, critical AI thinking, or assessing students’ interaction with AI tools.
Ideeas Lab: Teaching & AI resources
Description: A resource hub with teaching materials and tools, particularly aimed at engineering and technical fields.
When to use: When you want resources specifically tailored for engineering domains that integrate AI in assignments.
AI for Education: “Generative AI Critical Analysis Activities
Description: Classroom activities to help students critically examine AI outputs, ethics, and limitations.
When to use: When you want to design modules around AI ethics or have students evaluate AI rather than simply use it.
4. Taking it Further: Building Your Own AI Tools
HBSP: “How to Create Custom AI Chatbots that Enrich Your Classroom”
Description: A walk-through article for educators on designing custom AI chatbots for classroom engagement.
When to use: Use when planning to design or integrate a custom AI chatbot (e.g., as a teaching assistant, for Q&A) in your class.
OpenAI: “A Practical Guide to Building Agents” (PDF Business/Technical Guide)
Description: A detailed technical guide from OpenAI on building AI agents, including design, steps, and deployment.
When to use: Use when you or your students are planning to build or deploy an AI agent as part of a capstone or advanced project.
5. Professional Development & Staying Current
IBM Skills Build for Educators: College Educators resources
Description: A professional development site offering modules and training materials to build AI fluency and integrate digital skills into teaching.
When to use: When you want a structured PD path for yourself or want to build a course around AI literacy and workforce readiness.
University of Maine: LearnWithAI initiative
Description: A practical, “how-to” oriented site for faculty on integrating AI into courses.
When to use: Use when you want a site focused on faculty development and practical course integration.
Future-Cymbal Notion Page: Shared collection of AI-Teaching Resources
Description: A collaboratively curated Notion page of ideas, links, frameworks on AI in education; less “formal guide,” more open resource aggregation
When to use: Use when you want to browse a broad, ever-updating set of ideas rather than a polished handbook.
Description: It collects a wide variety of resources for educators around generative AI in the classroom — such as sample syllabus statements, institutional policy templates, teaching ideas, and faculty development materials.
When to use: When you are designing or revising your course syllabus and need clear language about how you will (or won’t) allow AI tools in student work.
Newsletters for Staying Current:
The Rundown -Daily newsletter summarizing AI news across research, policy, and industry.
The Neuron – Broad coverage of emerging AI trends and commentary, often with education-adjacent insights.
The Batch – Weekly deep dives into AI research, tools, and development—ideal for those following the tech side.
The Algorithmic Bridge | Alberto Romero – Thoughtful essays analyzing AI’s social, ethical, and educational impact.
Everyday AI Newsletter – Daily newsletter (and accompanying podcast) aimed at making AI accessible to “everyday people” whether educators, professionals, or non-tech specialists.
Conclusion: Start Small, Start Now
You don’t need to redesign your entire curriculum overnight. The best approach is to start small.
Pick one thing to try this month. It could be using a prompt library to help you write a coding assignment, adapting a syllabus policy, or introducing one critical analysis activity in a senior seminar. By experimenting now, you’ll be better prepared to lead your students in this new, AI-driven landscape.
Did I miss a great resource? Leave a comment and let me know!