Creating Course Materials with AI

What Materials Can AI Help Create?

Modern LLM-based AI tools can assist in drafting or brainstorming almost any kind of text-based course content. Here are some of the course materials educators are already creating using generative AI:

• Case Studies: AI can develop hypothetical scenarios or real-world examples to illustrate concepts and engage students in critical thinking.
• Lecture Slide Content: AI tools can generate slide decks based on a given topic or outline, incorporating key points, visuals, and examples to enhance presentations.
• Reading Lists: AI can suggest relevant articles, books, and resources for students to explore, helping instructors curate comprehensive reading lists.

Practical Guides

Case Studies

Lecture Slide Content

Reading Lists

Need to put together a list of readings or resources on a topic? AI can suggest books, articles, or materials that might fit your course. Caution: It may recommend some well-known works, but always double-check references because ChatGPT might invent citations or sources that sound real but aren’t.¹ When used carefully, it can help brainstorm relevant authors or keywords for you to search.

How to prompt: Clearly state the topic, the level of depth, and the type of sources you want. It helps to mention a few examples or constraints (e.g., recent research papers, classic textbooks, diversity of authors, etc.) to guide the AI.

1. Specify the scope: Start with a prompt like: “Suggest a reading list for a graduate-level course on Climate Change Policy. Include 5-7 key sources: a mix of seminal books or papers and recent articles. Provide the title, author, and a one-line description of each.” The model will return a list of titles with short descriptions.
2. Check for accuracy: Immediately verify the suggestions. ChatGPT may produce plausible-sounding titles that are not real or not exactly on target. Cross-check any citations in your library database or Google Scholar. It’s known that ChatGPT can hallucinate references, so treat its output as leads, not gospel. Often, the AI will include some genuine classics or well-known authors mixed with a few fabricated ones. Identify which are real. If uncertain, you can even ask the model: “Are these real publications? Verify the reference for X.” (Though it might not always admit fakes, so external verification is key.)
3. Refine or fill gaps: If the AI missed important topics or perspectives, prompt it again: “Also include a resource on the economics of climate policy in developing countries.” Or “Add an open-access report that students can read online.” You can iteratively ask for more until you have a well-rounded list. If you want diversity, you might say: “Ensure at least two authors from different regions or a female scholar’s work is included.” The AI can sometimes incorporate such criteria.
4. Get summaries (optional): To help you decide on or present these readings, you might ask the AI to summarize or compare them. e.g., “Provide a 2-sentence summary for each of the above sources, highlighting how it contributes to climate policy discussions.” This can generate quick annotations for your reading list handout, which you should verify and polish.

By using AI for reading lists, you brainstorm a broad set of resources quickly. Just remain vigilant about factual accuracy – always double-check that books/articles exist as described. Use AI to get ideas and then locate the actual sources via your library or reliable search. This approach saves time in curating materials but keeps scholarly integrity intact.

What Needs to be Considered

When using generative AI to develop teaching materials, instructors must take full responsibility for the content they create. This means carefully reviewing all AI-generated materials to ensure accuracy, check for potential biases, and verify that the content meets the specific educational goals of the course. AI tools can provide helpful starting points and suggestions, but they are not infallible sources of information. Instructors need to critically examine and modify the materials, drawing on their professional expertise and understanding of their students’ needs.

Transparency is crucial when incorporating AI into teaching preparation. Instructors should openly communicate with students about their use of AI tools, explaining how and why these technologies are being used in course development. This approach helps build trust, demonstrates academic integrity, and provides an opportunity to discuss the responsible use of emerging technologies. By carefully curating and personalizing AI-generated content, instructors can leverage these tools effectively while maintaining the essential human element that makes education meaningful and engaging.

Footnotes & References