Welcome to Module 2 of the AI Academic Accelerator! In the first module we built a foundation by exploring what artificial intelligence is, key terms that define the field, how AI systems learn from data and generate content, and the historical forces that have shaped this technology. Now we turn our attention to something more practical: how to communicate with AI systems effectively and how to leverage them as creative partners when designing courses.

This module starts with an exploration of prompt engineering. A prompt is the input you provide to a language model or generative system. Well-crafted prompts can yield clear answers, thoughtful explanations, lesson plan outlines and even creative brainstorming ideas. Poorly written prompts can lead to confusion or irrelevant outputs. You will learn techniques for writing prompts that provide context, direct the model toward the desired outcome, and include constraints that improve relevance. We will discuss question formats, anchor phrases and follow-up prompts that help you refine the system’s responses. Through examples you will see how small adjustments in wording can drastically change the quality of the output.

Once you have a grasp of prompting, we will explore how AI can help you co-develop the building blocks of a course. The module covers how to use generative models to draft syllabus statements, craft clear learning objectives, brainstorm weekly topics, and sketch assessment strategies. These activities are not about letting the AI take over your expertise; rather they are about using AI as a collaborative partner that suggests ideas and helps you think through options. You will learn how to evaluate AI-generated suggestions against educational best practices and your own course goals. The module will also address ethical considerations such as ensuring that AI-generated content aligns with institutional policies and academic integrity.

Throughout the module you will work with a variety of tools including chat-based models like ChatGPT and Claude as well as specialized assistants for curriculum design. We will provide a directory of tools with descriptions, links and cost models so you can decide which options suit your needs. Examples and templates will illustrate how to adapt prompts to different disciplines and student populations. Each topic page concludes with reflective questions to help you integrate what you’ve learned into your teaching practice.

By the end of this module you will be able to craft effective prompts, use AI to brainstorm and organize course material, and understand the strengths and limits of AI-assisted course design. This knowledge will prepare you for the next module on the ethics of AI in higher education, where we will examine bias, data privacy, and responsible use in depth. Let’s dive in and start designing courses with our new AI partners!

As you engage with the material, remember that the skills developed here build directly upon the foundational concepts you learned in Module 1. Effective prompts rely on understanding how AI models interpret language, and designing course materials with AI requires a clear vision of your learning outcomes. The more precise your goals, the more you can harness AI to expand and refine them. Feel free to experiment, iterate, and share your findings with peers. This collaborative approach will ensure that you not only master the mechanics of prompt engineering but also cultivate a thoughtful teaching practice that enhances student learning.