Since the launch of ChatGPT in November 2022, I have been immersed in studying generative artificial intelligence (GenAI) and its potential impact (positive and negative) on higher education. Obviously, given my position as the Academic Integrity Office Director at the University of California, San Diego, I am particularly interested in the impact that GenAI has, and will have, on academic integrity and have had to figure out how to answer questions from faculty on how to prevent cheating with GenAI, how to talk to students about academic integrity in the era of GenAI, and how to document cases of integrity violations involving GenAI.

However, those that know me and my writings, understand that I see academic integrity as a teaching and learning issue, not as a student conduct issue. So, my interests in GenAI go beyond its impact on student behaviour to its impact on teachers. And it is within that interest that I recently finished Dan Fitzpatrick’s (with Amanda Fox and Brad Weinstein) book “The AI Classroom: The Ultimate Guide to Artificial Intelligence in Education”. Even though the book was written with K-12 teachers in mind, I wanted to delve into it for two reasons: 1) K-12 teachers are trained to teach, and thus have a lot more pedagogical and assessment knowledge than do most HE teachers (which means we have a lot to learn from them); and 2) it was touted as a very practical book to enable teachers to go from zero to hero in their use of GenAI in education.

I was not disappointed. Many of the other books I’m reading (like Christian’s “The Alignment Problem” or “Rebooting AI: Building Artificial Intelligence We Can Trust” by Marcus & Davis) are theoretical or focused on building an understanding of GenAI and its broad implications for society. So, “The AI Classroom” provides a nice change of pace: practical, specific, illustrative, and encouraging.

After a quick backgrounder on Artificial Intelligence in Part I, Fitzpatrick and colleagues drop the reader in Part II directly into how to use GenAI to make teaching and teaching prep more efficient, as well as to make learning for the students more engaging and inclusive. Then, in Part III, the authors review current AI tools that can be used by teachers and students, from tools that serve as educational platforms to those that assist with research, converting text-to-audio (and image, and video, and 3D and code), and, of course, AI chatbots (other than ChatGPT). Finally, in Part IV, the authors walk us through what educational leaders need to think about and do in the face of the “AI Revolution” and they muse about the future of Artificial Intelligence and the future of education.

While the examples and illustrations are all geared to K-12 teachers, the key lessons are easily transferable to the higher education environment. Following are 3 highlights for higher education faculty that I took away from this book:

  1. “Outsource your doing, not your thinking.” (p. 33). When considering if and how GenAI should be used in your teaching, make a list of all of things you have to do on the route to enable actual engagement with your students in the learning environment. Craft learning objectives, design your lessons, create learning activities, develop assessments, evaluate assessments and provide feedback on student learning. GenAI can help you do all of these things. However, “outsource your doing, not your thinking” also provides guidance for faculty in thinking about when they should allow students to use GenAI in their learning. If students can outsource some of the doing behind learning and thinking (e.g., formatting citations; conducting research), then can we free up their minds for higher order thinking? And for those faculty worried that GenAI tools like ChatGPT will “hinder student development”, the authors argue that student “development is already hindered” by an educational system designed for a different world than the ones that students will inhabit as professionals (p. 47). The key is to figure out how we can “design learning…to ensure students’ knowledge and skills are developed” (p. 77). For me, this means figuring out how we can use GenAI to help us, or free up time to enable us, to asses process (the doing), rather than the product (e.g., the essay). We have relied on products for a long time in higher education, especially as we became more industralizd and routinized as our classes grew larger and larger. However, products are meant to be learning artifacts and so if the integrity of the learning artifact cannot be assured, then process is what we need to focus on.
  1. Use an AI Learning Framework (p. 80) with GenAI to develop in students the human skills that cannot be outsourced to machines. The authors’ argument here is really about leveraging GenAI to make learning more active and engaged. Active and engaged learning is typical in the primary school level, but as students progress up the educational ladder, school tends to get less and less engaging. By the time they reach college or university, readings, podcasted lectures, homeworks and exams are the typical fare. Instead, faculty could leverage GenAI to ignite student curiousity, then guide them in asking questions about the topic, engage them in the topic through discourse (with a GenAI tool, their peers and the instructional team), create opportunities for students to critically think about the content, and then apply their knowledge in authentic or meaningful assessments. GenAI can help facilitate all of these steps in authentic and active learning, essentially experiential learning, which is a powerful and natural way to learn and develop.
  1. Develop your skills at Promptcrafting (p. 90). Getting GenAI to do what you want it to do can be tricky. So, learning how to prompt and ask questions of GenAI is a valuable skill for both faculty and our students. Fitzpatrick and colleagues provide a simple and effective framework for prompting GenAI know as P.R.E.P. Prompt the machine, give it a Role or voice, be Explicit in your instructions, and set the Parameters for the answer. I found this framework to be simply helpful, especially because the authors then provide template after template for doing this, as well as illustrative examples of the templates-in-action through showing us the prompt and the resulting ChatGPT output. You can use this PREP for yourself, but also teach it to your students to help them use GenAI more effectively.

To illustrate, here’s how a professor at the college level might use PREP to create course content. Below is an image of a prompt I gave to ChatGPT-4 based on the template Fitzpatrick and colleagues provide on p. 132.

 ChatGPT Prompt for May blog

 Next is an image of the first paragraph and MC question that ChatGPT generated in response to my prompt.

ChatGPT output 1 for May 21 blog 

And after generating the second two paragraphs and MC questions (not shown), ChatGPT fulfilled the rest of the request as follows

ChatGPT output 2 for May 21 blog

Not bad, and all in 20 seconds! As the authors note, with any GenAI output, you will want to evaluate it, and teach your students how to evaluate it, before using it. And the authors provide another framework for doing just that: E.D.I.T. Evaluate the content for language, facts & structure; Determine accuracy and corroborate sources; Identify biases and misinformation; and Transform the content to reflect any of your own adjustments (p. 100).

The book is filled with helpful after helpful examples and templates for using the PREP and EDIT frameworks to quickly and easily make GenAI your teaching assistant, all of which are easily adaptable to the higher education setting.


There are over 300 pages in this book, with nuggets of wisdom in almost each one and so I have only touched the surface in this blog post. The good news is that the book is a quick read and provides an easy-to-navigate just-in-time resource for college and university faculty who want to begin to use GenAI in their teaching but don't know where to start. And, since it sells for under $30 USD, “The AI Classroom: The Ultimate Guide to Artificial Intelligence in Education” is a great purchase overall and if you are a higher ed faculty member, instructional developer/designer, or academic integrity expert, I highly recommend adding it to your summer reading list. You may be surprised with how easily and quickly you can begin to play around with, and plan for, how GenAI can help you teach, assess, and engage with students in learning come time for the fall term.