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• Because artificial intelligence will likely become the primary way humans access information, professors must prepare students to use the technology effectively in their lives and careers.
• Students will especially need to learn skills related to effective prompt engineering, which refers to the ability to craft questions that elicit the most useful answers from AI platforms.
• The more comfortable that faculty become with using AI, the better they will be at teaching students how to use this skill ethically and effectively in the years to come.

While ChatGPT has only recently captured public attention, artificial intelligence (AI) is not new. Some form of the technology has been around . However, the fact that AI is now being used for more applications and is more accessible to the general public has changed the conversation, as we realize that the technology will have a significant impact on —including teaching.

Indeed, in the very near future, AI models will likely be the primary way we access knowledge—and higher education institutions will be where many people learn to use the technology effectively. This new reality makes it clear that it’s time for educators to master a new skill set relevant to AI and to teach those skills to their students.

Model the Technology

Although many learners are experimenting with AI models such as ChatGPT, the first place most learners should learn how to use AI effectively is in the classroom. But this will happen only if schools have introduced relevant learning activities into their curricula and have linked those activities to appropriate learning objectives.

However, because many faculty are not comfortable using AI, they will need to learn how to integrate the technology into their classrooms. Schools can start by showing students and faculty how AI can be viewed as an ally, rather than an enemy. To convey this message, schools can take several steps to expose students and staff to the technology:

• Create seminars to train faculty in how to introduce use cases of AI and how to emphasize the benefits and limitations of this technology.
• Use  (LXPs) that leverage adaptive learning and AI processes that allow faculty to detect when students are having difficulty with the material and to customize their courses. Faculty can use feedback from an LXP to help students gain a deeper understanding of their weaknesses and enhance academic outcomes.
• Use  (RPA) systems to automate repetitive tasks, such as the students’ submission of assignments to correctors. Such automation frees up faculty’s time so they can concentrate on their primary missions.
• Delegate to AI other routine administrative tasks, such as accepting admissions forms and generating emails and automatic replies, allowing staff more time to offer individualized support to learners.

Perfect the Art of ‘Prompt Engineering’

Once faculty are comfortable with the technology, the most critical competency they will need to teach is the art of prompt engineering—the skill of formulating questions in ways that elicit the most useful answers. Effective prompt engineering encompasses the following areas where both faculty and their students will need to refine their knowledge and abilities:

 (LLMs). Understanding LLMs—the algorithms that lie behind the output of generative AI—is a vital component to harnessing the potential of and tailoring interactions with ChatGPT. Only through meticulous and unambiguous prompt construction can users elicit desired responses from the language model.

That makes it critical that faculty incorporate the use of platforms such as ChatGPT into their classrooms. Then, they can teach students how to steer ChatGPT’s output toward their intended objectives. For students, the goal is to interact with ChatGPT as if they were engaging in a conversation with a human. To do this, they must first understand how LLMs work.

Communication. Students might view effective communication as less important when they are inputting a prompt into ChatGPT than when they are interacting with their professors or peers. But providing clear and explicit instructions in an AI prompt is just as essential as providing clear instructions to colleagues—good communication helps users streamline their interactions with AI.

Faculty can help students learn how to refine their questions to achieve increasingly precise responses (known in research as an ). They will learn to establish context, define the task, and specify the desired outcome for the language model.

For students, the goal is to interact with ChatGPT as if they were engaging in a conversation with a human.

The better students are at communicating with AI, the more likely it is that they will have seamless and rewarding learning experiences as they use AI to deepen their understanding of complex concepts, find solutions to problems, or explore new areas of knowledge.

Contextualization. When it comes to mastering prompt engineering, contextualization can be just as important as an iterative approach. With this skill, students will provide relevant factors and background information within the prompt to help the language model understand the specific context of each query. By setting the stage and giving necessary details, they increase the chance of receiving accurate and meaningful responses.

Role-playing. Here, students learn to assume different personas or perspectives in different prompts. This can help students obtain responses that align with specific viewpoints or generate creative outputs based on the chosen character.

Those who learn the skills listed above will become adept prompt engineers who will make the most of this technology in a variety of job roles and situations. They will be able to use AI effectively to streamline the problem-solving process, achieve a specific result, or improve their overall job performance. But faculty can set them up for success only by embracing ChatGPT and generative AI in the classroom, as pedagogical tools to help students exercise and expand their critical thinking abilities.

Disrupting Traditional Teaching Models

It’s an understatement to say that AI technology is having a seismic effect on faculty. It clearly is disrupting traditional teaching methods and practices, so much so that many faculty initially reacted by banning its use in their classrooms. But just as ChatGPT offers students a new way of learning, it compels faculty to adopt a new way of teaching.

In fact, there is immense potential in utilizing ChatGPT as a practical learning tool to foster and enhance students’ creativity and design thinking. If faculty incorporate relevant exercises into their courses, students can learn to use AI not only to write better questions and generate more innovative ideas, but also to discover the technology’s limitations.

So, how should faculty embrace AI in their classrooms instead of banning its use? They can adopt evolved pedagogical models that use AI to develop skills in several areas:

Assessment. The rise of AI will inspire the revision and rethinking of teaching and assessment methods. Faculty can use AI platforms to diversify student assessments, including formative, normative, and ipsative evaluations. They can even use AI to assess the new set of skills related to AI itself. These skills include the development of analytical mindsets, familiarity with intelligent user interfaces, the ability to look beyond statistics to instead use predictive analytics, and an understanding of artificial neural networks.

However, while looking at students’ final deliverables in a particular course still will be an important part of assessment, those deliverables will not be the only measure of student learning. The objective should shift from focusing on deliverables to evaluating the different stages of the learning process itself.

Faculty can use AI to streamline their own workloads, turning to ChatGPT to handle repetitive tasks while they concentrate on the most valuable aspects of teaching and learning

In other words, educators will need to do more than confirm that students solved a problem when they assess student learning. Educators also will need to ask students to explain how and why they solved a problem in a particular way. For example, faculty can ask learners to detail how they have used AI tools to create their deliverables—from case studies and analyses to full-length dissertations. Learners also could share whether they found the technology useful and how they adjusted to make AI work for them.

Critical thinking. Using AI as a complementary tool may improve students’ learning process while challenging their critical thinking abilities. Encouraging human-machine collaboration reinforces a student’s ability to adapt the technology to any environment or job role.

Adaptability. There is an urgent need to prepare the future users, designers, and shapers of these technologies to keep up with the pace of change. An essential part of teaching students to use AI is to introduce them to new platforms and functionalities as these innovations arise.

Better yet, faculty also can use AI to streamline their own workloads. They can turn to ChatGPT to handle the repetitive tasks. They can use the platform for help writing syllabi, for example, while they concentrate on the most valuable aspects of teaching and learning: adopting innovative pedagogy, nurturing creative thinking and problem-solving abilities, and ensuring that students develop essential future skills.

AI Is Here to Stay

It is inevitable that faculty increasingly will be working hand-in-hand with AI models to support their teaching. For that reason, higher education institutions must support faculty as they face this new challenge and do as much as possible to make that collaboration a success.

In essence, university faculty are, in a sense, gardeners who are nurturing two different seeds in fertile ground. On the one hand, they are developing AI-ready students; on the other, they are shaping the future use of AI technologies. Faculty might not be able to stop the AI trend from growing, but in this role, they can direct its growth by preparing students to use it as effectively and ethically as possible.

In the coming years, it will be interesting and enriching to observe how faculty teach AI models, as well as how students decide to use AI models to solve problems in the classroom. The technology might also help us address one of the more challenging aspects of teaching: how to engage students in their learning process.

Students will need to master the competencies we outline above if they are going to be able to work effectively with AI. In fact, we believe that as faculty and students experiment more with AI models, they will come to view the technology not as a threat, but as a teammate in their work.

The more schools enable faculty and students to strengthen their technological skills, the more they will support successful AI-human interactions. And the more they support these interactions, the faster we all will accelerate a shift in our mindset, from merely assessing AI’s capabilities and implications to improving and refining the way we use it.