Making Faculty Comfortable With GenAI

• Some faculty have an aversion to AI because its answers are too general and its style doesn’t match their own. They can solve these problems by learning to craft precise prompts.
• AI can help faculty generate content, teach in multiple languages, and conduct research. It’s an equally useful tool for students, administrators, and career services staff.
• Vlerick Business School provides its faculty with AI tools such as an Assignment Profiler that ensures that students can’t complete assignments solely by relying on AI.

 
With the launch of products such as OpenAI’s ChatGPT and Google’s Gemini, generative artificial intelligence (GenAI) is poised to have an unprecedented impact on productivity and efficiency in all industries. Leading global corporations have shown that they recognize the potential of GenAI, but adoption by universities and business schools has been slow. How can academic institutions maximize their use of this technology?

At Vlerick Business School in Brussels, we recently surveyed our faculty and students to discover how GenAI is being used in education. We also surveyed members of the International Teachers Programme (ITP), a global consortium of more than 1,300 educators and education leaders, who were on hand to attend a workshop through our Learning Hub.

We found that AI adoption was very high among students. In fact, 100 percent of our master’s students and 87 percent of our MBA students stated that they had used some form of GenAI to conduct research, aid in brainstorming, or help them write drafts of papers.

Numbers were significantly lower for faculty. Only 71 percent of Vlerick’s faculty and 70 percent of the ITP educators said they were utilizing AI. Those who said they were not using the technology gave two main reasons, which we suspect would be echoed by faculty around the globe. Some respondents felt that AI does not return answers that are precise or specific enough to provide useful assistance. Others said they dislike AI because its answers do not match their writing style or tone of voice.

Put another way, faculty are often reluctant to utilize AI because of what could be described as a “loss in translation”—its inability to provide the information they want in the formats they prefer.

But this loss of translation occurs when users rely on general and unspecific input. Faculty will benefit from GenAI only when they know what to put into it and what they want out of it. To overcome their aversion to AI, faculty must make a clean break from how they have traditionally used search engines to ask computers for information. The interaction they have with the GenAI tool is different, so the language they use will be different as well.

We believe that when faculty know how to pose questions and refine answers, they will find GenAI tools to be indispensable.

Prompt Attention

The first critical skill faculty must learn is how to write prompts to ask AI for information. They should begin with the simplest approach, known as a “task + context” formula. An article on Medium.com explains that the task specifies an action verb and a goal, and the context provides enough “background info to constrain possibilities.”

For instance, the task might be “Analyze these survey results and summarize key takeaways,” while the context might be “The information will be presented at a faculty meeting.”

To overcome their aversion to AI, faculty must make a clean break from how they have traditionally used search engines to ask computers for information.

Once faculty are comfortable with these two powerful components of the prompt formula, they can begin adding other elements. For instance, the Medium article suggests that the prompt could specify exemplars that can guide the AI, a persona that describes who the AI should be, the format that the answer should take, and the tone (casual, formal, excited) that the AI should use. These other components can be added to the first two with intuition and ease, as they generally play a supportive rather than a central role.

After faculty master prompt formulas, they can turn to prompt patterns, which are templates designed to extract more functionality from AI. For instance, in the “flipped interaction” pattern, the GenAI tool asks questions and the user responds. As an example, a user who wants to test his math skills might ask GenAI to continue generating math questions until he has provided 20 correct answers.

In our workshops with ITP and Vlerick Business School faculty, we showed participants how to craft prompts to get more specific, helpful information, and we also addressed concerns about the validity of the information GenAI supplies. After this session, attendees had much more positive attitudes toward GenAI than they had expressed beforehand.

The Many Uses of AI

Once faculty become skilled at crafting prompts, they can use AI tools to simplify many classroom tasks. For instance, AI can help instructors:

• Generate content, including images and videos.
• Gamify learning and support interactive content such as virtual reality.
• Profile learners and create personalized content for them.
• Translate materials for students who learn best in other languages.
• Write exams and automate grading.
• Detect plagiarism.

Professors also can use AI outside of the classroom as they pursue their scholarship activities. AI tools can act as research assistants that help them brainstorm ideas, analyze data, and improve their writing.

Administrators can use GenAI to manage the admissions process, guide applicants into choosing the best programs for their needs, and increase the efficiency of the assessment process.

But faculty aren’t the only ones at the business school who can benefit from using GenAI. As our survey showed, students already are turning to AI when they need tutoring or when they want help with writing assignments.

Similarly, administrators can rely on GenAI to manage and fine-tune the admissions process and guide applicants into choosing the best programs for their needs. They also can use AI tools to increase the efficiency and inclusivity of the assessment process and gain greater insights into learning outcomes. Finally, career services personnel can rely on GenAI to help students map their future careers, write résumés, prepare for interviews, and expand their networks.

One Institution’s Story

At Vlerick Business School, faculty who are particularly attuned to AI are using it extensively in their teaching and research. But we have taken steps to ensure that the whole institution uses the technology in a number of areas.

I head up the Vlerick Learning Hub, which I run with a manager and a team of 12 learning designers and technologists. Our team works on all aspects of integrating AI into education, and we deliver workshops designed to help faculty develop their AI capabilities. I also serve as chair of the Future of Management Education (FOME) Alliance, through which Vlerick collaborates with other business schools to create engaging online learning experiences.

Through the Learning Hub, we have developed the Vlerick Assignment Profiler—a GPT that assesses whether a professor’s planned assignment could be completed solely by the use of GenAI tools. If the answer is yes, the assignment is deemed unsuitable in its current form. However, the AI tool offers recommendations designed to boost the resilience of the assignment, ensuring it requires human input to be completed.

The business school also maintains the Vlerick Visual Summary Creator. After users input lecture or meeting notes into the system, it creates a visual image that summarizes the whole event, focusing on the key points. When participants create images based on lectures and discussions, they are more likely to retain information than they would if they simply relied on written notes. The image acts as a memory trigger, which saves participants from having to read through copious notes to find the data they want to remember.

As an example, below is an image that was created by participants in my Digital Strategy course, which discusses human-machine interaction through AI and the blue balloons game. The game simulates the DARPA Red Balloon Challenge, a competition that urges participants to develop a strategy using digital technologies for solving broad-scope, time-critical problems. Participants in my class generated the image to share what they had learned on the first day of the program.

Faculty at the school embrace other AI technology as well. Video generation tools allow teachers to be filmed a single time and then recreated as incredibly realistic avatars. These avatars can be used in the production of a wide range of video content.

Voice translation tools allow professors to deliver lectures in their native tongues, then have AI translate the lectures into any other language. The tool can even replicate the instructors’ accents, tones, and speech patterns.

Guidance for the Future

While GenAI offers innumerable potential benefits, academic leaders must make sure to use it responsibly. This can be challenging, because there is not yet a worldwide consensus on the ethical use of AI. The European Union has implemented legislation to ensure that businesses take a risk-based approach to AI, and China also has adopted regulations. Countries such as the U.S., the U.K., and Singapore have set guidelines, but have not yet put specific regulations in place.

Until formal guidelines exist, business schools can adopt their own approaches, such as:

• Creating policies that outline the acceptable and unacceptable ways that faculty, staff, and students can use AI.
• Taking care not to share sensitive data with large language models.
• Maintaining transparency with all audiences. If AI has been used to create content, say so.

As long as educators use AI in a safe and ethical manner, the technology has a valuable place in the business school. It can make faculty more effective and productive, administrators more efficient, and students more comfortable on the learning journey. In so many ways, AI has the potential to transform the academic sector.

The authors would like to acknowledge the contributions of Fleur Dumont and Benjamin De Wulf from the Vlerick Learning Hub.