Artificial intelligence is making its way into classrooms at MacEwan University, but how students are being taught to use it varies considerably across programs and instructors.
Across the communication studies, computer science, and nursing faculties, professors are incorporating AI into their coursework in many ways, ranging from generative tools to HAL, which is an artificial patient simulator designed to help nursing students practice their clinical skills.
The shift comes as MacEwan University develops a broader framework for AI use, while leaving decisions about its place in the classroom largely up to individual programs and instructors.
MacEwan’s Centre for Teaching and Learning provides instructors with three suggested approaches to generative tools in assessments: permitted with acknowledgement, permitted with prior permission, or not permitted. However, the university notes that a complete ban on AI is not recommended because generative technology is increasingly incorporated into tools students already use, such as Grammarly.
The university’s 2023 Artificial Intelligence/Academic Integrity Working Group similarly recommended that decisions about AI remain discipline and context-specific. It also recommended adding learning outcomes that teach students about the capabilities and limitations of generative AI, as well as its ethical implications.
That flexibility has produced considerably different approaches across campus.
Communication studies
In communication studies, associate professor Dr. Rey Rosales has embraced generative AI in his teaching and encourages students to experiment with the technology.
“I’m more on the early adopters side because I embrace this,” said Rosales. “It’s really profound and life-changing and transformative technology.”
In his communication theory course, Rosales encourages students to use AI to assist with research and proposal writing, which allows them to spend more time working with real clients and developing projects based on real-world problems.
Rosales also said he has experimented with AI outside the classroom. He is supervising an independent study using AI-generated “synthetic audiences” to provide feedback on the Griff, which will then be compared with feedback gathered from a traditional focus group.
His approach reflects one end of a much broader spectrum among instructors over whether incorporating AI into classes prepares students for workplaces that are increasingly adopting the technology, or if it risks undermining the skills students attend university to develop.
For other communications studies instructors, incorporating AI has also meant reconsidering how students are assessed and which skills need to be developed ahead of implementing AI.
Journalism professor Dr. Steve Lillebuen said AI initially excited him, but its rapid development has made him more cautious about how it is used in the classroom. While he sees applications of the technology in both education and journalism, he is concerned about which skills and experiences students may lose if they rely on AI before developing their own critical thinking and media literacy skills.
“If you’re outsourcing that development to a computer, you’re just not going to be able to develop that critical eye and that scrutiny of sources that is so important in our degree.”
– Dr. Steve Lillebuen, associate professor in the department of communications.
In his courses, Lillebuen allows students to use some AI as a study aid to help them understand or summarize concepts and information, with the understanding that the technology can make mistakes. He also pointed to its use in journalism as a way to analyze large amounts of data or information during investigations before individuals verify the findings through additional reporting.
The technology has also required him to adjust how he assesses student learning.
In his literary journalism course, Lillebuen has replaced a traditional term paper with assignments that include academic peer reviews, concept trees, and intellectual reflections after finding that generative AI could produce what he described as a “very passable generic essay.”
“I don’t think term papers can function the way they used to,” said Lillebuen.
That tension looks different in computer science, where AI is both a tool students can use and part of the technology they are learning to understand.
Computer science
Computer science professor Dr. Calin Anton said he allows students to use AI for projects, but has moved away from take-home assignments after receiving work that students could not explain.
“I don’t think we can prevent its usage. I don’t think it would be right to prevent its usage because it improves the productivity. The thing is, how we’re gonna encourage the use of it in such a way that it’s not detrimental to the development of students.”
– Dr. Calin Anton, professor in the department of computer science at MacEwan University.
Anton used calculators as an analogy: students need to understand the fundamentals before relying on a tool to do the work for them.
In his artificial intelligence course, Anton plans to replace traditional take-home assignments with an approach that requires students to reproduce solutions in class without access to a large language model. In his cybersecurity course, he has replaced some assignments with external IBM certifications. IBM certifications are “industry-recognized credentials” used to test and validate skills across various computer science skill sets, such as artificial intelligence, automation, data, and analytics.
For Anton, being able to evaluate what an AI produces is increasingly important for students because generated code can be inefficient, incorrect, or insecure.
“So, in a sense, my feeling is more and more with LLMs, critical thinking becomes extremely valuable and actually critical,” he said.
Nursing
Nursing faculty member Hunaina Allana said students are exposed to tools such as Microsoft Copilot, virtual simulations, and AI-supported learning resources. She encourages students to use generative AI for tasks such as creating study resources and improving the clarity of nursing documentation, while stressing that students remain responsible for verifying the technology’s output.
“My biggest concern is not AI itself — it is how we use it ethically and responsibly,” said Allana in a written response to the Griff. “As a faculty, I need to ensure that students’ own thinking, clinical judgment, and critical thinking skills remain at the center of their learning.”
MacEwan’s nursing program has also introduced HAL, an AI-powered patient simulator capable of conversational speech, facial expressions, and physiological responses. Unlike a chatbot producing an essay or assignment, the simulator allows nursing students to practice responding to patients and making clinical decisions in a controlled environment.
Design
A 2025 paper published in MacEwan’s Pedagogical Inquiry and Practice documented a project led by design professor Dr. Isabelle Sperano that explored how undergraduate design students interacted with generative AI tools.
According to the paper, students worked with several AI chatbots and reflected on the different characteristics they perceived in their interactions with them. The students identified and visually represented six AI “personalities,” including “the assistant,” “the angel,” and “the slacker.”
The authors suggested these personifications could be used in classrooms to build AI literacy by prompting students to think critically about their interactions with AI, leading them to question the accuracy of AI-generated outputs. They also cautioned that personifying AI could create misconceptions about how the technology works if it’s not accompanied by adequate education on how generative AI processes information.
These examples illustrate why a single university-wide approach to AI may be difficult to apply in practice. Generating computer code, communicating with a simulated patient, or reporting a news story each involves different skills and professional expectations.
For students, this can mean that the rules and the lessons surrounding AI can change considerably from one classroom to the next.
MacEwan’s current guidance tells students to check their course outlines and ask instructors how AI can be used on individual assignments. The university also does not license any generative AI detection tools, citing concerns about their reliability and built-in biases.
As AI becomes further embedded in the software that students already use, the question facing instructors is increasingly shifting from whether students will encounter the technology to what they should be expected to know how to do without it.
For Allana, that balance ultimately comes down to keeping the technology in a supporting role.
“Ultimately, technology should enhance—not replace—the educator, hands-on practice, clinical experience, and human connection at the heart of nursing education.”
