Collaboration as a Catalyst for Faculty Development

It started with a dinner party. A small group of faculty members from two higher education institutions had gathered for an evening of good food and casual conversation. As it often happens with educators, the discussion inevitably drifted toward students, teaching methods, and the ever-looming influence of technology—specifically, AI.

One of the faculty members, clearly proud of her vigilance, recounted how she had recently caught a student using ChatGPT to cheat during a final exam. She shared how she immediately failed the student, framing it as a triumph for academic integrity. Around the table, nods of agreement echoed her sentiment—a collective sigh of relief that the sanctity of traditional assessment had been upheld. I couldn’t stay silent.

“Is it really cheating,” I asked, “if the student is simply using the tools available to them?”

The table grew quiet, and a few puzzled looks were cast my way. I pushed forward: “When employees use tools like Excel, coding assistants, or AI software to perform their jobs, we reward them for their resourcefulness and efficiency. Why should students be treated differently?” Some faces reflected curiosity, others disagreement. I went on to make my case—the way we assess students in higher education is outdated and inadequate for a world transformed by technology. If we cling to traditional exams and assessments that ban the very tools driving progress, we risk preparing students for a past that no longer exists.

As expected, my perspective was met with resistance. Some insisted that AI tools like ChatGPT make learning too easy, that students won’t think critically if machines do the work for them.

To Be Fair: Not All AI Use Is Suitable

Now, before the defenders of traditional education start sharpening their pitchforks, let me clarify: I’m not suggesting we hand students their diplomas simply for copy-pasting prompts into ChatGPT. There’s a line between using AI to facilitate learning and using it to avoid learning altogether. Asking ChatGPT to write a 10-page essay and then submitting it as is? That’s not resourcefulness; that’s academic laziness—or as I like to call it, creative plagiarism with a tech twist.

However, this doesn’t mean we should ban the tool outright. The question isn’t whether AI use is right or wrong—it’s how it’s used. AI can serve as a brainstorming assistant, a research companion, or a tool for enhancing critical thinking—if educators actually design assessments that demand meaningful engagement. Like a hammer, AI is only as useful (or dangerous) as the hands wielding it. So rather than whining about misuse, maybe it’s time to teach students how to wield the tool correctly.

The Faculty Roadblock: Progress vs. Tradition

The dinner party wasn’t just an amusing anecdote; it revealed a broader and deeper issue. Faculty members—whether consciously or not—often act as a barrier to progress in higher education.

While industries like tech, business, and even medicine sprint forward, embracing AI and automation, higher education plods along at a snail’s pace. Why? Because too many educators cling to traditionalism like it’s a life raft in a sea of change. Rather than adapting to the realities of modern technology, many faculty members double down on outdated teaching and assessment methods, as if preserving them will somehow freeze time.

This resistance is understandable. After all, change is uncomfortable, and embracing tools like AI means admitting that the way we’ve been teaching might no longer work. But let’s be honest: the problem isn’t that AI makes learning too easy—it’s that AI makes our jobs harder. It forces us to rethink teaching, redesign assessments, and learn alongside our students. That takes effort—effort that some faculty simply aren’t willing to make.

The result? Higher education becomes slower to adapt than nearly any other sector. And the irony? Students are left better equipped to navigate the real world than the educators preparing them.

If you think I’m being harsh, consider this: according to EDUCAUSE’s 2025 Top 10 IT Issues, higher education is struggling to address trust, relevance, and adaptability in the face of technological disruption [EDUCAUSE, 2024]. But while institutions invest millions in technology, those efforts often stall because faculty members are busy grumbling about digital distractions rather than embracing digital transformation.

The Problem With Traditional Assessments

The faculty member’s story about catching a student “cheating” is a prime example of higher education’s struggle to adapt to the realities of modern technology. Traditional assessments—timed exams, rote memorization, and isolated essays—were designed for a pre-digital era. These methods assume that knowledge must be stored in the brain and recalled on demand. But in a world where information is accessible at the click of a button, such skills are no longer sufficient.

Professionals today are valued for their ability to apply knowledge, not just possess it. Employers reward creativity, problem-solving, and critical engagement with tools like AI. When a marketing professional uses AI to craft a campaign or a software developer uses coding assistants to streamline work, they are celebrated for their productivity. Students, on the other hand, are penalized for doing the same.

For example, imagine a computer science student using ChatGPT to debug a program. Instead of viewing this as cheating, educators could ask students to document the process—to explain what the AI suggested, why it worked (or didn’t), and what they learned from the experience. This approach doesn’t eliminate critical thinking; it enhances it by requiring students to engage meaningfully with AI tools.

The Relevance Crisis: Are Degrees Losing Value?

As I argued at the dinner table, some degrees are on the path to irrelevance if higher education doesn’t change course. It’s a bold statement, but one supported by evidence. Employers across industries are increasingly skeptical of traditional degrees, particularly in fields where skills evolve faster than curricula.

Take technology and business as examples:

• Tech Industry: Companies like Google and IBM now prioritize skills-based hiring. Short-term coding bootcamps, certifications, and self-paced programs have become viable alternatives to four-year degrees. Tools like GitHub Copilot and AI assistants are part of the job—not optional.
• Business and Marketing: Platforms like LinkedIn Learning and Coursera offer micro-credentials that teach targeted, actionable skills—from data analytics to AI-driven marketing. These certifications are more agile and cost-effective than traditional degrees, making them attractive to both employers and learners.

The question we must ask ourselves is this: What value does a degree offer in these fields if students graduate unprepared for the tools and challenges they’ll face? If higher education does not align itself with industry needs, it will lose its credibility and relevance.

A Better Way Forward: Modernizing Assessments

The solution is not to ban AI tools but to rethink how we evaluate learning. Educators and institutions should embrace modern assessments that reflect real-world skills and contexts. Some promising alternatives include:

1. Project-Based Assessments: Instead of exams, students tackle projects that simulate real-world challenges. For example, business students could develop a marketing strategy using AI tools, presenting their process and outcomes.
2. Portfolio-Based Learning: Students build portfolios showcasing their work over time, including reflections on how they used AI tools to improve outcomes. This approach highlights growth, creativity, and critical thinking.
3. AI-Augmented Assignments: Rather than banning AI, assignments can integrate it. For instance, law students could use AI to analyze cases but would be graded on their interpretation, reasoning, and conclusions.

Conclusion: The Dinner Table Lesson

That dinner party conversation stayed with me. It revealed a deep divide between those clinging to traditional methods and those of us who see AI as an opportunity to reimagine education. The way we assess students must evolve to keep pace with the rapid changes in technology and society. Penalizing students for using AI tools is like punishing employees for using email instead of sending a letter—it misses the point entirely.

But here’s the kicker—higher education’s real problem isn’t technology. It’s the unwillingness of faculty to adapt. Institutions must invest in changing not just policies and curricula but the very mindsets of educators. If they don’t, higher education risks becoming irrelevant. And let’s face it—when students graduate unprepared, it won’t just be their problem. It will be ours.

The student who uses ChatGPT today could be the innovator who transforms their industry tomorrow—if we only give them the chance.

So, the next time we see a student using AI, let’s pause before calling it cheating. Instead, let’s ask: How can we turn this into a teachable moment? That is where the future of education begins.