As Artificial Intelligence (AI) continues to reshape the academic landscape, lecturers are finding themselves in a high-stakes game of catch-up. For Rev. Dr. Francis Anyanzu, SJ, a lecturer in Peace Studies and International Relations at Hekima University College, the “AI Era” is less about policing students and more about evolving alongside them.
In a recent sit-down, Dr. Anyanzu opened up about the challenges of identifying AI-generated content, the importance of “interrogating” technology, and the practical strategies he uses to ensure intellectual integrity in his statistics and research classes.
The Lecturer’s Dilemma: Catching the “Strange” Writing
Dr. Anyanzu admits that the rapid rise of generative AI has created a significant hurdle for educators across Kenya. Reflecting on a recent Kenya Education Network (KENET) meeting, he noted that many lecturers feel students are often steps ahead of the faculty.
“I wouldn’t say that I have caught a student using AI, but there are sometimes indications that the writing looks a bit strange,” Dr. Anyanzu explained. However, he pointed out a deeper systemic issue: “How do you prove that this is an AI? How do you penalize a student when you don’t have a policy or a system in place?”
Hekima is currently working on an official AI policy to address these grey areas, but until then, Dr. Anyanzu is relying on innovative pedagogical shifts.
Strategies for Authenticity
To move beyond a reliance on software detectors, Dr. Anyanzu has restructured his coursework to emphasize real-time engagement and varied assessment styles:
- The “Midnight Quiz”: Following statistics classes, he often assigns short, immediate quizzes. By focusing on the steps taken rather than just the final answer, he can verify the student’s logic.
- Group Work & Supervision: By utilizing group dynamics and supervised in-class exams where students use Excel and Word under his watch, he minimizes the opportunity for external AI generation.
- The Oral Defense: One of his most effective tools is the oral exam. “Oral is a way of checking whether the person is using AI,” he noted, as it requires the student to explain their reasoning in person.
Surprisingly, Dr. Anyanzu does not view AI as a total enemy. In fact, he encourages its use, provided it is used to build skills. He suggests that for complex data analysis in dissertations, using AI tools is often more educational than outsourcing the work to a human consultant.
“The point is not really to use AI or not, but how do you use it? What for? And how do you interrogate what AI produces?”
He warns against “generative” habits where students simply generate data and paste it. Instead, he advocates a model in which students interact with AI-generated outputs to discover new skills and deepen their understanding.
Looking Ahead
Currently teaching Social Research Methods, Elements of Statistics, and Forced Migration and Human Trafficking, Dr. Anyanzu remains excited about the future of his curriculum. As he looks forward to taking on new responsibilities in the migration program, his focus remains clear: forming ethical, skilled professionals who can navigate a tech-heavy world without losing their personal intellectual edge.
Pro-Tips: How to Use AI Ethically (The Dr. Anyanzu Way)
Based on Dr. Francis Anyanzu’s philosophy, AI shouldn’t be a “ghostwriter” for your degree; it should be a high-powered research assistant. Here is how to stay on the right side of academic integrity while still utilizing modern tools:
| The “Don’t” (Academic Dishonesty) | The “Do” (Intellectual Growth) |
| The “Copy-Paste”: Generating an entire essay or data set and submitting it as your own. | The “Interrogation”: Asking AI to explain a complex statistical concept or to suggest a structure for your research. |
| Outsourcing Analysis: Paying someone else to do your data analysis for your dissertation. | Skill Building: Using AI tools to help you learn how to use Excel or SPSS more effectively for your own data. |
| Passive Acceptance: Trusting every fact or citation AI gives you without double-checking. | Critical Review: Fact-checking AI outputs and “interrogating” the logic it presents to see if it holds up to academic rigor. |
By Pamela Adinda, HUC Communications & International Office Coordinator
