Students are increasingly using AI to complete their take-home assignments. This is something I encourage. AI is a fact of life today. The technology is here, it’s powerful, and it’s quickly becoming a standard tool in the professional world.
What is interesting to me is an occasional reaction when I use AI to grade assignments.
One student recently challenged my use of AI to grade assignments. I explained how I train AI to properly grade the assignment. I also explain that I review what AI suggests, I evaluate it and then make the final decision for grading. In other words, I’m doing exactly what I expect my students to do. AI is a great tool; however users and students still must critically evaluate the response from AI before relying on it.
The well-known lesson here is that the first answer from AI is usually not the best and final answer.
AI is a starting point, not a finished product. The first output is often generic, incomplete, or slightly off target. What separates strong work from mediocre work is what happens next.
This is where critical thinking comes in.
Students must evaluate AI’s response:
- Is it actually answering the question?
- Is it precise and technically correct?
- What’s missing?
- How can it be improved?
- What kind of practical examples can be provided to help clarify and answer the question?
From there, they refine their prompts, ask better questions, and iterate. This process—often called prompt engineering—is a real, learnable skill. And like any skill, it improves with practice.
When this process is used well, the results by students are amazing. I am teaching a class of professionals who are going into a medical related field. I can give them an advanced accounting assignment and with very little background and experience, they can provide solid will developed answers that in the past only accounting majors could provide.
AI will continue to change the education landscape and, when used well, will make students even more valuable as they enter the work-force.