The growth of generative AI in education presents both opportunities and challenges. For students, AI can be a useful learning companion. For academics, it raises important questions about authenticity, learning and assessment. The key challenge is not simply whether students use AI, but how we can encourage thoughtful, ethical and critically engaged use that keeps human learning at the centre. Drawing on approaches that emphasise supportive, non-accusatory feedback, this article explores how both students and educators can navigate the AI era constructively.  

GenAI in assignments: keeping the human voice at the heart of learning

"I'm not here to catch you out. I'm here to understand how you learned."

Imagine receiving feedback that opens a conversation rather than closes one. In a world where generative artificial intelligence (GenAI) is rapidly becoming part of everyday study and work, that mindset may be more important than ever.

Across higher education, the use of GenAI is now widespread. Students are turning to AI tools to brainstorm ideas, check grammar, organise their thinking and, in some cases, generate content. At the same time, academics are grappling with how to assess learning fairly while encouraging responsible use of emerging technologies. The challenge is global, affecting learners and educators across disciplines, institutions and countries.

Yet perhaps the most important question is not whether AI is being used, but how we ensure that genuine learning remains visible.

Beyond detection: a different conversation

When discussions about AI in assessment arise, they can quickly become dominated by concerns about misconduct, detection tools and academic integrity. While these issues matter, focusing solely on policing AI risks missing a valuable educational opportunity.

Instead, educators can frame feedback as an invitation to reflect. Rather than asking, "Did you use AI?" a more productive question might be:

"How did you approach this assignment, and what did you learn from the process?"

This shift changes the dynamic entirely. It encourages students to think about their decision-making, their understanding of the subject matter and the role that any digital tools may have played in supporting their learning. It transforms feedback from an accusatory encounter into a meaningful educational dialogue.

For students: AI is a tool, not a substitute for thinking

The most effective use of GenAI is not about outsourcing intellectual effort. It is about enhancing it.

Students can use AI to generate initial ideas, identify areas for further reading, improve clarity, or check grammar and spelling where permitted. However, the real value of higher education lies in developing the ability to analyse, evaluate, question and create. These are human capabilities that no AI tool can genuinely replace.

Before submitting work, students might ask themselves:

• Does this assignment reflect my own understanding?
• Could I explain the key ideas in my own words?
• Have I checked the accuracy of any AI-generated information?
• Is my own voice clearly visible throughout the work?

These questions encourage learners to move beyond passive acceptance and towards active engagement. In an age of abundant information, critical questioning is becoming one of the most important academic skills of all.

For academics: feedback that encourages reflection

Many educators have experienced reading assignments that seem unusually polished, formulaic or disconnected from a student's previous work. Responding effectively requires professional judgement, sensitivity and context.

A supportive approach might involve reflective prompts such as:

• What was the main argument you were trying to make here?
• Which part of this assignment best demonstrates your own thinking?
• How did you decide which sources and ideas to include?
• How did you verify the accuracy of the information used?

Questions like these focus on understanding, reasoning and ownership. They encourage students to articulate their thinking rather than defend themselves against accusations. They also provide opportunities for learning, regardless of whether AI was involved.

Why the human voice still matters

One consistent theme emerges across conversations about AI in education: the importance of preserving the human voice.

Students often assume that more polished language automatically leads to better work. However, academic quality is not measured purely by fluency. Educators are looking for evidence of understanding, critical engagement and personal insight.

Sometimes an imperfect but authentic explanation reveals far more learning than a flawlessly written paragraph generated elsewhere.

This is particularly important because AI tools can occasionally produce inaccurate information, fabricate references or present superficial analyses in a highly confident style. When students rely too heavily on such outputs, their own understanding can become hidden from view. As a result, opportunities to demonstrate learning may be lost.

A shared responsibility

The future of education is unlikely to involve choosing between AI or no AI. Instead, it will involve developing thoughtful practices that help learners use these technologies responsibly.

For students, this means maintaining ownership of their thinking, questioning AI outputs and ensuring that their learning remains visible.

For academics, it means creating assessment and feedback approaches that prioritise reflection, dialogue and growth. For a range of gentle, non-accusatory feedback options, see this Roy (2026).

 
Ultimately, the goal is not to win a technological arms race between students and institutions. The goal is to support, enhance and enable learning.

As AI becomes increasingly embedded in our educational landscape, perhaps the most powerful reminder for both students and educators is this:

Technology may generate words, but learning happens when humans question, reflect, challenge and think.

And it is those uniquely human qualities that education should continue to value most.