You can write the most detailed, thoughtful, pedagogically sound feedback in the world.

But if your students don’t read it, does it even matter?

It’s a painful truth in education: feedback is often overlooked, ignored, or misunderstood—despite being one of the most powerful drivers of improvement.

At SmartMarker, we’ve spent the last year diving into this problem. Working with educators, training providers, and hundreds of real student submissions, we set out to answer one key question:

What makes students engage with their feedback?

And more importantly, how can we help them use it to improve?

The Traditional Feedback Drop-Off

Ask educators how much time they spend marking. Ask students how much time they spend reading the feedback.

You’ll notice a gap.

In many STEM and vocational programmes, we found:

• Students skim for the grade and move on

• Feedback that isn’t clearly tied to outcomes gets ignored

• Vague comments (“needs more explanation”) don’t lead to action

• Delayed turnaround makes the feedback irrelevant by the time it arrives

This isn’t a motivation issue. It’s a communication issue. Students need feedback that feels personalised, understandable, and immediately useful.

What SmartMarker Does Differently

SmartMarker uses AI to generate structured, criteria-based feedback in language students understand.

Here’s what’s changed:

1. Feedback is Specific, Not Generic

Instead of comments like “expand on this section”, students see:

“You provided relevant environmental factors, but did not explain their impact on the construction process. This limits evidence for LO2, criteria C2.1.”

Students now know exactly what they missed, and where.

2. Feedback is Organised by Learning Outcomes

Feedback is grouped by learning objective or assessment part, so students can clearly see how their performance maps to the course’s goals.

This turns a messy comment section into a structured learning map.

3. Justifications Reference Their Own Work

SmartMarker highlights specific excerpts from the student’s submission to support its evaluations.

“The AI has identified this paragraph as evidence for Merit criteria. Here’s why…”

This kind of feedback doesn’t just instruct—it teaches.

What We’ve Seen So Far

Across partner institutions using SmartMarker:

• Students are 3x more likely to fully read AI-generated feedback than traditional paragraph comments

• Engagement rates rise when feedback includes specific criteria and quoted examples

• Learners report feeling more confident in understanding what “Pass”, “Merit”, or “Distinction” actually mean

• Educators receive fewer clarification requests, freeing them up to support where it really counts

A Quick Case Snapshot

In a pilot across a Level 3 Construction programme, one trainer reported:

“I used to get a wave of emails after returning assignments—students asking what I meant by ‘not clear enough’ or ‘didn’t meet LO3’. With SmartMarker, they now come back with specific questions about how to improve. That’s a massive shift.”

Final Thought

When students receive feedback that’s clear, connected to their work, and tied to learning goals, they pay attention.

And when they pay attention, they improve.

That’s the power of structured, AI-powered feedback done right. Not just faster grading, but smarter, more impactful conversations about learning.

Want to help your students take feedback seriously and use it to grow?
Get in touch and see how clarity changes everything.