Feedback has always been central to learning. It guides students toward improvement, motivates them to keep trying, and helps them make sense of their own progress. With the rise of AI tools in education, platforms like Redmenta now make it possible for students to receive instant, detailed feedback. But the big question remains: Is AI enough on its own, or is the human touch still essential?
The truth is that the best results come from a partnership: AI + Teacher = Better Feedback. Let’s unpack why.
Imagine a student has just submitted an essay. Instead of waiting days for comments, the AI generates immediate notes such as:
For a learner, this is gold: the feedback is instant and specific. No vague “needs improvement,” but a concrete pointer they can act on straight away. This immediacy ties directly into formative assessment theory. Black and Wiliam (1998) highlight that feedback is most effective when it is both timely and focused on closing the learning gap. AI makes it possible for students to see what they can fix almost as soon as they finish writing—something even the most dedicated teacher cannot always deliver for an entire class at once.
Equally important is consistency. If 25 students make the same grammatical mistake, AI will flag it in the same way for each of them. This reduces the variation that sometimes creeps into teacher feedback when time is short or energy is low.
In short: AI acts like a first draft editor: it gets the basics right quickly and reliably, giving teachers more time to focus on deeper learning.
Now imagine another scenario: the same student receives AI feedback pointing out grammar errors and structural issues. But what the AI cannot see is that this student has worked incredibly hard on developing stronger arguments compared to their last draft.
This is where the teacher steps in. Instead of simply saying, “Fix these grammar points,” the teacher might write: “I can see how much stronger your reasoning is in paragraph three compared to your last essay. Keep pushing in this direction. Let’s tackle verb agreement next.”
Here, the teacher provides personalization, encouragement, and context—things no AI can deliver. Research on feedback literacy (Carless & Boud, 2018) shows that students must not only receive feedback but also make sense of it and decide how to act on it. Teachers play a critical role in framing feedback in ways that motivate and guide, not overwhelm.
Moreover, teachers bring nuance and emotional intelligence. If a struggling student only sees a long list of “mistakes,” they might shut down. A teacher knows when to soften criticism, when to emphasize progress, and when to set a bigger challenge. This is essential if feedback is to support learning rather than discourage it.
There is also the matter of tone and nuance. A struggling student might feel discouraged if presented with a long list of red flags from AI. A teacher can soften the language, highlight progress, and balance critique with motivation. This connects to Vygotsky’s (1978) idea of scaffolding within the learner’s “zone of proximal development”: machines can highlight errors, but only humans can provide the supportive push that encourages growth without overwhelming.
When used thoughtfully, AI and human feedback don’t compete, they complement each other. AI provides speed, clarity, and consistency, while teachers bring personalization, context, and nuance.
Picture it as a two-step process in Redmenta:
This model ensures that all students receive actionable comments quickly, while also benefiting from the motivational and pedagogical expertise only a teacher can provide.
So, does AI make feedback better? The answer is yes but only when paired with human insight. AI ensures that no student is left waiting for feedback and that corrections are clear and consistent. Teachers then step in to frame those corrections within the learner’s journey, making feedback personal, motivating, and connected to bigger learning goals.
AI starts the conversation. Teachers make it matter.
