One of the best experiences of academic growth I had was because of my high school English teacher who took the time to write specific comments about my essays. In the 2000s when typing a paper required a person, I wrote those essays in word on a boxy desktop computer. My teacher naturally invested large quantities of his time to read our essays and to give well -considered comments.
Personalized feedback has not become cheaper or easier over time. As Russ Roberts asks in this episode: “How do we scale and feedback?” Until recently it was a bottleneck, limited by the availability of a competent human time. We cannot (yet) fully automate empathy, discernment or pedagogical intuition.
For now, the question is still what kind of feedback teachers can give that students can really give benefits. Daisy Christodoulou, the guest in this episode, offers a sobering criticism of how educators tend to give feedback in education. One of her points is that much of the written feedback that teachers give is vague and does not really help students improve. She shares an example of Dylan William: a high school student was told that he “had to make their scientific questions more systematically.” When asked what he would do differently next time, the student answered: “I don’t know. If I knew how I could be more systematic, I would have been the first time.” The teacher knows what a more “systematic” essay would look like, but the student did not (presumably) do not do specific exercise exercises that would help them achieve control.
Christodoulou expresses that students who do not do well often do not know How To get better, and generic feedback such as “Try it again” or “are clearer” offers no path ahead. I loved her metaphor in which writing was compared with marathon training. You don’t train for a marathon by letting one run every day. You build it up with a mix of shorter runs, strength training, stretching – activities that don’t even look like running, but are essential to run well. Similarly, becoming a better writer does not always mean writing another complete essay. It may mean that building vocabulary, practicing sentence construction or targeting inference work.
Christodoulou emphasizes the need for teachers to think in terms of Models of progression– To identify the small, specific steps that move a student from where they are to control. An example she gives: a student who is told to ‘distribute more transparent’ may not need any other essay allocation, but instead a targeted set of lessons about vocabulary, prefixes and suffixes. This is what meaningful feedback looks like – it leads to action.
Christodoulou also turns to the question that many of us are now struggling: Can AI help scales meaningful feedback? Can it assess essays in a way that is actually useful? From this recording at the beginning of 2025, the answer is: not entirely. There are still problems with accuracy, consistency and what AI models tend to ‘hallucinate’. Some of those problems can eventually be solved – but even now Christodoulou and her team are experimenting with hybrid models where teachers give audio Feedback and AI transcribe and organizes it. This kind of cooperation, where the teacher remains the source of insight and the AI handles the labor -intensive part, can be a path ahead.
At the same time there is a growing tension in classrooms: students want more and more skip The hard work of writing all the way and turning to ai -generated answers. So we try to scale up authentic feedback, just as students are tempted to shorten the learning process because of how easy it is. That challenge to retain the value of thinking and writing in the era of immediate text generation is one that we will struggle with for a while. As a teacher, Christodoulou encouraged me to think further than “let me show you again” for my students. I will try to break down smaller exercises that will help them achieve new advanced skills.