How to Ask for Feedback

A request for feedback that names its situation comes back with three things: where the work stands now, the gap between that and the goal, and the next change to make. A request gets those three back only when it states the situation, the skill being built, a genuine self-evaluation of the work so far, and one or two questions.

Who is asked matters less than how the request is written. The skill is in writing the request.

Core takeaways

• Self-evaluation comes first in every situation. It is the least reliable channel before the skill is developed and the most reliable once the skill is there.
• A request needs two things in balance: enough context for the reviewer to understand the situation, and a narrow enough focus for the reply to land on the skill being built.
• A vague request can do harm. More than a third of feedback interventions leave performance worse than before, and the harm concentrates in replies about the person rather than the work.
• A request has five parts: context, learning goal, an evaluation of the work, one or two targeted questions, and a review of the reply.
• Feedback improves performance only when the next attempt uses it. If the last reply has not changed what happens next, another request will not help; the next step is to run the experiment.
• The long-term aim is to judge one’s own work well enough that a request checks a reading instead of asking for one.

Who to ask

Self-evaluation is the first response in every situation. How reliable it is depends on the skill being judged. Before the skill is developed, it is the weakest of the four channels. Once the skill is there, it is the strongest, because an external feedback cycle takes days or weeks to come back and a self-generated one finishes inside the same session. Developing that self-evaluation is the long-term goal. It is not a backup for when nobody else is free.

The other three channels cover the gaps a single session cannot close.

Channel	What it is reliable for	When it earns its place
Self-evaluation	Tracks current skill: low before the skill is developed, highest overall once it is	First response in every situation
Peers	Varies with expertise	Fast, regular, niche questions, and the accountability that keeps a loop running
Experienced reviewer	Complex or persistent problems; the reply only counts if it is acted on	When the session cannot close the gap
General-purpose model	Standard technique questions; weaker on nuance	Before spending someone’s time

Peers vary with expertise. They are fast and regular. An experienced reviewer is for a complex or persistent problem, and the reply only counts if it is acted on. Reviewers disagree with each other and miss things. A general-purpose model is the thing to try for a standard technique question before spending someone’s time.

A Skills Audit is the structured self-evaluation that comes before a request is sent: the skill rated at its current level and its target level, with the next action set from the gap between them.

What a request has to include

The reply depends on what the request gives the reviewer. A request that works holds two things in balance: enough context that the reviewer understands the situation, and enough focus that the reply lands on what matters.

Focus and information combine in four ways, and only one of them is the aim.

• Broad focus with little information comes back as general comment on everything, and it is hard to act on.
• Narrow focus with little information comes back precise and aimed at the wrong thing.
• Broad focus with plenty of information comes back thorough and unfocused. Adding more context on its own does not fix a request.
• Narrow focus with enough information comes back as targeted improvement on the skill the goal names.

Naming the goal gives the reviewer something to evaluate against.

Why a vague request can do harm

A vague request returns vague guidance. The risk is real, though not every vague request causes harm. More than a third of feedback interventions leave performance worse than before. The harm concentrates where the reply is about the person rather than the work. Feedback aimed at the self is the weakest kind. A badly answered request can cost more than it returns. After a request that does not state its situation, the reply to expect is one about the writer’s worth rather than about the work. The structure of a request keeps the reply on the task.

The five parts of a request

The request has five parts, each named by a letter: C, L, E, A, R. Each letter is something the request does.

C, context. Where the work sits, what is coming, such as an exam or a deadline, and the circumstances that shape what a good answer looks like.

L, learning goal. The specific skill or process being built. A goal about how the learning happens lasts longer than a goal about what gets produced: getting better at asking questions, at a mapping technique, at reflecting on what works. Naming that goal is the feed-up, the statement of where the work is going, which the rest of the reply is measured against.

E, evaluate the work. This is the longest and most important step, and it costs more than a quick ask. On a question with an obvious answer the write-up is not worth doing; a search of existing notes is cheaper. Four prompts do the work: what was tried; what went well and what was hard; how that compared with what was expected; where the most important improvement looks to sit. The third prompt matters most. A reply is only usable against a stated expectation, because the gap between what was predicted and what happened is what changes how the work goes. “I don’t know” is not an answer: if the answer were obvious there would be no request. How the work is evaluated tells the reviewer about Metacognition: The Control Layer, the monitoring layer the reviewer reads when they read the reflection, and it is often more diagnostic than the work itself. Writing the evaluation also forces engagement with the problem before the problem is handed over.

A, ask targeted. One or two questions. Where many areas feel uncertain, ask about the ones with the highest yield, because improving many things at once is not possible. The second question can test the self-assessment itself: is this read right, or is something missing.

R, review and follow up. Absorb the reply before responding. Clarify what is unclear. When a point is hard to hear, keep attention on the work.

Two example requests

Two requests about the same work:

How is my exam prep going?

History exam in three months, prepared with interleaved retrieval. Re-reading, summary pages, textbook questions, and a friend's quiz. Big-picture ideas hold; dates do not. Recall is inconsistent: roughly seven in ten come back, and nearly all the loss is detail. Hypothesis: re-reading is taking the time the other methods need. How to improve recall of fine detail without losing the big picture? Is that read right, or is something missing?

The first request comes back with a general comment, and the second comes back with a plan.

What to do with the reply

Feedback improves performance only when it is used. The loop is not closed until a next attempt uses the reply. Three moves follow a reply: read it objectively, especially where it disagrees with the self-assessment; build a plan with priorities and specific experiments; test, review, and return with a new request only when the experiments are used up. The cycle is: receive, analyse, implement, produce new work, receive again.

The plan a reply produces is a hypothesis. In the same exam-prep case, one week of that hypothesis went as follows. Re-reading was dropped. Thirty minutes a day went to high-yield cards. Summary pages were replaced by maps. Inside the week, thirty minutes was not enough and the maps were too hard to build. The time went up to forty-five minutes, and the maps became a hybrid of short linear notes and small maps. That revision is what “test and review” means. In that same case a heavy reply was handled as material for a plan rather than as a verdict, because the comments were about the methods and not about the ability.

How big the next experiment should be

Marginal Gains sets the size of the next experiment: an improvement small enough to be almost certain, then another stacked on it. Kolbs Experiential Cycle is how the experiment gets reflected on: what happened, how it went, what rule that suggests, what changes next. On a complex problem, run three or four experiments before returning with a new request. On a simple one, do weeks of independent work first. Those numbers are approximate.

When to send the next request

If the last reply has not changed what happens in the next attempt, the loop is still open, and another request will not close it. Run the experiment instead.

A request that names its situation comes back with something that can be acted on in the next session. A reply that is general praise, or “keep going,” shows that the request did not give the reviewer enough to work with.

Giving feedback to others

Giving a reply benefits the giver. It forces critical evaluation, and it forces reflection on the methods the giver already uses. Seeing other people’s work widens the giver’s own approach. A reply worth giving has four traits: it is specific and gives examples; it names strengths before suggestions; it is about the work rather than the person; and it carries concrete next steps.

The skill this builds

The skill being built is self-evaluation. The external request is a temporary support for building it. The end point is a request that checks the writer’s own reading of the work rather than asking for one. That monitoring and adjustment is Self-Regulation, the larger loop this practice sits inside.

How to practice this

1. Before writing a request, rate the skill at its current level and its target level. Set the next action from the gap between them. Notice whether that self-evaluation closes the gap inside the session.
2. Write the context and the learning goal. Name the skill or process being built rather than the thing being produced. Notice whether the goal gives a reviewer something to evaluate against.
3. Write what was tried, what went well and what was hard, and where the most important improvement sits. Then write how that compared with what was expected. Notice whether an expectation was stated; without one the reply has nothing to be measured against.
4. Ask one or two questions, and pick the ones with the highest yield. Make the second question test the self-assessment: is this read right, or is something missing. Notice whether the reply confirms the read or corrects it.
5. Read the reply objectively, especially where it disagrees with the self-assessment. Build a plan with priorities and specific experiments. Notice whether the comments are about the methods or the ability; comments about methods are plan material.
6. Run the experiments and revise the plan as they go. Return with a new request only when the experiments are used up. Notice whether the last reply changed the next attempt; if not, run an experiment instead of asking again.

Open questions

What standard of self-evaluation is good enough before escalating.

Sources

• Hattie, J. & Timperley, H. 2007. “The Power of Feedback.” Review of Educational Research 77(1), 81–112. The three questions a reply must answer (where going / how going / where next), and self-level feedback as the weakest of four levels.
• Kluger, A. N. & DeNisi, A. 1996. “The effects of feedback interventions on performance.” Psychological Bulletin 119(2), 254–284. More than a third of feedback interventions reduced performance.
• Wisniewski, B., Zierer, K. & Hattie, J. 2020. “The Power of Feedback Revisited.” Frontiers in Psychology 10:3087. Revised effect is medium and highly variable; a minority of effects remain negative.
• Butler, D. L. & Winne, P. H. 1995. “Feedback and self-regulated learning.” Review of Educational Research 65(3). Internal feedback is the regulator external feedback has to enter.
• Boud, D. 2000. “Sustainable assessment.” Studies in Continuing Education 22(2). Learning to judge your own work is the long-term purpose.
• Boud, D. & Molloy, E. 2013. “Rethinking models of feedback for learning.” Assessment & Evaluation in Higher Education 38(6). The loop is not complete until a next attempt uses the reply.
• Sadler, D. R. 1989. “Formative assessment and the design of instructional systems.” Instructional Science 18. Formative assessment as building evaluative knowledge.
• Seijts, G. H. & Latham, G. P. 2005. “Learning versus performance goals.” Academy of Management Executive 19(1). Learning goals outperform outcome goals on novel and complex work.
• Topping, K. 1998. “Peer assessment between students in colleges and universities.” Review of Educational Research 68(3). Peer assessment as a learning activity for the giver.