The engine can't teach you. Here is what a question does that +1.3 cannot.
An engine eval grades your move but never sees your reasoning. Feedback research says the reasoning is what matters. Commit to a reason first and the correction has something to stick to. Your most confident mistakes may even be the easiest to fix.
Published 2026-09-03
+1.3. That's what the engine gives you. It's accurate to a tenth of a pawn and it shows up in milliseconds. It says nothing about you. It doesn't know why you played the move or what you were going for, it can't tell which of your habits got you there, and it won't notice when you do the same thing next week.
This post is about the gap between a grade and actual feedback. It's also about why a coach asks you a question before telling you anything. The question is where most of the learning happens.
What a number leaves blank
If a teacher has read one review of feedback research, it's probably John Hattie and Helen Timperley's. Their main claim is simple enough. Feedback is among the strongest influences on learning, but how much it helps depends entirely on what it's about. Feedback on the task, on your process, and on how to regulate yourself next time works. Feedback aimed at you as a person (“good job”) does almost nothing. Good feedback, they argue, answers three questions: where am I going, how am I going, and where to next.1
A later meta-analysis put the average effect lower than Hattie's early syntheses did, and found it varied hugely, for the same reason: most feedback isn't about the process.2 An eval answers “how am I going” in about the narrowest way possible, and the other two stay empty. It scores the outcome of a decision without ever seeing the reasoning behind it.
Feedback needs something to stick to
Nate Kornell, Matthew Hays and Robert Bjork had people guess an answer before they were shown it, and set things up so the guess was almost certain to be wrong. Even so, the failed guess helped people remember the right answer later, compared with just studying it.3 Janet Metcalfe's review of the research on errors lands in the same place from a lot of different angles. Making an error and then getting corrected beats being handed the answer, and instruction built to avoid errors is likely counterproductive.4
In chess terms, say you commit to a reason: “I took on e3 because trading off that knight looked like the simplest way out.” Now there's something for the correction to hook onto. When the coach shows you that Black recaptures with check and picks up the knight on f7 a move later, you know exactly which thought it's correcting. Compare that with the engine just showing you Qe6 when you never committed to anything. You nod and move on, and none of it sticks.
The blunders you were surest of are the easiest to fix
Brady Butterfield and Janet Metcalfe expected high-confidence errors to be the hardest to correct. They found the opposite. On general-knowledge questions, the wrong answers people felt surest about were the ones most likely to get fixed on a later test, once they'd seen the right answer.5 This is called hypercorrection. It needs corrective feedback to happen, and it's mostly been shown with trivia, so we don't want to push it further than that. It suggests the move you were sure about, and wrong about, is the one you're most likely to stop playing, but only if someone gets you to say how sure you were and then shows you the fix.
That's why a coach asks how sure you were. The engine never asks.
The skill engine review never trains
John Flavell named it in 1979: metacognition, knowing about and keeping track of your own thinking.6 A player who's good at this knows when they're calculating and when they're guessing. They notice when their plan has quietly shifted. They can tell “this move is good” apart from “I want this move to be good.” None of that is chess knowledge, and all of it shows up in your results.
You can't practice keeping track of your thinking if nothing ever asks you to report it. A question makes you do that. You have to look back at what you actually did and put it in words, and that's usually when you find out it wasn't what you thought.
Strong players get something out of slowing down too. One study scored moves with engine evaluations and found that both strong and weaker players picked objectively better moves after extra deliberation than on their first instinct. That held on easy and hard problems alike.7
We still use the engine. It just doesn't talk first.
We're not saying passive review is useless. In the classic testing-effect study, students who reread a passage actually beat the self-testers on a quiz five minutes later. The flip only showed up a week out.8 The engine is the most accurate judge of a chess position there has ever been, and Chessalyz runs one under everything. What we changed is the order. You go first. The engine checks your answer after.
eval: +1.3
best: Qe6
Where am I going? How am I going? Where next? Blank, a number, blank.
“You spent a real think on Bxe3. What was your evaluation of the resulting trades, and what other candidate moves were you comparing it against?”
Once you've written your reason, it shows where it broke, what Black got out of it, and what to check first next time.
- 1.Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81-112. doi.org/10.3102/003465430298487
- 2.Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology, 10, 3087. doi.org/10.3389/fpsyg.2019.03087
- 3.Kornell, N., Hays, M. J., & Bjork, R. A. (2009). Unsuccessful retrieval attempts enhance subsequent learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(4), 989-998. doi.org/10.1037/a0015729
- 4.Metcalfe, J. (2017). Learning from errors. Annual Review of Psychology, 68, 465-489. doi.org/10.1146/annurev-psych-010416-044022
- 5.Butterfield, B., & Metcalfe, J. (2001). Errors committed with high confidence are hypercorrected. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27(6), 1491-1494. doi.org/10.1037/0278-7393.27.6.1491
- 6.Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906-911. doi.org/10.1037/0003-066X.34.10.906
- 7.Moxley, J. H., Ericsson, K. A., Charness, N., & Krampe, R. T. (2012). The role of intuition and deliberative thinking in experts' superior tactical decision-making. Cognition, 124(1), 72-78. doi.org/10.1016/j.cognition.2012.03.005
- 8.Roediger, H. L., III, & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249-255. doi.org/10.1111/j.1467-9280.2006.01693.x
Your last game has a question in it.
Connect Chess.com or Lichess, or paste a PGN. Chessalyz finds the moments that decided the game, asks what you were thinking, and coaches from your answer. Five games a month are free.
Try it on your last game- Why writing down your reasoning makes a chess lesson stick
You check the engine line after a loss, nod, and play the same move next week. About fifty years of memory research explains why, and why a good coach asks you a question before telling you anything.
- Make new mistakes: why your flashcards should be your own blunders
Why the positions you actually lost make better flashcards than a puzzle you've never seen, and what the memory research says about reviewing them.
- Learning by thinking: what a fifteen-minute post-mortem does that another game does not
Masters have always gone back over their own games. Club players mostly don't. The research on why that habit matters, and why playing more doesn't replace it.