I really appreciate the discussion!
Sybotes, Toadofsky, if you have links to previous posts here or elsewhere regarding this I'd love to take a look.
jperkins that article is definitely more towards what I'm thinking about. I started looking more into some scientific supporting arguments, but I'm not cognitive psychologist/learning expert. This Wiki article was fun to start reading: https://en.wikipedia.org/wiki/Operant_conditioning
My brief understanding of that and a few published article summaries seems to suggest that a mix of both positive and negative reinforcement is ideal for building behavior/learning.
I'm not sure that it would be more resource-intensive then what already is being computed. A "best (least bad) move" is already being computed during analysis, I think just displaying something like "(#total_moves - (#inaccuracies + #mistakes + #blunders))/(#total_moves)" could be simple positive feedback.
There's definitely an interesting discussion about where the line is between "what lichess should do" and "what you should get elsewhere". I would argue that if mistakes/centipawn loss/etc. are provided, then any positive metrics that can be computed in a similar manner fall into the same category.
I'll attempt to spend some time looking at the front-end code and see if there's anything simple I can come up with. Again the discussion is much appreciated!


