A modern take on Matthias Wandel's classic [0], which has you guess a variety of geometric attributes (e.g. angle bisection, centroid locating, shape regularization), not just simple partitioning of a line.
Great idea! Have you considered storing triplets <range, correct number, selected number> for each try and making image plots of these (x/y coordinates are correct/selected numbers, color of each pixel represents frequency) for multiple users for each range? I think the image might reveal interesting properties of human eyeballing, like near-perfect accuracy around 50%, but with less obvious correlations.
It would be great to have a 'training' mode, where you get to repeat ones you miss. This would increase the learning speed.
Easy training- repeat the one you just borked
Medium training- cycles through say 5 examples until you get all five within your target range (1%, 0.1%, whatever)
[0] https://woodgears.ca/eyeball/index.html
This is fun!
It would be great to have a 'training' mode, where you get to repeat ones you miss. This would increase the learning speed.
Easy training- repeat the one you just borked Medium training- cycles through say 5 examples until you get all five within your target range (1%, 0.1%, whatever)
Also, I tried this on laptop as well as my phone, I liked it more on my phone (I know the whole point is about precision though)
*my old pal Claude
A time limit would make sense imho. For extra challenge, add diagonal or curved lines.
0 out of 1,600
I still missed. Even when there was centered text.
Maybe the human is the weakest link
...
handleClick({clientX: els.bar.getBoundingClientRect().left + els.bar.getBoundingClientRect().width / state.n * state.target })
(It was pure luck)