- Players who receive spatial feedback during training (as we provide in Aim Lab) learn better and faster than those who receive basic binary feedback, as is provided by FPS games.
- Training improves players’ aim twice as much as players who did not receive training
- The benefits of training on aim performance continued even after training ended.
DOES ADVANCED FEEDBACK HELP PLAYERS IMPROVE THEIR PERFORMANCE?
Aim Lab provides augmented feedback about your weaknesses and biases to help you get better, faster. During our closed beta we saw that after only 200 plays, players hit twice as many targets during a fixed 60 second period of time while playing our Spidershot Ultimate task.
To dig deeper on the effect of feedback we designed a web-based, two-dimensional aiming experiment to measure how accurately players could make a mouse movement and click a target on the screen. We recruited more than 200 players to participate in the experiment and each player completed 200 trials of the aiming task.
For each trial, players were presented with targets that they had to click as quickly as possible. After each trial, players were given feedback about whether they hit the target or not (categorical feedback). After 50 of these trials, we changed the feedback for some players, who then received information about the exact location of their click on each trial and for the previous 10 trials (spatial feedback). This type of feedback provides players with a continuous report of how well they were performing. These players completed 100 trials with this enriched spatial feedback while the rest of the players continued the task with categorical feedback. For the last 50 trials, all players received the categorical feedback—this way, we could see if there was any lasting benefit to performance after training had ended.
The figure below shows the improvement in accuracy over the course of the experiment. The performance of players in the spatial feedback condition is shown in red and the players in the categorical condition is shown in blue. We grouped the x-axis into 6 different experimental phases: before training (Pre), during training (Train1 through Train4), and after training (Post).
The data show that while players perform very similarly before training—as you’d expect—the performance begins to diverge during training. Players in the spatial feedback condition show significant gains in aim performance throughout the training period above and beyond what we see from players in the categorical feedback condition. Importantly, the gain in aim performance persists even after training ends. At the end of the experiment, players who received training showed improvement in their aim performance that was about double what we see from players who did not.
These results are interesting, and tell us a few things. First, since all players showed some improvement over the course of the experiment, it suggests that there is some learning through repetition happening. If you play more, you will see improvements in performance. Second, aim training multiplies this effect. If you train more, you will see even greater improvements in aim performance, and these benefits continue to pay off even after training has ended.
We think that this data speaks for itself, but we’re eager to hear from you—the players—about your thoughts on the data, the results, and suggestions for how we might continue this work into the future.