Active Brain Computer Interfaces (BCIs) allow people to exert voluntary control over a computer system: brain signals are captured and imagined actions (movements, concepts) are recognized after a training phase (from 10 minutes to 2 months). BCIs are confined in labs, with only a few dozen people using them outside regularly (e.g. assistance for impairments). We propose a "Co-learning BCI" (CLBCI) that reduces the amount of training and makes BCIs more suitable for recreational applications. We replicate an existing experiment where the BCI controls a drone and compare CLBCI to their Operant Conditioning (OC) protocol over three durations of practice (1 day, 1 week, 1 month). We find that OC works at 80% after a month practice, but the performance is between 60 and 70% any earlier. In a week of practice, CLBCI reaches a performance of around 75%. We conclude that CLBCI is better suited for recreational use. OC should be reserved for users for whom performance is the main concern.