Researchers from the universities of Finland, Switzerland and Cambridge in the UK have published the results of a global study highlighting the speeds at which people can type on their mobile devices.
The results from 37,000 volunteers showed that younger people are much quicker at typing on their mobiles.
On average, mobile users were able to type at a speed of 36.2 words per minute (WPM), with 2.3% of errors left uncorrected.
By comparison, the average on keyboards is around 52 words per minute.
The quick typing test can be accessed here, on both desktop and mobile devices.
A summary of the findings are below:
- On average, participants typed at 36.17 WPM;
- 75% of participants had a performance below 43.98 WPM;
- The fastest typists reached over 80 WPM;
- On average, participants left 2.34% of errors uncorrected;
- 75% of participants left less than 3.07%;
- The uncorrected error consisted of 11.1% insertion errors, 55.6% substitution errors, and 33.3% omission errors;
- Substitution was the most salient error type, which is in line with a study of text entry on physical keyboards;
- On average, participants performed 1.89 backspaces per entered sentence.
The results showed how age differences affect mobile typing capabilities. The researchers found that participants of age between 10 and 19 typed fastest (39.6 WPM) while their 40-50-year-old counterparts could only manage between 26 and 29.
Unsurprisingly, participants who reported to use two fingers were significantly faster than those who used only one finger – with two thumbs typing being the fastest.
The researchers also found evidence of relationships between performance and use of intelligent text entry techniques: such as auto-correct usage correlating to more faster entry rates, while word prediction impacted speed negatively.
Intelligent text entry (ITE) methods use statistical language models to exploit the redundancies inherent in natural languages to improve text entry.
The reason why predictive text actually slows down input is because users have to draw their attention away from typing to focus on the list of words predicted by the technology, the research showed.
The full results of the study can be found here.