Mobile platforms aim to provide a range of choices to the customer to make changes in the product as per his requirement, aesthetic sense and ease of access. Keeping this in mind, majority of mobile platforms come with built-in accessibility features which make it easy for the user to access information as per his requirement and convenience.
The multiple ways that mobiles can be personalized involves changing the screen size, the font color, font itself, along with magnifying text and reading background. The vast opportunities of personalization make the learning experience inclusive and customized.
To make an M-learning software appeal universally, the makers must keep in consideration that there are many learners who might be hearing impaired. Such people won’t be able to get an audio-based notification that rings in the background of an application they are currently using.
In such cases, visual cues are the best way to give a notification to the learner that some important message has been delivered or some area needs to be looked into. It also is a useful feature for people who don’t want constant buzzes or audio notifications to distract them from their work.
Nowadays, all M-learning tools have started implementing reading features when a person struggles with text. By using The Reading Feature, the person can listen to the in-built narrator read out lines after lines from the text.
People with dyslexia or literacy concerns with, say English, will be able to just listen to the lines and get the meaning all fine. Speech to text readers have been hailed as a breakthrough for visually impaired people, who earlier had to always rely on a physical narrator to read them some text.
In addition to these, screen readers and voice command readers have helped people navigate their cars without having to look up locations in a physical map. Developers are working on a speech recognition tool which will provide excellent writing support to writers.
Using this software, writers will be able to narrate sentences into the system and the sentences will be recognized by the editor and automatic transcripts of spoken sentences will be made. Not only that, they can also edit the transcripts through verbal commands.
This will save them a lot of time as all they have to do now is speak, as compared to what they used to do earlier, i.e. speak into a recording device, transcript it, and then edit it.