ML: More with Less

When designing ML (mobile learning) solutions, the temptation can be to cut corners by simply cramming an existing resource (e.g. a website) into a smaller screen.

This often turns out to be a poor solution (as highlighted by the W3C Device Independence report) for several reasons, including:

1. It leads to a poor navigation experience (due to incompatibilities with screen size, interface design, etc.)
2. perhaps more importantly – using resources on the go is not the same as sitting at one’s desk (the priorities, needs and circumstances can be very different, therefore calling for different solutions)

When planning out a process of content adaptation for mobile interfaces, it can pay off to think critically about which elements to keep and what to omit, shuffle the order of things (based on mobile user priorities) and consider potential restrictions (e.g. sun glare, screen size, availability of internet signal, etc.). With mobile learning, the rule of the thumb tends to be: less is more.

Mobile learning – doing more with less. (Image: CC by OakleyOriginals.)

An example of a great adaptation from desktop resource to ML tool is the Open University library mobile site, which was updated earlier this year.

Based on a user consultation, consumer feedback and studies of user behaviour through Google Analytics, the mobile version of the Library website was revamped. Content was stripped down to offer only the most used services on the home page. New context-specific tools were implemented (e.g. SMS reminders) and the navigation experience was simplified by developing a consolidated search to bring together results from various sources.

Tools like MoFuse or GetMo might do a decent job optimising design and layout for mobile interfaces. However, as well as layout, it is important to think about the priorities, needs and circumstances of ML users, which often means getting the hands dirty and redesigning resources.