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Learning from the data: is style important?

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Learning from the data: is style important?

Individual differences need to be taken into account if organisations are to extract the maximum value from the data they collect and generate, a Qlik executive suggests.

If you're a parent of a school-aged child or are otherwise involved in education or training, you've probably heard about learning styles – the idea that people are more able to absorb material delivered in ways that match the way they most easily learn.

The evidence is apparently far from cut and dried, but these styles are often classified as visual, auditory and kinesthetic.

Business intelligence, visualisation and analytics software vendor Qlik's ANZ regional pre-sales manager James Belsey says the real-world benefits of BI are largely derived from assisting institutional learning, which is built on individual learning.

{loadposition stephen08}So BI needs to engage all three learning styles. For example, for auditory learners, auto-generated narratives in written or spoken form will describe the shape of the data selected or the contents of a chart. Having a technology such as Amazon Echo “speak” these narratives may provide a compelling option for people who learn through hearing, he says.

Similarly, haptic feedback and 3D printing will likely play a future role in creating tangible outputs for the kinaesthetic learners so they can physically touching the associations of their learning.

"Our own experience and research on multi-touch UIs points found that people retain and ascribe more importance to data if they touch it, even when all they’re actually touching is a piece of cold glass. This is why designing BI software products specifically for the touchscreen experience is about more than just mobile devices," says Belsey.

Very large and high resolution displays and perhaps VR experiences will provide new options for visually-led learners, he suggests.

"Overall, more support for a range of learning types is critical if BI is to deliver as much value to decision makers as it can from the data-driven possibilities open to them. However, delivering information in more forms is only useful if people can make sense of the data - that is, if they know how to read it, if they are data literate."

So Belsey suggests organisations should mandate training in data literacy in order to gain an advantage from the increasing amount of data that is available.

"As data literacy becomes more prevalent, we’ll see more demands for and of data, which can only result in reaching better, faster decisions with BI when it caters to a full range of learning styles."


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