Why learning for future innovation is an essential skill

There are few parts of our lives that haven’t been fundamentally changed by the growth of technology over the past few decades – and nobody knows this better than Information Technology (IT) professionals. In fact, if you work in IT there’s a good chance that your job didn’t even exist ten years ago. But technology isn’t only changing the IT world: it’s changing almost every facet of the way we live, work and interact.

How you approach this level of change on a daily basis can either be the catalyst for boundless innovation or a serious detriment to the success of your business. In this blog, we’ll take a look at why being prepared to learn for future innovation can be the best defense against stagnation in an ever-changing market.

Learning for future innovation requires specific techniques and agility

Learning for future innovation is a very different process to learning for something that already exists – learning for an existing technology is more straight-forward because the method you choose is already tried and tested. Learning for future innovation, by contrast, seems almost self-contradictory. While it’s certainly no walk in the park, there are ways to make this easier, and at the rate that technology continues to drive our world forward, there will be an ever increasing number of topics to cover. And, if the mounting evidence is to be believed, most of us have been taught how to learn ‘wrongly’ throughout our lives. For professionals who are serious about learning future technologies, it’s vital to be able to adapt to a variety of working conditions, learning styles and environments in order to think outside the box and innovate more easily than the competition.

Everybody learns in their own way; no two learning styles are the same.

Every person has their preferred learning style, and what works for one person might be totally ineffective for the next. Here is a brief description of the most common learning styles:

• Elaborative interrogation: Being able to explain why an explicitly stated fact or concept is true – in other words, repeatedly questioning the facts or pushing the concept to its limits.
• Self-explanation: Explaining new concepts in the context of existing information, or explaining the necessary steps taken during problem solving.
• Summarisation: Summarising information in various lengths, to study from later.
• Highlighting/underlining: Marking the pertinent sections of a text or piece of work to be revisited later.
• Keyword mnemonic: Using keywords and mental imagery to associate verbal materials.
• Imagery for text: Forming a set of related mental images from text materials while reading or listening.
• Rereading: Restudying text material again after an initial reading, often several times.
• Practice testing: Self-testing or doing practice tests on the material that needs to be learned.
• Distributed practice: Implementing a schedule of practice that spreads out study activities over time, with the objective of forming a long-term understanding.
• Interleaved practice: A schedule of practice that mixes different kinds of problems, or a study programme that mixes different kinds of material within one single study session.

Having an understanding of the different learning styles and how they differ from one another isn’t only a good way to find out which works best for you, it’s also a valuable tool for understanding how the other members of your team may prefer to learn. Ultimately, working as a team means that being able to translate new information into a format your colleagues are able to understand is as important as being able to understand it yourself.

With over 10 years experience delivering courses, our trainers understand their audiences and are able to deliver the subject matter in ways that all attendees can digest.  For more information on how to kick-start your learning journey towards future innovation, or to enquire about our DevOps consultation services, please contact us today.

Image credit: Digitalist Mag