Learning Is a Learned Behavior. Here's How to Get Better at It.
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Metacognition (thinking about thinking) is about being more inspective about how you know what you know. It's a matter of asking ourselves questions like: Do I really get this idea? Could I explain it to a friend? What are my goals? Do I need more background knowledge? Or do I need more practice?
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Learning how to learn is a meta-skill. It is a critical skill for everyone who needs to pick up and master new concepts frequently.
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Learning how to learn is critical for everyone. Most of us have to deal with a changing world and to learn how to manage tons of new information.
However, most of our learning methods are outdated and far from optimal. It may even be giving us an illusion of learning, like re-reading and highlighting that don't provide proper feedback to show what you haven't learned.
Focused and diffuse modes provide two models for how we develop, elaborate, deepen and broaden connections. Both methods are important.
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We have an impressive ability to learn, but our motivation to do so tends to decrease with age:
In this digital age, knowledge and expertise have been devalued.
What you know is now less relevant than what you can learn, and employers are less interested in hiring people with particular expertise than with the general ability to develop the right expertise in the future.
When we can all retrieve the same information, the key differentiator is not access to data, but the ability to make use of it, the capacity to translate the available information into useful knowledge.
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Like any other discipline, becoming good at analyzing data requires seasoning and experience. Executives with deep analytical expertise, sitting on the top of the organizational charts are responsible for spreading a culture of evidence-based, data-driven decision making.
This also ensures that data quality, data hygiene, implementation of data management and data privacy are respected and adhered to.
The larger group of non-executives need to reinforce proper analytical techniques, and while not everyone can be an elite quantitative analyst, there is a certain basic level of proficiency that can be attained.
Employees need to be provided with project opportunities and made to attend training academies that provide the specific activities to be completed for increasing their analytical capability.
Organizations that invest in senior-level expertise and reinforce daily analytical activities will be able to take advantage of Big Data to expand and evolve in the future.