I do watch KBC quite often on Sony TV. It is a TV show where people can become millionaires by answering 'tough questions' like "which is the longest rail bridge in India', 'which cricketer won the Arjuna award in 2011' and so on. It is an indeed a lovely show to test your 'data-retrieving ability' and earn 'money' from that ability.
But 'data' should not be confused with 'knowledge'. It should be remembered that the journey of talent building starts with 'data'; it does not end with data. In the journey of building your talent, 'data' classification is the first step. The next steps are data > information > knowledge > raw working model > Skill ( mature working model). And it is the combination of skills that help you develop the talent, be it in singing, mathematics or programming.
Data > Information > Knowledge
For instance, when you hear that software company like TCS has a turnover of 2.1 billion in a quarter, this input is Data. Not useful by itself. So you add context to the data to make it useful. This becomes information. For instance, if i tell you that the turnover of its competitor Infosys was 1.8 billion in the same quarter, this data becomes more useful for you. Data with appropriate context is Information. You can view data from different windows of context. For instance, if i tell you that the turnover of TCS in the previous quarter was 2.5 billion, the data assumes different significance. Information therefore is 'contextual'. Smart people use 'multiple' contexts to make the data useful to them.
On the other hand Knowledge is 'information with why'. Knowledge deepens your understanding of the subject. For instance, when you want to understand why TCS turnover is low/high this quarter, you gain more knowledge of the subject. For that you will have to get more information, such as the amount of turnover of TCS this quarter from North America as compared to Europe? Or the turnover of TCS from Banking domain as compared to say Telecom domain? The journey from Information to knowledge is driven by your desire to understand 'why'. You have to view the same data from different 'windows' and gain more understanding of what that turnover means.
Knowledge > Skill
The journey till knowledge can be covered by sitting in the arm chair. Next step in the journey - of converting knowledge into useful action - requires active working mode.
For instance, imagine you are a share broker or business analyst. What action would you recommend to your client-investor on the basis of 'turnover of 2.1 billion last quarter'? Should he buy more shares of TCS or sell them? This skill is based on how you 'process the knowledge' into action. For this processing, you design a 'working model' to understand and predict the share price; one of the element of which is turnover.
When you are inexperienced, your working model is 'raw'. It is based on few elements with thin interconnections between them. With deeper 'understanding', you add more elements to your working model and also connect them 'densely'. Your working model improves as it starts reflecting 'as-is reality' of share price in a better way. With further deeper understanding and reality-testing ( both are required), your working model matures. Now you are called a sharp 'share analyst'.
This is the skill stage of talent building. It may take years to reach this. Some fail to reach this 'skill' stage because of the inherent difficulties in 'reality-testing'. One can read research papers and model to incorporate 'more and more elements' in the model, but all that is useless until you can 'test them' in the reality appropriately. If the model is not reflecting reality, we say that the person's knowledge is 'theoretical'.
Imagine, that instead of a share analyst, you are a manager of Infosys of telecom domain. In that scenario, your working model has to be developed with very different elements. This working model therefore is highly individualised and has to be developed and reality-tested by every individual for his own 'action'.
It has also been seen that talented individuals do not possess more data; they possess more relevant knowledge, that is better working model. For instance, when the pieces on the chess board were placed randomly, it was seen that both amateur and professional chess players remembered position of about 14 pieces on the board. However, when an actual chess board of a live game ( in between) was shown to amateur and professional chess players, professional chess players remembered all the pieces on the board, while amateurs could remember half of the pieces on the board.*
Conclusion
As your child is still studying and developing his 'knowledge', you are more concerned in helping your child develop his journey from data > information> knowledge. A skillful teacher can help your child build this chain better.
And because we build knowledge from one level to another in a chain, not understanding arithmetic in the 5th class creates difficulty in understanding arithmetic in 6th class. At this time, your child needs individual customised 'guidance' to identify and rectify his chain; not a coaching class that teaches the entire class of students. Later, we shall see what skillful teachers do differently.
From the above discussion, you would also appreciate that a coaching class may help your child get better marks, not necessarily gain better knowledge, because the actions for gaining more knowledge are not similar to actions for getting more marks. And remember, both are necessary: marks for short-term, and knowledge for long-term purpose.
You would also appreciate now that Internet only presents 'data' to your child. To convert that data into knowledge or action requires a huge degree of effort. Please do not ask your child to surf internet to decide which discipline he should choose in his life, because internet just provides data on different disciplines, not even information.
* Talent is overrated: Geoff Colwin
But 'data' should not be confused with 'knowledge'. It should be remembered that the journey of talent building starts with 'data'; it does not end with data. In the journey of building your talent, 'data' classification is the first step. The next steps are data > information > knowledge > raw working model > Skill ( mature working model). And it is the combination of skills that help you develop the talent, be it in singing, mathematics or programming.
Data > Information > Knowledge
For instance, when you hear that software company like TCS has a turnover of 2.1 billion in a quarter, this input is Data. Not useful by itself. So you add context to the data to make it useful. This becomes information. For instance, if i tell you that the turnover of its competitor Infosys was 1.8 billion in the same quarter, this data becomes more useful for you. Data with appropriate context is Information. You can view data from different windows of context. For instance, if i tell you that the turnover of TCS in the previous quarter was 2.5 billion, the data assumes different significance. Information therefore is 'contextual'. Smart people use 'multiple' contexts to make the data useful to them.
On the other hand Knowledge is 'information with why'. Knowledge deepens your understanding of the subject. For instance, when you want to understand why TCS turnover is low/high this quarter, you gain more knowledge of the subject. For that you will have to get more information, such as the amount of turnover of TCS this quarter from North America as compared to Europe? Or the turnover of TCS from Banking domain as compared to say Telecom domain? The journey from Information to knowledge is driven by your desire to understand 'why'. You have to view the same data from different 'windows' and gain more understanding of what that turnover means.
Knowledge > Skill
The journey till knowledge can be covered by sitting in the arm chair. Next step in the journey - of converting knowledge into useful action - requires active working mode.
For instance, imagine you are a share broker or business analyst. What action would you recommend to your client-investor on the basis of 'turnover of 2.1 billion last quarter'? Should he buy more shares of TCS or sell them? This skill is based on how you 'process the knowledge' into action. For this processing, you design a 'working model' to understand and predict the share price; one of the element of which is turnover.
When you are inexperienced, your working model is 'raw'. It is based on few elements with thin interconnections between them. With deeper 'understanding', you add more elements to your working model and also connect them 'densely'. Your working model improves as it starts reflecting 'as-is reality' of share price in a better way. With further deeper understanding and reality-testing ( both are required), your working model matures. Now you are called a sharp 'share analyst'.
This is the skill stage of talent building. It may take years to reach this. Some fail to reach this 'skill' stage because of the inherent difficulties in 'reality-testing'. One can read research papers and model to incorporate 'more and more elements' in the model, but all that is useless until you can 'test them' in the reality appropriately. If the model is not reflecting reality, we say that the person's knowledge is 'theoretical'.
Imagine, that instead of a share analyst, you are a manager of Infosys of telecom domain. In that scenario, your working model has to be developed with very different elements. This working model therefore is highly individualised and has to be developed and reality-tested by every individual for his own 'action'.
It has also been seen that talented individuals do not possess more data; they possess more relevant knowledge, that is better working model. For instance, when the pieces on the chess board were placed randomly, it was seen that both amateur and professional chess players remembered position of about 14 pieces on the board. However, when an actual chess board of a live game ( in between) was shown to amateur and professional chess players, professional chess players remembered all the pieces on the board, while amateurs could remember half of the pieces on the board.*
Conclusion
As your child is still studying and developing his 'knowledge', you are more concerned in helping your child develop his journey from data > information> knowledge. A skillful teacher can help your child build this chain better.
And because we build knowledge from one level to another in a chain, not understanding arithmetic in the 5th class creates difficulty in understanding arithmetic in 6th class. At this time, your child needs individual customised 'guidance' to identify and rectify his chain; not a coaching class that teaches the entire class of students. Later, we shall see what skillful teachers do differently.
From the above discussion, you would also appreciate that a coaching class may help your child get better marks, not necessarily gain better knowledge, because the actions for gaining more knowledge are not similar to actions for getting more marks. And remember, both are necessary: marks for short-term, and knowledge for long-term purpose.
You would also appreciate now that Internet only presents 'data' to your child. To convert that data into knowledge or action requires a huge degree of effort. Please do not ask your child to surf internet to decide which discipline he should choose in his life, because internet just provides data on different disciplines, not even information.
* Talent is overrated: Geoff Colwin
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