Keep your heart with all vigilance,

for from it flow the springs of life.

Skill & Luck

Model Thinking is coming to an end! I've learned much from this course and the various models are going to be very helpful to think about and understand issues. Even so, it hasn't been easy and I am quite glad to have seen it to the end.  

This week, it's about Randomness which is highly relevant to skill and luck - to what extent is the outcome dependent on skill and luck respectively. This can be expressed by the following formula:

outcome = ๐‘ฅ๏นข๐œ€ 
Where ๐‘ฅ denotes the factors, including skill.
Where ๐œ€ denotes error, including luck.

Of interest is the paradox of skill: Among highly skilled individuals, the difference in outcome is more likely to be due to luck than it is to skill. While it is possible to show that this is true mathematically, we need only to think of examinations such as PSLE. The difference in scores among top students is more likely due to luck than it is to skill.  

That PSLE measures too finely has been raised and repeated by several ministers in recent months. That the difference in one mark between the top scorer and the second is of significance is hard to prove. To further discuss the result of this ranking would be flogging a dead horse. Instead, the discussion ought to focus on a viable alternative, specifically the way results are expressed.

Interestingly, as students progress to higher levels, assessment tools are more blunted. At the 'O' levels, there is no score and the results are expressed along a nine-scale grade from A1 to F9. At the 'A' levels, it is reduced to a six scale grade from A to U.   

The big lesson here is that while national examinations such as PSLE are necessary, we ought to be careful with the level of precision at which we measure. Measure too precisely and assessment becomes a record of the luck and variables that are beyond the student's control.  

Solow Growth Model and ICT

Detailed Description vs. Precise Definition