Im doing a relatively simple report/project in my science class (8th grade) on the efficiencies of various sorting algorithms, and I need to explain Big-O notation in a way which is:

1) Easy for a middle aged teacher who's knowledge of a computer pretty much stops at " It uses electricity"

and

2) Is compact enough to be able to put onto a poster board that people don't give up on reading it and walk away.

So what i've come up with so far is

Any suggestions as to how I could make this better, and (even better) is anything up there wrong?Big O gives the upper bound for time complexity of an algorithm. For example, an algorithm that is O(n) (where n is the number of items to be processed) means that the highest amount of instructions executed is equal to the number of instructions in the algorithm. If an algorithm is O(n^2), that would mean that the highest number of instructions executed is equal to the number of instructions in the program squared.