By duderbattalion 54 Comments
One of my professors brought up a very interesting point regarding the phrase "Steep learning curve" that is used quite often in videogame terminology. It always pisses him off when he hears people talking about having a hard time due to the "Steep learning curve". According to him, the steepness of the learning curve is actually a measure of how easy it is to learn something. In other words, the shallower a curve, the harder it is to learn that operation.
So next time you talk about how god damn difficult Super Meat Boy is, remember .. the difficulty curve is shallow, not steep !
P.S: The axises of the graph are based on Machine learning conventions. Though I can see a few ways to contradict my own point .. but I'd love to hear your take or counter take on it.
UPDATE: Holy crap .. and here I thought no one reads a word I post ;)
Actually, I think I need to clarify a couple of things I wrote above. As you can see in the P.S section of the blog, I was having a discussion about Machine learning where a learning curve IS measured as a graph of performance over time. Of course, this is not the way we use it in general conversation. I think Onno10 hit it on the head with this graph here:
If you look at it, both graphs are correct in their own sense. They just show things in a different manner. The measure of performance is inversely proportional to difficulty, so of course the graphs are antithetical to each other ! In mathematics, I guess it's easier to get a measure of performance as compared to getting a measure of difficulty, hence we use the "inverted" graph of a learning curve, so to say. And of course, an assumption being made is that performance is a truer measure of determining how much you have learned. Again, this is open to debate and I am much aware that when someone uses the aforementioned phrase, they are talking about the amount of things to learn versus time, instead of a performance chart.
It's just a different take on viewing something that we are so used to viewing in a completely opposite manner. I am glad it generated such a discussion.
Good luck, have Batman !
UPDATE 2: Again, I re-iterate .. the concept of the learning curve above was in the context of machine learning. Performance .. easier to evaluate, Difficulty .. not so much. Hence the inverted y-axis. In our day to day conversation, sure .. difficulty vs time is the accepted norm.
Also, I do not understand the concept of a wrong Y-axis. It's a graph representation where I choose to represent learning as a function of performance instead of things to learn. Both the graphs work, just that they show things in a different way.