I always imagined that a steep learning curve was metaphorically like a hill that took increasing energy with increasing slope. Turns out that the axes of a learning curve are learning on the y axis and experience on the x axis. So if the curve is steep, you learned stuff quickly. Many other good examples in the article. May the steep curve be with you.
Steep learning curve just means learning quickly, usually I’ve heard it used for being /forced/ to learn quickly, as a type of hardship.
I disagree with the article that “steep learning curve” implies something learned easily, and neither does it imply something difficult to learn. It refers solely to rate of learning. Other interpretations are innumerate.
I have only ever heard 'steep learning curve' used to indicate that learning efforts have very small returns initially (think about 'how much you know' on the Y and 'competency' on the X)
Everyone seems to assume the curve starts to shoot up at x=0. I always imagined the steep learning curve's steepness as starting at x>0, thereby creating some stalling or slow growing plateau requiring the bulk of the effort before you reach a certain point where there's a huge, rewarding jump (some "aha" moment) that releases all the build up tension. Compare A (constant, please mentally unjag it) vs B (steep):
| A _.-----
| _/ /
| _/ /
| _/ /
|/ /
|----' B
+--------------
There could be delayed steepness, but I think most people would use "steep" to refer to those moments of struggle and effort along the way, rather than the "aha" feeling of suddenly elevated knowledge after the jump. I don't think there's a term for the latter, except maybe a "satisfying" learning curve.
Using the "hill" metaphor, the X-Axis would be "progress in carrying out the task" vs the Y-Axis "effort spent struggling to figure out what you need to do next".
I.e. a steep curve means a high ratio of time spent looking for answers / reading docs; a flat curve means you're proceeding with the task feeling productive.
I've mostly seen the term in regards to game design i.e. a game having a steep learning curve means that it's hard to get into because it requires the player to have a lot of understanding about the game's mechanics before the player is able to realize his/her intentions inside the game with predictable outcomes.
In that context having a "not so steep" learning curve can help players ease into a vast, previously unknown, ruleset much easier by introducing it piece by piece, instead of literally overwhelming the player by throwing all of it at him/her at once.
If i say that windsurfing "has a steep learning curve" i mean that to make progress, to move along the X, you must learn faster, move more quickly up the Y. It isnt that you do learn quickly, just that steady progress on one axis requires faster movement on the other. It's really three dimensional: experiance, knowledge, and the speed at which you want to move along those two.
That's not the common usage, though. What I hear most (and usually mean when I use the phrase) is that the initial phases of learning the basics is very difficult, but then after you have those down, moving on through more advanced material is comparatively easy.
> Gold standard. In the domains of psychological and psychiatric assessment, there are precious few, if any, genuine "gold standards." Essentially all measures, even those with high levels of validity for their intended purposes, are necessarily fallible indicators of their respective constructs.
The reason we refer to double blind trials as being the "gold standard" isn't to imply that they have some level of validity, but because they were popularized by Harry Gold.
The reason this list exists is to discourage phrases that are, among other things, misunderstood. So your argument that people don't understand the reference simply strengthens the case against using the phrase.
I can't help thinking that sometimes scientific and "lay" use of a word diverges beyond repair. With a linguistic hat on, who is to say who is right?
e.g. "energy", "weight", "hacker", and within the linked article "fetish". (In a sentence which also displays ignorance of the difference between smartphone and feature phone...)
The article is excellent, but I guess I'm saying in some cases you can try to re-educate while in others you just have to accept that there are multiple meanings of the same word.
Quoting some Dawkins on what "a gene for X" means:
When a geneticist speaks of a gene "for" red eyes in Drosophilia, [...] he is implicitly saying: there is variation in eye colour in the population; other things being equal, a fly with this gene is more likely to have red eyes than a fly without the gene. That is all that we ever mean by a gene "for" red eyes.
"Steep learning curve. Scores of authors use the phrase “steep learning curve” or “sharp learning curve” in reference to a skill that is difficult to master. For example, when referring to the difficulty of learning a complex surgical procedure (endoscopic pituitary surgery), one author team contended that it “requires a steep learning curve” (Koc et al., 2006, p. 299). Nevertheless, from the standpoint of learning theory, these and other authors have it backward, because a steep learning curve, i.e., a curve with a large positive slope, is associated with a skill that is acquired easily and rapidly (Hopper et al., 2007)."
Curve does not mean "slope". I feel like it's the "learning theory" folks that aught to change their terminology for this one.
It is interesting that the paper starts with a quote from Steven Pinker, who coined the term 'euphemism treadmill'. When you change language because it is occasionally misused you don't solve the problem, you just move it.
Not only you just move it, but you also contribute to it. What is worst, putting the government force behind it validates such motion and makes future precedent.
All in all, from a certain perspective it's a nice list, but keep a critical mind while reading it because the author sometimes seeks to rewrite the terms used to advance his own views on what is valid and what isn't.
I find it worrying that the buzzfeed template has found its way to ncbi.nlm.nih.gov. Granted, they did dedicate an entire paragraph to fifty different complicated topics, but the feeling is the same.
I think you'd be hard-pressed to find any similarity besides enumeration and HTML with the NIH article posted here and a listicle you'd find on Buzzfeed, much less find anything to worry about. It's well explained and referenced and features no graphics or clickbait text.
It's well referenced only on on a numeric scale; the breadth of topics makes the 209 links irrelevant. A great deal of the points are semantic in nature-- yes, It's not exactly correct to say that schizophrenia is "genetically determined" if genetics only are 90% responsible, so what? Yes, antidepressants are technically selective-serotonin-reuptake-inhibitors. Authors tend to use simpler and mostly-correct terms instead of very complicated but completely-correct terms in order to communicate their ideas properly. This is a necessary trade-off that is made when communicating with human language.
It's akin to clickbait in that it's inflammatory by design. "50 Psychological and psychiatric terms to avoid" or "25 Foods You'll Never Be Able To Eat Again", the point is to cheaply engage the reader with terms they probably use (or food they probably eat) in order to reel them in. Then you hammer the same point into dozens of different situations.
> A great deal of the points are semantic in nature
Yes, they are cautioning against using terms that are frequently misunderstood or encourage jumping to an incorrect conclusion.
> genetics only are 90% responsible
From section (1) of the paper:
>> Moreover, genome-wide association studies of major psychiatric disorders, such as schizophrenia and bipolar disorder, suggest that there are probably few or no genes of major effect
> so what?
Your suggestion that genetics could be "90% responsible" when available evidence is suggesting "few or no genes of major effect" is a good example of the kind of counterfactual belief that the paper is trying to fix.
> Yes, antidepressants are technically selective-serotonin-reuptake-inhibitors.
From section (2) of the paper:
>> some authors argue that these medications are considerably less efficacious than commonly claimed, and are beneficial for only severe, but not mild or moderate, depression, rendering the label of “antidepressant” potentially
Again, this isn't a minor technical quibble. The actual evidence for SSRIs (etc) having effects that counteract depression is thin and open to a lot of interpretation. Calling them "antidepressants" gives the incorrect, misleading impression that we know actually understand how depression works or how it is affected by these medications.
Gee, remember Letterman's top 10 lists, back before internet was a thing? Yeah, me too. Neither invented lists, though, and sometimes they are one of the more efficient ways to communicate information.
