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I am using a chevron for hiding and collapsing an area on my interface. I have found versions of chevrons out there that use 2, and others that use a single:

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Is there any standard or reason to favor one over the other?

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My only comment would be for the Web when using horizontal chevrons like this: « Left and Right » to use the double (if done using text). The reason is that often a single less-than or greater-than character can be mistaken as an HTML parsing glitch and thus looks odd > – scunliffe Aug 23 '11 at 18:01
Thanks. So it definitely seems like 2 is the way to go! – Matt Rockwell Aug 23 '11 at 18:10
@scunfliffe +1 agreed, the double chevron » simply looks better than the > many website have used the double chevron in their text links/buttons for this reason – SampleJACK Aug 23 '11 at 18:34
I was about to answer...then I lost interest. Let the graphic designer choose. – Glen Lipka Aug 24 '11 at 0:52

1 Answer

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I highly recommend doing some A/B testing on simple things like these. That being said, they wont make a significant difference between users unless there is some ambiguity in the interface.

Typically I'd use the double-chevron when the distance of collapse is larger (>50% of interface size), and the single when the distance is smaller (<25%).

You might have noticed that there's a gap from 25–50%, where I use my gut instinct.

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+1 Awesome thanks! I was leaning toward double, and yes it is collapsing about 1/3, so win/win there. – Matt Rockwell Aug 23 '11 at 17:54
I don't see how A/B testing is going to provide any useful results whatsoever if that's the only change being tested. – Charles Boyung Aug 24 '11 at 15:42
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@Charles Boyung, A/B testing is just testing usage between two options. It doesn't have to be A/B/N testing for this case. All I was saying was to try it both ways and see which one works better. – zzzzBov Aug 24 '11 at 15:43
@zzzzBov - I know what A/B testing is. I'm saying that with something so trivial as this, you won't get any significant data to prove one is more usable than the other. – Charles Boyung Aug 24 '11 at 15:44
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@Charles Boyung, Rather than assume that you wont get any significant data, run a test and see whether the results indicate that there isn't a significant difference. – zzzzBov Aug 24 '11 at 15:46

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