Boxes and Arrows: Comments by Matt Queen

Matt Queen — Fri, 26 Jan 2007 14:52:31 GMT

I read this in a section titled “Highest-rated suggestions.” I thought that is was an invitation to write this article. So I clicked on the link “Submit your story now” under “Write for Us.” To my shock, my post appeared in the suggestions section! (Along with yours). After reading a bit about the new review process, I see that the site inadvertently lead me to step on Scott’s toes. Of course you can’t delete posts, so I’ll just request my post be deleted. Feel free to email me to compare notes before your article draft if you’d like. Sorry for the confusion.

Matt Queen
queen@synergia.com

Matt Queen — Fri, 26 Jan 2007 14:52:31 GMT

Sorry, I’d like to rescind on this offer.

Matt

Matt Queen — Fri, 26 Jan 2007 14:52:32 GMT

Thanks Liz

Matt Queen — Wed, 23 May 2007 13:17:03 GMT

Glad I could help with the lingo! There is another distinction though. Suppose you ‘diagram’ 1 user during a session. I would be inclined to call that a flow diagram too! However, suppose you diagram 10 users? Then, user cognitive states like “edit list for X” becomes, “edit” as more users exhibit the same behavior. Then, you get some predictability (with a level of abstraction). More users will do this edit stage! As soon as corroborated predictability sets in … then it’s a model. Intuitively, the phrase “model predictions” is commonly used with that same meaning. BTW, that speech always gets a standing ovation :)

Matt Queen — Fri, 26 Jan 2007 14:52:32 GMT

Of this you speak the truth. And, your comment, ”... believing they will get a ‘free design’ and ‘save money’ having the programmers sort of ‘design-while-coding’.”—sounds like the voice of experience :)

That is a case study I’d like to read.

Matt Queen — Fri, 26 Jan 2007 14:52:37 GMT

Hi Amanda. One way you can coerce your concerns into a research question (fit to write and article about) would be to express it as the following question: “What do users need but seldom ask for—and why?”

Your answers might relate to how user interviews are structured, how data was collected, how stake holder interpretations developed, how much stake holders actually care about user data, etc. In short, this research question is fairly open and has many possible directions. The answers would be interesting to read about. If you could investigate answers to the research question and present the results of your investigation in a meaningful case study, this research will fly!

I’d be happy to be a good colleague and trade ideas about this subject with you in prep for your investigation—send me email.

mqn at u.washington.edu

Matt Queen — Fri, 26 Jan 2007 14:52:37 GMT

Your concerns seem more closely related to semiotics. I am certainly no semiotics expert. Also, I agree with your comments about the usefulness of icons on the web. I completed a draft of this article a few days ago, here is an excerpt that explains a use and setting for this analysis:

“Systems used by first responders in hazardous materials incidents (see MARPLOT for example) rely on icon design to signify entity classification (e.g. small icon of a schoolhouse) and level of critical danger to an entity (e.g. a school icon is painted red on a map). Immediately recognizing danger to a school amongst lumber yards, garbage dumps, and plant nurseries is imperative. Any time slip in the search and discrimination task could delay notification and evacuation of hundreds of children. How then can we diagnose problems with icons that fail in this regard?”

There are a host of web applications that fit this characterization:
http://yosemite.epa.gov/oswer/ceppoweb.nsf/content/ds-noe…

I agree the study of semiotics is important yet the field is not very well worked out. There are some good authors to recommend though:

Knowlton, J.Q. (1966). On the Definition of “Picture.” AV Communication, 14, 157-183.

Or for review of the seminal lit.

Anglin, G., Towers, R., & Levie, H. (1996). Visual message design and learning: The role of static and dynamic illustrations. In D.H. Jonassen (Ed.), Handbook of Research for Educational Communications and Technology. New York: Simon and Schuster Macmillan.

Matt Queen — Fri, 26 Jan 2007 14:52:46 GMT

small-quick-dirty explorations are my favorite. I would love to see this written up with a discussion unpacking these results.

Matt Queen — Fri, 26 Jan 2007 14:52:47 GMT

Also, glad to see Fitt’s law being used for its actual purpose! The law gets tossed around so much.

Matt Queen — Tue, 02 Sep 2008 06:21:35 GMT

I haven’t heard of The Bridge though many similar methods exist in the expert systems lit. Practice mapping, for example, is a much more complex version of interaction modeling that often involves decision analysis techniques in lieu of the cognitive bias warrants I described above. Was there any mention of whether The Bridge enjoyed any success (case studies, anecdotes, etc.)?

Matt Queen — Fri, 26 Jan 2007 14:52:50 GMT

The most well known HCI work involving Fitt’s law was done at Xerox—truthfully, I haven’t heard of any other major studies that would provide benchmarks. Perhaps you could follow from here:
http://en.wikipedia.org/wiki/Fitts‘_law

and find something though.

Matt Queen — Fri, 26 Jan 2007 14:53:03 GMT

Glad to see this is such a hit! I’m glad it promises to be useful for folks. As for answers to the growing list of questions:
About using color to lead the eye … using color is referred to as “creating a feature based search” (the feature being color, yet it could be – say, shape [find the triangle amidst the cluster of circles]). However, using color only provides a purposeful difference in the P channel because the M channel is luminance only. That is why unique low spatial frequencies help. They act to provide purposeful differences in the dual pathways of a users visual system. Also, though a sub population of users might be color blind, a better reason to provide low spatial frequency differences as well as color differences is that we actually don’t see in color in peripheral vision! I know this sounds crazy but try this: open a document up in your favorite text editor. Choose a document that has a full page of text. Then, select a word close to the top left of the page and change the color of the word letters (try blue and red for example). Now, center your focus on a word toward the middle or bottom right of the page. Can you see the color of the word? Probably not. In fact you can play around to see exactly where you can’t see the color anymore in terms of how close you place your focal point. Now imagine your user using the application, while they are in the context of reviewing content, categorizing tags, and whatnot – could they “see” the color differences?

About the non standard icon sizes and visual angle equation … I found this site by googling “size-distance-invariance equation,”

http://retina.anatomy.upenn.edu/~bart/scriptie.html

scroll to the passage that begins with, “Later theories of perception yield the well-known size-distance-invariance hypothesis.” That website uses the same Gilinsky article I pulled the equation from yet makes some elaborations for smaller visual angle sizes (either far away from icon or icon is really small).

Spacing in icon discrimination trials … Here is where things get sticky. The display I used provides enough space to require the user to shift their eyes to view the stimulus, match, and distracter images (that is at least 2 fixation points assuming that the user is sure the first image and second image are the same). I wanted the user to hold the image in a visual buffer for a split second and compare an image to the buffer to truly examine the uniqueness of the spatial frequency component. There are some issues with this approach. Someone might argue that low frequency information is not held as well in the visual iconic store (look at something really bright, then close your eyes and watch it fade away from the visual iconic store). Is that splitting hairs, being too anal? I don’t know. Yet, there are far more pressing issues that preclude this experimental setup from being rigorously academic – namely, there is no objective way to measure the distinctness of a visual pattern design (I just heard all the designers cheer, and I kind of cheered myself just then). Although, If a brave soul is interested, I have some ideas of how you might get around that and fit this together for something more scientific (has do with krigging coefficients … I do love a teaser).

Anyhow, I’ll answer any and all questions and I’m glad you folks find this useful. Have fun.

Matt Queen — Fri, 26 Jan 2007 14:53:03 GMT

I just mentioned in an email to Dustin Hamilton that he hit the nail on the head, distance filtering of icons is an evaluative technique—not a design technique. My knee-jerk reaction of how to coerce this method into a design tool is to create a plug-in for Photoshop or GIMP (preferably) that would allow an auto-updated window of the design space filtered at set distances. That way all design decisions (small and large) could be made in the context of the filtered frequency views. I imagine there is someone out there with enough talent and time to create such a tool. It seems like it would be useful.

Matt Queen — Fri, 26 Jan 2007 14:53:04 GMT

I’m not sure whether designers rely too much on icons though I know they are a popular way to represent actions (cut/paste) and categories (media file vs. word document) – which requires care (ex. “is this icon on the web an action or a category, or both?”).
The necessity of having 20 visually unique and distinguishable icons sounds like quite a design problem … the main problem being, “why is that a necessity?” Suppose we cut this 20 to 15 and partition them out. For example we have a web application that has 3 modes while each mode has a toolbar holding 5 icons. The user only sees 5 icons in the toolbar at time and we will decide that icons appearing in menus are preclassified differently in the mind of the user than icons that persist in the UI. The point isn’t that a user can distinguish between a low frequency representation of an icon in the first toolset and the second. The point is that they can easily distinguish between the currently available tools (then we leave the problems arising from modal issues to another type of analysis). Finally, suppose we would rather not rely on icons (after all they can be expensive) and opt for well thought out labels in our UI. Believe it or not, labels have low frequency components as well! The large letter forms of capitols, risers, and descenders (ex. “X”, “t”, “g”) coupled with the amount of kerning and line space contributes to the recognition of labels. We use the P channel (specifically, “detailed shape”) to read the labels yet rely on low frequency components to aide the identification of a word. Some reading research suggests that we actually don’t “read” all the letters in a word. Rather, we recognize a word by its large distinguishing visual features. We could argue that large visually distinguishing features are low frequency components. Does this make sense (perhaps improve the usefulness of this technique for you at all?).

Matt Queen — Fri, 26 Jan 2007 14:53:04 GMT

Yes I agree Rex. The current state of knowledge in neuroscience and cognition supports the mix of top down (recognizing/identifying) and bottom up (sensing/describing). Following the discussion into icons and signs, you could look up the works of Joan Peeck, “The Role of Illustrations in Processing and Remembering Illustrated Text” and Robert B. Kozma’s “Learning With Media.” I think those are good references for looking at icons and illustrations. They aren’t neuroscience so you won’t find any discussion of retinal architecture but they are chalk full of wisdom about how users learn and absorb information from media. As for research specific to icons and spatial frequency – as far as I know – you just read it! If others have found articles of this nature post them: I’d be interested.