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6.831 • User Interface Design and Implementation

Massachusetts Institute of Technology
Department of Electrical Engineering and Computer Science
Fall Semester, 2006

AC3: Fitts's Law

The point of this activity is to get a hands-on understanding of Fitts's Law. You need a web browser to run the experiment workbench; you'll find a link to it at the top of the 6.831 home page, or you can enter its URL directly:

1 Warmup

Using the initial settings of the workbench, try doing the task. Collect about 10 mouse clicks for the initial settings, and record the results below. Note that ID = log(D/S) and STDERR = STDEV / sqrt(N).

Size (S) Distance (D) Index of difficulty (ID) Count (N) Mean time (T) Standard deviation (STDEV) Standard error (STDERR)

2 Target Size and Distance

Use the workbench to run trials with targets of varying size or distance. If you're in the left half of the lecture room, from your point of view, you should vary the size. If you're in the right half, you should vary the distance.

Use at least 3 sizes or distances, and collect about 20 mouse click times for each size or distance. The output textbox holds 20 lines, so just fill it up. Keep both targets the same size in each trial. Don't try to save time by using targets of two different sizes at once. Vary geometrically (i.e., 1,2,4,8,... not 1,2,3,4,...). Keep the distance D significantly larger than the size S. The same person should do all 3 trials.

Record the results below. What kind of relationship should you see between the index of difficulty (ID) and the mean time (T)? Plot the points roughly in the space on the right to see if you get that relationship.


3 Nonsquare Targets Model

The targets we've used so far have been square. Now let's think about rectangular targets of size W by H, where W and H are significantly different. Think about how we explained Fitts's Law in terms of the human information processor model, and try to extend Fitts's Law to cover this case. Here are some possible hypotheses:

Write down your hypothesis (which may be one of the above, or completely different), and briefly justify it.

4 Nonsquare Targets Experiment

Now devise and run a set of trials to test the relationship between T, W, and H. For example, you might compare tall skinny targets and short fat targets.

Compute index of difficulty (ID) according to your hypothesized relationship from the previous problem. Plot your points roughly in the space on the right. Does your hypothesis look reasonable?