exercises

9. evaluation techniques

EXERCISE 9.3

In Section 9.4.2 (An example: evaluating icon designs), we saw that the observed results could be the result of interference. Can you think of alternative designs that may make this less likely? Remember that individual variation was very high, so you must retain a within-subjects design, but you may perform more tests on each participant.

answer

Three possible ways of reducing interference are:

  • During the initial training period, swap back and forth between learning the two sets of icons, with the aim of getting the subjects used to swapping between the two sets of remembered icons. However, this design could be argued to suffer the same flaws as the original. If the abstract icons had been taught in isolation perhaps they might have fared far better.
  • We could invent a third set of 'random' icons (call them R). We could then interpose them in the experiment, that is present the icons in the orders RARN and RNRA. The intention is to swamp any transfer effect in the 'noise' of the random icons. It could be argued that our experiment then measures the robustness of the icon sets to such 'noise'!
  • We could give the subjects multiple presentations, for example ANAN and NANA presentation orders. This would not remove transfer effects, but it would give us some way to quantify them. Imagine that in the ANAN group the second presentation of the abstract icons was significantly worse than the first, but there was not a similar effect for natural icons in the NANA group. This would give us both positive evidence of a transfer effect, and perhaps some quantitative measure. However, even going from this additional evidence to a strong conclusion will be difficult.

Notice that all the above measures require additional subject time and one has to constantly weigh up the advantages of richer experiments against those of larger subject groups.

Other exercises in this chapter

ex.9.1 (ans), ex.9.2 (ans), ex.9.3 (ans), ex.9.4 (ans), ex.9.5 (ans), ex.9.6 (tut), ex.9.7 (tut)

all exercises for this chapter