Transfer of Learning Between Solid Modelers: An Investigation of Icon Recognition

Citation:
Rutkowski R, Okudan Gül E, Ogot M. "Transfer of Learning Between Solid Modelers: An Investigation of Icon Recognition." age. 2005;10:1.

Abstract:

Selecting the right solid modeling software is a complex, multi-criteria decision making problem.
There are many issues a decision-maker needs to take into account, such as ease of learning,
educational materials built into the software, learning curve issues, performance of the software
for different solid modeling functions, operations and utilities, and cost. Beyond selecting the
right software, the decision-maker should also be concerned about (1) conceptual learning of the
solid modeling topics while “the right software” is being used, and (2) transfer of conceptual
learning between solid modelers. This is because a sound conceptual learning might increase the
probability of learning another solid modeling software in less time.

Accordingly this paper investigates the impact of icon recognition as an aid to transfer
conceptual learning between solid modelers. The investigation includes a review of the literature
on icon design and usage as it relates to solid modeling, in addition to an experiment in which
the icon recognition correctness and duration for over 20 operation icons were compared across
two modelers. The results shed light into the impact of icon designs on the transfer of learning
between solid modelers using the correct recognition counts as the transfer measure.

Notes:

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