An expertise reversal effect of segmentation in learning from animated worked-out examples
Many animations impose a high cognitive load due to the transience of information, which often hampers learning. Segmentation, that is presenting animations in pieces (i.e., segments), has been proposed as a means to reduce this high cognitive load. The expertise reversal effect shows, however, that design measures that have a positive effect on cognitive load and learning for students with lower levels of prior knowledge, might not be effective, or might even have a negative effect on cognitive load and learning for students with higher levels of prior knowledge. This experiment with animated worked-out examples showed an expertise reversal effect of segmentation: segmented animations were more efficient than continuous animations (i.e., equal test performance with lower investment of mental effort during learning) for students with lower levels of prior knowledge, but not for students with higher levels of prior knowledge.
|Keywords||Cognitive load, Expertise reversal effect, Instructional animations, Multimedia learning, Segmentation|
|Persistent URL||dx.doi.org/10.1016/j.chb.2010.05.011, hdl.handle.net/1765/63171|
|Journal||Computers in Human Behavior|
Spanjers, I.A.E, Wouters, P.J, van Gog, T.A.J.M, & van Merriënboer, J.J.G. (2011). An expertise reversal effect of segmentation in learning from animated worked-out examples. Computers in Human Behavior, 27(1), 46–52. doi:10.1016/j.chb.2010.05.011