Chunking as a characteristic of implicit motor learning

Abstract

Following early work by Masters (1992) a new literature has emerged in motor learning, which suggests that the way in which movements are acquired mitigates whether skill failure will occur under psychological pressure. This literature argues that in most instances skill failure occurs as a consequence of anxious performers monitoring and consciously controlling their movements. Implicit modes of learning prevent the accumulation of task relevant knowledge which can be held and manipulated by working memory, so avoiding default to conscious control. The mechanisms underlying this ‘robustness’ under pressure are not well understood. One technique, analogy learning, shown recently to result in implicit characteristics (Liao & Masters, 2001), may be enlightening. Two experiments are presented, which hypothesise that chunking is the mechanism which underlies the implicit characteristics of analogy learning. Chunking is a process in which discrete ‘bits’ of information are integrated into a new memory representation through learning. If chunking is the mechanism which underlies analogy learning, the analogy should chunk only fundamental technical information subsumed under the analogy (e.g., relevant ‘bits’ of information), since chunking occurs only when the discrete ‘bits’ of information are relevant or meaningful to the learning process. A test of this chunking hypothesis is that the analogy should be effective when the skill has been learned using relevant rather than irrelevant rules. The first experiment established the rules relevant to a right-angled triangle analogy for learning the topspin forehand drive in table tennis. In the second experiment, two groups of novices learned to hit the topspin forehand using either the analogy relevant or irrelevant rules prior to presentation of the analogy. Performance was then tested after presentation of the analogy. The results showed that, after the analogy was presented, learners who used the relevant rules exhibited robust performance under a secondary task load, whereas, those who used irrelevant rules did not. It was concluded that chunking may be the mechanism which underlies implicit processes in analogy learning.