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Effects of model-based and memory-based processing on speed and accuracy of grammar string generation
Thomas J Domangue1, Robert C Mathews, Ron Sun
1Department of Psychology, Lousiana State University, Baton Rouge, LA 70803, USA.
Journal of Experimental Psychology. Learning, Memory, and Cognition
|September 10, 2004
Summary
Learners utilize conscious mental models for slow, accurate skill performance. Instance-based memory training yields faster, less accurate results, preferred by participants.
Area of Science:
- Cognitive Psychology
- Skill Acquisition
- Learning Science
Background:
- Skill performance relies on two knowledge types: conscious mental models and memory-based instances.
- Understanding how training influences the use of these knowledge types is crucial for effective learning.
Purpose of the Study:
- To investigate the impact of training conditions on the availability and utilization of model-based versus memory-based knowledge.
- To examine the effects of different training methods on the speed and accuracy of skill execution.
Main Methods:
- Three experiments manipulated training to emphasize either model-based or memory-based knowledge of an artificial grammar.
- Participants generated letter sequences, with performance measured by speed and accuracy.
Main Results:
- Model-based training resulted in slow, accurate performance.
- Memory-based training led to faster, less accurate performance, optimal when high accuracy wasn't critical.
- Participants showed a preference for memory-based knowledge when both training types were available.
- Model-based accuracy diminished over a retention interval.
Conclusions:
- Training modality significantly influences the type of knowledge (model-based vs. memory-based) employed in skill execution.
- Memory-based knowledge facilitates faster performance, while model-based knowledge supports higher accuracy.
- Learner preference and knowledge decay over time are important factors in skill retention and application.