Direct and indirect effects of fluid intelligence on the retrieval practice effect.
Marcos Felipe Rodrigues de Lima1, Luciano Grüdtner Buratto1
1Departamento de Processos Psicologicos Basicos, Instituto de Psicologia, Universidade de Brasulia.
Fluid intelligence (gF) influences how people learn from retrieval practice, especially with difficult material. Higher gF aids learning during practice, indirectly boosting the retrieval practice effect for complex information.
Area of Science:
- Cognitive Psychology
- Educational Psychology
- Neuroscience
Background:
- Retrieval practice with feedback is a powerful learning strategy.
- Individual differences in fluid intelligence (gF) may modulate learning from retrieval practice.
- Previous research suggests gF interacts with item difficulty in retrieval practice effects.
Purpose of the Study:
- To generalize findings on the interaction between gF, item difficulty, and retrieval practice effects.
- To investigate the relationship between gF and learning gains during the practice phase.
- To examine the mediating role of practice performance in the gF-retrieval practice effect relationship.
Main Methods:
- 144 participants studied word pairs, followed by restudy or retrieval practice with feedback.
- Cued-recall and fluid intelligence (gF) tests were administered.
- Analysis focused on retrieval practice effects, practice performance, and their relationship with gF.
Main Results:
- Findings on the interaction between gF and item difficulty in retrieval practice were generalized.
- Positive correlations were observed between gF and the number of items recalled during practice.
- Fluid intelligence indirectly influenced the retrieval practice effect, mediated by practice performance.
Conclusions:
- Fluid intelligence plays a significant role in optimizing learning from retrieval practice, particularly for challenging content.
- Individuals with higher gF may employ more effective cognitive strategies during learning and practice.
- Future research should explore mediator generation, retrieval opportunities, and criterion-based learning.
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