Striking the Balance: How Variability Shapes Retrieval Practice and Worked Examples for Transfer Learning

The ability to generalize and apply knowledge to new situations is the hallmark of effective learning. There are multiple ways to improve learning towards generalization. Retrieval practice and worked examples have both been shown to improve learning, retention, and generalization. The literature on category learning also suggests that exposure to more varied examples, rather than the same example repeatedly, improves generalization. However, while retrieval practice is usually investigated with repeated examples, worked examples learning is usually investigated using varied content. Across two studies, we investigated how combining content variability with worked examples or retrieval practice promotes generalization when students receive initial instruction before practice (Experiment 1) and when they do not (Experiment 2). We found that when learners received initial instruction, retrieval practice led to better generalization compared to worked examples, regardless of whether the stimuli were repeated or varied. When initial instruction was not provided, worked examples resulted in better generalization than retrieval practice when items were repeated. However, retrieval practice produced comparable generalization to worked examples when items were varied. These findings suggest that variability supports generalization, particularly when learners must induce underlying rules, and that retrieval practice, traditionally associated with memory retention, can also facilitate inductive learning when applied to varied examples. This study emphasizes the importance of adapting learning strategies to align with the instructional context and task demands.