The Power of Distributed Practice
By Bryan Caplan
If highlighting doesn’t help students learn, what does? According to Dunlosky et al.’s “Improving Students’ Learning With Effective Learning Techniques” (Psychological Science, 2013), one of the most effective pedagogical techniques is distributed practice. Description:
To-be-learned material is often encountered on more than one occasion, such as when students review their notes and then later use flashcards to restudy the materials, or when a topic is covered in class and then later studied in a textbook. Even so, students mass much of their study prior to tests and believe that this popular cramming strategy is effective. Although cramming is better than not studying at all in the short term, given the same amount of time for study, would students be better off spreading out their study of content? The answer to this question is a resounding “yes.” The term distributed practice
effect refers to the finding that distributing learning over time (either within a single study session or across sessions) typically benefits long-term retention more than does massing learning opportunities back-to-back or in relatively close succession.
Some typical results:
To illustrate the issues involved, we begin with a description of a classic experiment on distributed practice, in which students learned translations of Spanish words to criterion in an original session (Bahrick, 1979). Students then participated in six additional sessions in which they had the chance to retrieve and relearn the translations (feedback was provided). Figure 10 presents results from this study. In the zero-spacing condition (represented by the circles in Fig. 10), the learning sessions were back-to-back, and learning was rapid across the six massed sessions. In the 1-day condition (represented by the squares in Fig. 10), learning sessions were spaced 1 day apart, resulting in slightly more forgetting across sessions (i.e., lower performance on the initial test in each session) than in the zero-spacing condition, but students in the 1-day condition still obtained almost perfect accuracy by the sixth session. In contrast, when learning sessions were separated by 30 days, forgetting was much greater across sessions, and initial test performance did not reach the level observed in the other two conditions, even after six sessions (see triangles in Fig. 10). The key point for our present purposes is that the pattern reversed on the final test 30 days later, such that the best retention of the translations was observed in the condition in which relearning sessions had been separated by 30 days. That is, the condition with the most intersession forgetting yielded the greatest long-term retention. Spaced practice (1 day or 30 days) was superior to massed practice (0 days), and the benefit was greater following a longer lag (30 days)
than a shorter lag (1 day).
On the basis of the available evidence, we rate distributed practice as having high utility: It works across students of different ages, with a wide variety of materials, on the majority of standard laboratory measures, and over long delays. It is easy to implement (although it may require some training) and has been used successfully in a number of classroom studies. Although less research has examined distributed-practice effects using complex materials, the existing classroom studies have suggested that distributed practice should work for complex materials as well.
P.S. For a summary of all of Dunlosky et al.’s findings,
HT: Nathaniel Bechhofer