In the present article, we “deconstructed” the self-directed memory advantage and found that simply being able to control the timing of study led to recognition memory advantages. After replicating the basic advantage in Experiment 1, we found that controlling for attentional differences between conditions slightly improved the recognition of items from yoked study, but eliminated any differences in spatial memory (Exp. 2). In subsequent experiments, the self-directed advantage was preserved after removing learners’ ability to decide which items to study (Exp. 3) and how long to study each item (Exp. 4).
Across all four experiments, we found surprisingly consistent evidence of a recognition memory advantage for self-directed study. Similar patterns have recently been observed in a range of tasks including object identification (Craddock, Martinovic, & Lawson, 2011), memory for 3-D faces or objects (Harman et al., 1999; Liu et al., 2007; Meijer & Van der Lubbe, 2011), and spatial learning (Chrastil & Warren, 2012; Luursema & Verwey, 2011; Plancher et al., 2013). However, the mechanism behind these effects has been unclear because self-directed conditions generally differ from passive observation in a variety of ways, each of which could potentially influence memory. Like other examples of goal-directed behavior, self-directed study entails a hierarchy of cognitive control processes (Botvinick, 2008). The present study highlighted the distinction between decisions about the content of study (a higher-level process) and coordination of the study experience with attention (a lower-level process). At the higher level, people may select information so as to maximize the number of items that can be memorized (e.g., preferring to study easy items first; Metcalfe, 2002) or to focus on items for which their existing memory is poor (Metcalfe & Finn, 2008). At the lower level, each study episode may require decisions about its onset and duration, and memory is tied to attentional and motivational processes involved in the execution of those decisions (Chun & Turk-Browne, 2007). Our results suggest that this kind of low-level control is sufficient to enhance recognition memory for visual objects.
Although we found a consistent advantage in terms of recognition memory, the effect on spatial recall was much less clear. In Experiment 1, we found improved spatial memory from self-directed study (replicating the finding from Voss et al. 2011b). In subsequent experiments in which study sequences were more constrained (due to precuing or fixed search paths), and thus the orientation of attention was better matched between conditions, the same effect was either absent or inconsistent across different analyses. It is possible that reducing self-directed learners’ control over window movements led to less processing of spatial information; however, it is important to note that the need to make spatial decisions in Experiment 2 did not lead to any differences in spatial recall. Overall, our results add to evidence that a self-directed advantage for spatial memory is relatively inconsistent across different tasks (Chrastil & Warren, 2012), and suggest that it may closely depend on the nature of exploration in a given environment.
Our results also differed from those of Voss et al. (2011b, c), in that we did not find a larger self-directed advantage for items studied more often (Exps. 1–3) or that were quickly revisited (Exp. 1). Instead, additional study led to better memory regardless of encoding condition. One explanation for this discrepancy is that it was easier for the yoked learners in our task to coordinate attention with the study sequence, and as a result they also benefited from more exposure to an item. A selective benefit for self-directed study might occur in situations in which cues are not available to help yoked observers in the same way, but our findings suggest that such a pattern results from differences in coordination of attention rather than arising from a decision-making process that is only present during self-directed study.
What causes the recognition advantage for self-directed study?
We found that the self-directed advantage was present when control was limited to choosing when to reveal the next item, suggesting that during self-directed blocks participants were better able to coordinate new presentations with their own preparatory state. Increasing evidence indicates that prestimulus neural activity can predict subsequent memory (Guderian, Schott, Richardson-Klavehn, & Düzel, 2009; Otten, Quayle, Akram, Ditewig, & Rugg, 2006; Yoo et al., 2011), and that this activity is modulated by motivational factors including the anticipation of reward (Gruber & Otten, 2010). Self-directed learning might interact with these processes in a number of ways. One possibility is that learners monitor ongoing fluctuations in their internal state (e.g., due to distraction or mind-wandering) and can schedule new episodes in an adaptive manner. Alternatively, decisions to begin a new study episode might play a causal role in initiating those attentional or mnemonic processes.
One objection may be that during yoked blocks participants were not required to make a response, raising the possibility that the advantages were related to executing motor responses. However, we think it unlikely that the motor component can account for the memory enhancement. Voss et al. (2011b), Exp. 2 compared yoked observation with a “manual” condition that required key presses in response to an external cue in order to move the window along a predefined path. They found no advantage for this condition, with recognition performance similar to that of participants in our yoked condition. Other comparisons of self-directed and yoked study that included a secondary task in order to control attention and motor activity across conditions have also found advantages for active control (Liu et al., 2007; Meijer & Van der Lubbe, 2011).
It would be hard to argue against the hypothesis that selecting content during learning can influence later memory. For example, in richer contexts in which materials vary more in their difficulty (e.g., studying a textbook), an advantage from strategic selection of information would be expected to play a larger role. It is likely that the participants in Experiments 1 and 2 were engaged in strategic decision-making about how to navigate the array or making judgments about which items required further study. Collectively, however, our experiments showed that the self-directed advantage was maintained after removing elements of control that would allow the learner to make memory-based decisions about what to study and for how long.
Deconstructing self-directed study using yoked designs
The purpose of “yoked” experimental designs is to equate the content of study while isolating the impact of decision-making on performance. As we have demonstrated, comparing active exploration and passive observation via this method requires careful consideration of the many ways in which these conditions differ, particularly when the outcome of interest is subsequent memory. Although our experiments were based on the design of Voss et al. (2011b), a number of other examples of yoked designs have suffered from the same confound that we have described. For example, Meijer & Van der Lubbe (2011) used a task in which the goal was to memorize a set of 3-D objects. During self-directed study, the learners interacted with an object by rotating it with a mouse, whereas in yoked study they passively observed the interaction of another participant. The results showed a consistent benefit for self-directed study in terms of recognition, but it was unclear whether this advantage was related to low-level processes related to the interaction, or to higher-level metacognitive control (e.g., exploring parts of the object that were poorly encoded).
Rather than treating self-directed study as a unitary process, a more productive approach may be to decompose it into a hierarchy of control processes. A yoked design may be useful for testing the effects of individual decision-making processes while ensuring that the “passive” condition also experiences the outcomes of those decisions, but it is important that the influence of other forms of adaptive control is controlled for in the design. For example, the effect of high-level decision-making about the content of study may be best studied in paradigms in which self-directed learners cannot control the dynamics of individual study episodes (e.g., the honor/dishonor paradigm, in which the decision to study something is separated from the actual study opportunity; Kornell & Metcalfe, 2006).
Of course, comparing fully self-directed study with passive observation can reveal the magnitude of an advantage in a given learning problem, which may be especially relevant for educational contexts in which the most common format may be passive observation (e.g., viewing lectures). Our results add further insight to these comparisons, however, by revealing the extent to which different forms of “active learning” lead to differences in performance. Whereas people may be biased in how they make high-level decisions about how to sequence study episodes (Bjork et al., 2013), our results show that simply allowing people to control the temporal dynamics of study episodes may have widespread benefits for learning and memory.