Memory retrieval often enhances later memory compared with restudying (i.e., the testing effect), indicating that retrieval does not simply reveal but also modifies memory representations. Dividing attention (DA) during encoding greatly disrupts later memory performance while DA during retrieval typically has modest effects-but what of the memory-modifying effects of retrieval? If these effects are similar to study-based encoding, they should be greatly disrupted by DA, a possibility consistent with elaborative and effortful accounts of the testing effect. Alternatively, the mnemonic consequences of retrieval may be largely resilient to distraction, like retrieval itself. In 3 experiments, participants studied word pairs (Phase 1) then engaged in restudy of some pairs and retrieval of others (Phase 2), followed by a final cued-recall test (Phase 3). Phase 2 restudy and retrieval occurred under full attention (FA) or DA. The experiments were designed to induce either material-specific (Experiments 1 and 2) or material-general (Experiment 3) interference, as well as to produce comparable secondary task performance between the restudy and retrieval groups (Experiments 2 and 3). Consistent with prior research, retrieval improved final recall (i.e., the testing effect) whereas DA disrupted final recall. Critically, the 2 factors interacted such that the negative effect of DA on final recall was substantial in the restudy condition but quite modest in the retrieval condition-resulting in a larger testing effect in the DA than FA condition. The encoding effects of retrieval seem resilient to distraction which has implications for theories of the testing effect. (PsycINFO Database Record

Abstract. Compared to restudying, retrieval practice has often been found to enhance memory (the testing effect). However, it has been proposed that materials with high element interactivity may not benefit from retrieval practice. Transitive inference (TI) requires just such interactivity, in which information must be combined across multiple learning elements or premises. The current study employed a 7-element TI paradigm in which participants initially learned a set of premises (e.g., A > B, B > C, C > D, etc.), then engaged in either restudy or retrieval practice with the premises, and then were given a final test that assessed memory for the original premises and one’s ability to make transitive inferences about them (e.g., to infer that B > D). Three experiments examined TI on final tests with retention intervals of a few minutes (Experiment 1), 2 days (Experiment 2), or up to a week (Experiment 3). Retrieval practice consistently failed to enhance transitive inference. Furthermore, retrieval practice significantly reduced TI in Experiment 1. Across experiments, TI was numerically worse in the retrieval-practice than restudy condition in 4 of 5 comparisons, and a small-scale meta-analysis revealed a significant negative effect of retrieval practice on TI.

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We tested the specificity of human face search efficiency by examining whether there is a broad window of detection for various face-like stimuli—human and animal faces—or whether own-species faces receive greater attentional allocation. We assessed the strength of the own-species face detection bias by testing whether human faces are located more efficiently than other animal faces, when presented among various other species’ faces, in heterogeneous 16-, 36-, and 64-item arrays. Across all array sizes, we found that, controlling for distractor type, human faces were located faster and more accurately than primate and mammal faces, and that, controlling for target type, searches were faster when distractors were human faces compared to animal faces, revealing more efficient processing of human faces regardless of their role as targets or distractors (Experiment 1). Critically, these effects remained when searches were for specific species’ faces (human, chimpanzee, otter), ruling out a category-level explanation (Experiment 2). Together, these results suggest that human faces may be processed more efficiently than animal faces, both when task-relevant (targets), and when task-irrelevant (distractors), even when in direct competition with other faces. These results suggest that there is not a broad window of detection for all face-like patterns, but that human adults process own-species’ faces more efficiently than other species’ faces. Such own-species search efficiencies may arise through experience with own-species faces throughout development, or may be privileged early in development, due to the evolutionary importance of conspecifics’ faces.

Retrieving from memory both reveals as well as modifies memory. It is important to understand how these encoding effects of retrieval differ from other forms of encoding. One possible difference relates to attention: divided attention is well known to disrupt memory encoding but typically has much less impact on memory retrieval. However, less is known about the relative attentional demands of the encoding consequences of retrieval. The current experiments examined retrieval-based encoding using free recall, a retrieval task purported to require substantial attentional resources. In three experiments, participants studied common category exemplars (Phase 1), restudied or freely recalled the exemplars (Phase 2), and then took a final free-recall test (Phase 3). Phase 2 occurred under full attention (FA) or divided attention (DA). In all three experiments, the negative effect of DA on final recall was significant in the restudy but not retrieval condition. The pattern persisted with short (Experiment 1) or long study lists (Experiment 2), requiring lesser or greater retrieval effort, and with multiple Phase 2 tests, permitting the development of more elaborate retrieval strategies (Experiment 3). The encoding effects of retrieval appear resilient to distraction, even using a memory task that is more effortful and easily disrupted by DA (i.e., free recall). In addition, these results are inconsistent with elaboration and effort accounts of retrieval-based learning.