Attention and the forward testing effect.

Memory retrieval affects subsequent memory in both positive (e.g., the testing effect) and negative (e.

Prior knowledge and new learning: An experimental study of domain-specific knowledge.

It is commonly claimed that higher domain knowledge enhances new learning-the knowledge-is-power hypothesis. However, a recent meta-analysis (Simonsmeier et al., 2022) has challenged this idea, finding no overall relationship between prior knowledge and new learning across hundreds of highly variable effect sizes.

Transitive inference and the testing effect: Retrieval practice impairs transitive inference.

There is substantial interest in the extent to which the testing effect (the finding that retrieval practice enhances memory) extends to more complex forms of learning, especially those entailing greater element interactivity. Transitive inference (TI) requires just such interactivity, in which information must be combined across multiple learning elements or premises to extract an underlying structure. Picklesimer et al.

Attention, the testing effect, and retrieval-induced forgetting: Distraction dissociates the positive and negative effects of retrieval on subsequent memory.

Memory retrieval affects subsequent memory in ways both positive (e.g., the testing effect) and negative (e.

Levels of retrieval and the testing effect.

Retrieval enhances subsequent memory more than restudy (i.e., the testing effect), demonstrating the encoding (or reencoding) effects of retrieval.

The Effect of Retrieval Practice on Transitive Inference.

Compared to restudying, retrieval practice has often been found to enhance memory (the ). 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.

Assessing why the testing effect is moderated by experimental design.

The testing effect is 1 of several memory effects moderated by experimental design, such that the effect on free recall is larger in a mixed-list than pure-list design (Mulligan, Susser, & Smith, 2016). The current experiments assess hypotheses regarding why this pattern is found. Three extant accounts of design effects (Nguyen & McDaniel, 2015) are the item-order account, the retrieval-distinctiveness account, and the rehearsal-borrowing account.

The testing effect under divided attention: Educational application.

In educational settings, tests are typically used to assess learning. However, research has also shown that tests can enhance retention, often to a greater degree than restudying (i.e.

Divided attention and the encoding effects of retrieval.

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.

The generation effect and experimental design.

The generation effect is moderated by experimental design, as are a number of other encoding variables, such that the generation effect recall is typically larger in mixed-list than pure-list designs. In typical experiments on design effects, each study list is followed by its own recall test. Rowland, Littrell-Baez, Sensenig, and DeLosh (2014) found that the testing effect was not moderated by experimental design using a procedures in which multiple study lists were followed by a single, end-of-session recall test over all lists.

The testing effect under divided attention.

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.

Finding faces among faces: human faces are located more quickly and accurately than other primate and mammal faces.

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).