Veronica X. Yan

Type I error inflation in the traditional by-participant analysis to metamemory accuracy: a generalized mixed-effects model perspective.

In order to examine metacognitive accuracy (i.e., the relationship between metacognitive judgment and memory performance), researchers often rely on by-participant analysis, where metacognitive accuracy (e.g., resolution, as measured by the gamma coefficient or signal detection measures) is computed for each participant and the computed values are entered into group-level statistical tests such as the t test. In the current work, we argue that the by-participant analysis, regardless of the accuracy measurements used, would produce a substantial inflation of Type I error rates when a random item effect is present. A mixed-effects model is proposed as a way to effectively address the issue, and our simulation studies examining Type I error rates indeed showed superior performance of mixed-effects model analysis as compared to the conventional by-participant analysis. We also present real data applications to illustrate further strengths of mixed-effects model analysis. Our findings imply that caution is needed when using the by-participant analysis, and recommend the mixed-effects model analysis.

Multilevel Induction of Categories Venomous Snakes Hijack the Learning of Lower Category Levels

The induction of categories and concepts from examples—which plays an important role in how people come to organize and understand the world—can happen at multiple levels, but how do competing values at these different levels affect learning? Using perceptually rich images of snakes, we asked participants to attend to either the snakes’ specific genus or a broader categorization and then tested induction at both levels. We also varied the intrinsic value of the broader categorization (high value: whether the snake was venomous; low value: whether it was tropical). We found an interaction between study instruction and intrinsic value: Participants in the low-value condition were better able to induce the level they were instructed to attend to (i.e., genus or broader category) than to induce the level they were not instructed to attend to, whereas participants in the high-value condition, regardless of the level of categorization they were instructed to attend to, were significantly better at learning the broad categorization (for them, whether the snake was venomous) than were participants in the low-value condition. Our results suggest that intrinsically valuable features can disrupt the intentional learning of other, task-relevant information, but enhance the incidental learning of the same information.

An Identity-Based Motivation Framework for Self-Regulation

Will you be going to that networking lunch? Will you be tempted by a donut at 4 p.m.? Will you be doing homework at 9 p.m.? If, like many people, your responses are based on your gut sense of who y...

Study sequence matters for the inductive learning of cognitive concepts.

The sequence in which problems of different concepts are studied during instruction impacts concept learning. For example, several problems of a given concept can be studied together (blocking) or several problems of different concepts can be studied together (interleaving). In the current study, we demonstrate that the 2 sequences impact concept induction differently as they differ in the temporal spacing and the temporal juxtaposition of to-be-learned concept problems, and in the cognitive processes they recruit. Participants studied 6 problems of 3 different statistical concepts, and then were tested on their ability to correctly classify new problems on a final test. Interleaving problems of different to-be-learned concepts, rather than blocking problems by concept, enhanced classification performance, replicating the interleaving effect (Experiment 1). Introducing temporal spacing between successive problems decreased classification performance in the interleaved schedule—consistent with the discriminative-contrast hypothesis that interleaving fosters between-concept comparisons—and increased classification performance in the blocked schedule—consistent with the study-phase retrieval hypothesis that temporal spacing causes forgetting and subsequent retrieval enhances memory (Experiment 2). Temporally juxtaposing problems of concepts 3-at-a-time rather than 1-at-a-time improved overall classification performance, particularly in a blocked schedule—consistent with the commonality-abstraction hypothesis that blocking fosters within-concept comparisons (Experiment 3). All participants also completed a working memory capacity (WMC) task, findings of which suggest that the efficacy of the above study sequences may be related to individual differences in WMC.

Multilevel Induction of Categories

The induction of categories and concepts from examples—which plays an important role in how people come to organize and understand the world—can happen at multiple levels, but how do competing values at these different levels affect learning? Using perceptually rich images of snakes, we asked participants to attend to either the snakes’ specific genus or a broader categorization and then tested induction at both levels. We also varied the intrinsic value of the broader categorization (high value: whether the snake was venomous; low value: whether it was tropical). We found an interaction between study instruction and intrinsic value: Participants in the low-value condition were better able to induce the level they were instructed to attend to (i.e., genus or broader category) than to induce the level they were not instructed to attend to, whereas participants in the high-value condition, regardless of the level of categorization they were instructed to attend to, were significantly better at learning the broad categorization (for them, whether the snake was venomous) than were participants in the low-value condition. Our results suggest that intrinsically valuable features can disrupt the intentional learning of other, task-relevant information, but enhance the incidental learning of the same information.

How should exemplars be sequenced in inductive learning? Empirical evidence versus learners’ opinions

The sequencing of exemplars during study can have a large effect on category or concept induction. Counter to learners’ intuitions, interleaving exemplars from different categories is often more effective for learning the different underlying categories than is blocking all the exemplars by category (e.g., Kornell & Bjork, 2008). Prior research suggests that blocking and interleaving each support different aspects of induction: Interleaving appears to enhance between-category discrimination, whereas blocking appears to promote the learning of within-category commonalities. In Experiments 1 and 2, participants studied paintings by 12 artists and were asked to induce the different artists’ painting styles. We explored whether hybrid schedules can leverage the benefits of both types of schedules, comparing blocked, interleaved, and 3 hybrid schedules—blocked-to-interleaved, interleaved-to-blocked, and miniblocks. The miniblocks and blocked-to-interleaved schedules were as effective, statistically, but not better than pure interleaving. The blocked schedule led to the worst performance. In Experiments 3 and 4, we explored participants’ a priori beliefs by having them self-schedule hypothetical future category-learning tasks. Although participants demonstrated some metacognitive sophistication with respect to the relative benefits of blocked and interleaved study, pure interleaving was the least popular schedule, despite its being one of the most, effective schedules for learning.

Optimal sequencing during category learning: Testing a dual-learning systems perspective.

Recent studies demonstrate that interleaving the exemplars of different categories, rather than blocking exemplars by category, can enhance inductive learning-the ability to categorize new exemplars-presumably because interleaving affords discriminative contrasts between exemplars from different categories. Consistent with this view, other studies have demonstrated that decreasing between-category similarity and increasing within-category variability can eliminate or even reverse the interleaving benefit. We tested another hypothesis, one based on the dual-learning systems framework-namely, that the optimal schedule for learning categories should depend on an interaction of the cognitive system that mediates learning and the structure of the particular category being learned. Blocking should enhance rule-based category learning, which is mediated by explicit, hypothesis-testing processes, whereas interleaving should enhance information-integration category learning, which is mediated by an implicit, procedural-based learning system. Consistent with this view, we found a crossover interaction between schedule (blocked vs. interleaved) and category structure (rule-based vs. information-integration).