Individual Differences in Structure Building: Impacts on Comprehension and Learning, Theoretical Underpinnings, and Support for Less Able Structure Builders.

In this article, we highlight an underappreciated individual difference: structure building. Structure building is integral to many everyday activities and involves creating coherent mental representations of conversations, texts, pictorial stories, and other events. People vary in this ability in a way not generally captured by other better known concepts and individual difference measures. Individuals with lower structure-building ability consistently perform worse on a range of comprehension and learning measures than do individuals with higher structure-building ability, both in the laboratory and in the classroom. Problems include a range of comprehension processes, including encoding factual content, inhibiting irrelevant information, and constructing a cohesive situation model of a text or conversation. Despite these problems, recent research is encouraging in that techniques to improve the learning outcomes for low-ability structure builders have been identified. We argue that the accumulated research warrants the recognition of structure building as an important individual difference in cognitive functioning and that additional theoretical work is needed to understand the underpinnings of structure-building deficits.

Individual and age differences in block-by-block dynamics of category learning strategies.

The present experiment examined individual and age differences in the dynamics of category learning strategies. Participants learned categories determined by a disjunctive rule with relational features through a feedback training procedure. During training, participants responded to strategy probes following each block to provide online assessment of the extent to which rule- and exemplar-based strategies were used throughout the training period. We introduced this measure as an alternative to model-based approaches to assessing individual differences in strategy use during training. Following training, participants classified ambiguous transfer objects that were assumed to distinguish between earlier use of rule- and exemplar-based learning strategies. We included this measure to obtain a relatively objective index of strategy use during training. Next, participants provided global ratings of their use of rule- and exemplar-based strategies during training. Results showed that strategy preferences expressed on the final training block predicted categorisation of ambiguous transfer objects better than global strategy reports. In addition, we utilised the block-by-block strategy reports to investigate the dynamics of learners' strategy preferences over the course of training. The findings revealed greater fluidity in strategy preferences for both younger and older adults than has been previously documented in the category learning literature. The novel block-by-block strategy reports in conjunction with the transfer-based approach allowed for a more nuanced examination of individual and age differences in strategy use and categorisation performance.

Feature highlighting enhances learning of a complex natural-science category.

Learning naturalistic categories, which tend to have fuzzy boundaries and vary on many dimensions, can often be harder than learning well defined categories. One method for facilitating the category learning of naturalistic stimuli may be to provide explicit feature descriptions that highlight the characteristic features of each category. Although this method is commonly used in textbooks and classrooms, theoretically it remains uncertain whether feature descriptions should advantage learning complex natural-science categories. In three experiments, participants were trained on 12 categories of rocks, either without or with a brief description highlighting key features of each category. After training, they were tested on their ability to categorize both old and new rocks from each of the categories. Providing feature descriptions as a caption under a rock image failed to improve category learning relative to providing only the rock image with its category label (Experiment 1). However, when these same feature descriptions were presented such that they were explicitly linked to the relevant parts of the rock image (feature highlighting), participants showed significantly higher performance on both immediate generalization to new rocks (Experiment 2) and generalization after a 2-day delay (Experiment 3). Theoretical and practical implications are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).