Lucy C. Erickson

Who Is Good at This Game? Linking an Activity to a Social Category Undermines Children’s Achievement

Children’s achievement-related theories have a profound impact on their academic success. Children who adopt entity theories believe that their ability to perform a task is dictated by the amount of natural talent they possess for that task—a belief that has well-documented adverse consequences for their achievement (e.g., lowered persistence, impaired performance). It is thus important to understand what leads children to adopt entity theories. In the experiments reported here, we hypothesized that the mere act of linking success at an unfamiliar, challenging activity to a social group gives rise to entity beliefs that are so powerful as to interfere with children’s ability to perform the activity. Two experiments showed that, as predicted, the performance of 4- to 7-year-olds (N = 192) was impaired by exposure to information that associated success in the task at hand with membership in a certain social group (e.g., “boys are good at this game”), regardless of whether the children themselves belonged to that group.

Beyond Word Segmentation: A Two- Process Account of Statistical Learning

The term statistical learning was originally used to describe sensitivity to conditional relations between syllables in the context of word segmentation. Subsequent research has demonstrated that infants are sensitive to many other kinds of statistical information. The range of statistical learning phenomena presents a challenge to prior theories and models, which have primarily focused on a single aspect of learning. From our perspective, sensitivity to conditional information yields discrete representations (such as words). Integration across these representations yields sensitivity to distributional information. To achieve sensitivity to both kinds of statistical information, we propose a framework that combines processes that extract units from the input with processes that compare across these extracted items. We review the literature on statistical learning to show how these processes map onto prior research, and we discuss how the interaction between these processes gives rise to more complex patterns of learning than either process achieves in isolation.

Discovering Words in Fluent Speech: The Contribution of Two Kinds of Statistical Information

To efficiently segment fluent speech, infants must discover the predominant phonological form of words in the native language. In English, for example, content words typically begin with a stressed syllable. To discover this regularity, infants need to identify a set of words. We propose that statistical learning plays two roles in this process. First, it provides a cue that allows infants to segment words from fluent speech, even without language-specific phonological knowledge. Second, once infants have identified a set of lexical forms, they can learn from the distribution of acoustic features across those word forms. The current experiments demonstrate both processes are available to 5-month-old infants. This demonstration of sensitivity to statistical structure in speech, weighted more heavily than phonological cues to segmentation at an early age, is consistent with theoretical accounts that claim statistical learning plays a role in helping infants to adapt to the structure of their native language from very early in life.

Statistical learning and the critical period: how a continuous learning mechanism can give rise to discontinuous learning.

Infants and children are generally more successful than adults in learning novel languages, a phenomenon referred to as a critical or sensitive period for language acquisition. One explanation for this critical period is the idea that children have access to a set of language learning processes or mechanisms unavailable to adults. From this perspective, developmental change is explained in terms of a discontinuity of learning processes. We suggest that this is not the only possible explanation for developmental change in language learning outcomes. Instead, we propose that the mechanisms underlying language acquisition (in particular, we highlight statistical learning) are largely continuous across the lifespan. From this perspective, developmental change is explained in terms of experience, differences in the input with age, and maturational changes in the cognitive architecture supporting learning, even while the learning process itself operates continuously across developmental time. WIREs Cogn Sci 2016, 7:276-288. doi: 10.1002/wcs.1394 For further resources related to this article, please visit the WIREs website.

Endogenously and exogenously driven selective sustained attention: Contributions to learning in kindergarten children.

Selective sustained attention is vital for higher order cognition. Although endogenous and exogenous factors influence selective sustained attention, assessment of the degree to which these factors influence performance and learning is often challenging. We report findings from the Track-It task, a paradigm that aims to assess the contribution of endogenous and exogenous factors to selective sustained attention within the same task. Behavioral accuracy and eye-tracking data on the Track-It task were correlated with performance on an explicit learning task. Behavioral accuracy and fixations to distractors during the Track-It task did not predict learning when exogenous factors supported selective sustained attention. In contrast, when endogenous factors supported selective sustained attention, fixations to distractors were negatively correlated with learning. Similarly, when endogenous factors supported selective sustained attention, higher behavioral accuracy was correlated with greater learning. These findings suggest that endogenously and exogenously driven selective sustained attention, as measured through different conditions of the Track-It task, may support different kinds of learning.