Most research in statistical learning (SL) has focused on the mean success rates of participants ... more Most research in statistical learning (SL) has focused on the mean success rates of participants in detecting statistical contingencies at a group level. In recent years, however, researchers have shown increased interest in individual abilities in SL, either to predict other cognitive capacities or as a tool for understanding the mechanism underlying SL. Most if not all of this research enterprise has employed SL tasks that were originally designed for group-level studies. We argue that from an individual difference perspective, such tasks are psychometrically weak, and sometimes even flawed. In particular, the existing SL tasks have three major shortcomings: (1) the number of trials in the test phase is often too small (or, there is extensive repetition of the same targets throughout the test); (2) a large proportion of the sample performs at chance level, so that most of the data points reflect noise; and (3) the test items following familiarization are all of the same type and an identical level of difficulty. These factors lead to high measurement error, inevitably resulting in low reliability, and thereby doubtful validity. Here we present a novel method specifically designed for the measurement of individual differences in visual SL. The novel task we offer displays substantially superior psychometric properties. We report data regarding the reliability of the task and discuss the importance of the implementation of such tasks in future research.
What determines individuals’ efficacy in detecting regularities in visual statistical learning? O... more What determines individuals’ efficacy in detecting regularities in visual statistical learning? Our theoretical starting point assumes that the variance in performance of statistical learning (SL) can be split into the variance related to efficiency in encoding representations within a modality and the variance related to the relative computational efficiency of detecting the distributional properties of the encoded representations. Using a novel methodology, we dissociated encoding from higher-order learning factors, by independently manipulating exposure duration and transitional probabilities in a stream of visual shapes. Our results show that the encoding of shapes and the retrieving of their transitional probabilities are not independent and additive processes, but interact to jointly determine SL performance. The theoretical implications of these findings for a mechanistic explanation of SL are discussed.
Although the power of statistical learning (SL) in explaining a wide range of linguistic function... more Although the power of statistical learning (SL) in explaining a wide range of linguistic functions is gaining increasing support, relatively little research has focused on this theoretical construct from the perspective of individual differences. However, to be able to reliably link individual differences in a given ability such as language learning to individual differences in SL, three critical theoretical questions should be posed: Is SL a componential or unified ability? Is it nested within other general cognitive abilities? Is it a stable capacity of an individual? Following an initial mapping sentence outlining the possible dimensions of SL, we employed a battery of SL tasks in the visual and auditory modalities, using verbal and non-verbal stimuli, with adjacent and non-adjacent contingencies. SL tasks were administered along with general cognitive tasks in a within-subject design at two time points to explore our theoretical questions. We found that SL, as measured by some t...
Why is it difficult to learn a second language as an adult? We focus on the way adults’ existing ... more Why is it difficult to learn a second language as an adult? We focus on the way adults’ existing knowledge of words impacts L2 learning. We suggest adults’ prior knowledge leads them to rely less on multiword units, and that this hinders learning certain grammatical relations between words. We test this prediction in two artificial language learning studies of grammatical gender with adult learners. In the first study, we manipulate whether the artificial language is segmented during initial learning and show that learning from unsegmented input leads to more article–noun units, and to better learning. Individually, learners who were more likely to treat the article and noun as one unit
showed better learning on an off-line measure, confirming the link between unit-size and learning outcomes. In the second study, we show this pattern does not hold when
the article conveys semantic information (animate vs. inanimate), illustrating the way unit size interacts with informativity during learning. The findings provide novel evidence for the advantage of learning grammar from multiword units, highlight the benefit of learning
segmentation and structure simultaneously, and offer an experience-based explanation for L1–L2 differences that relates building blocks to learning outcomes.
Most research in statistical learning (SL) has focused on the mean success rates of participants ... more Most research in statistical learning (SL) has focused on the mean success rates of participants in detecting statistical contingencies at a group level. In recent years, however, researchers have shown increased interest in individual abilities in SL, either to predict other cognitive capacities or as a tool for understanding the mechanism underlying SL. Most if not all of this research enterprise has employed SL tasks that were originally designed for group-level studies. We argue that from an individual difference perspective, such tasks are psychometrically weak, and sometimes even flawed. In particular, the existing SL tasks have three major shortcomings: (1) the number of trials in the test phase is often too small (or, there is extensive repetition of the same targets throughout the test); (2) a large proportion of the sample performs at chance level, so that most of the data points reflect noise; and (3) the test items following familiarization are all of the same type and an identical level of difficulty. These factors lead to high measurement error, inevitably resulting in low reliability, and thereby doubtful validity. Here we present a novel method specifically designed for the measurement of individual differences in visual SL. The novel task we offer displays substantially superior psychometric properties. We report data regarding the reliability of the task and discuss the importance of the implementation of such tasks in future research.
What determines individuals’ efficacy in detecting regularities in visual statistical learning? O... more What determines individuals’ efficacy in detecting regularities in visual statistical learning? Our theoretical starting point assumes that the variance in performance of statistical learning (SL) can be split into the variance related to efficiency in encoding representations within a modality and the variance related to the relative computational efficiency of detecting the distributional properties of the encoded representations. Using a novel methodology, we dissociated encoding from higher-order learning factors, by independently manipulating exposure duration and transitional probabilities in a stream of visual shapes. Our results show that the encoding of shapes and the retrieving of their transitional probabilities are not independent and additive processes, but interact to jointly determine SL performance. The theoretical implications of these findings for a mechanistic explanation of SL are discussed.
Although the power of statistical learning (SL) in explaining a wide range of linguistic function... more Although the power of statistical learning (SL) in explaining a wide range of linguistic functions is gaining increasing support, relatively little research has focused on this theoretical construct from the perspective of individual differences. However, to be able to reliably link individual differences in a given ability such as language learning to individual differences in SL, three critical theoretical questions should be posed: Is SL a componential or unified ability? Is it nested within other general cognitive abilities? Is it a stable capacity of an individual? Following an initial mapping sentence outlining the possible dimensions of SL, we employed a battery of SL tasks in the visual and auditory modalities, using verbal and non-verbal stimuli, with adjacent and non-adjacent contingencies. SL tasks were administered along with general cognitive tasks in a within-subject design at two time points to explore our theoretical questions. We found that SL, as measured by some t...
Why is it difficult to learn a second language as an adult? We focus on the way adults’ existing ... more Why is it difficult to learn a second language as an adult? We focus on the way adults’ existing knowledge of words impacts L2 learning. We suggest adults’ prior knowledge leads them to rely less on multiword units, and that this hinders learning certain grammatical relations between words. We test this prediction in two artificial language learning studies of grammatical gender with adult learners. In the first study, we manipulate whether the artificial language is segmented during initial learning and show that learning from unsegmented input leads to more article–noun units, and to better learning. Individually, learners who were more likely to treat the article and noun as one unit
showed better learning on an off-line measure, confirming the link between unit-size and learning outcomes. In the second study, we show this pattern does not hold when
the article conveys semantic information (animate vs. inanimate), illustrating the way unit size interacts with informativity during learning. The findings provide novel evidence for the advantage of learning grammar from multiword units, highlight the benefit of learning
segmentation and structure simultaneously, and offer an experience-based explanation for L1–L2 differences that relates building blocks to learning outcomes.
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Papers by Noam Siegelman
showed better learning on an off-line measure, confirming the link between unit-size and learning outcomes. In the second study, we show this pattern does not hold when
the article conveys semantic information (animate vs. inanimate), illustrating the way unit size interacts with informativity during learning. The findings provide novel evidence for the advantage of learning grammar from multiword units, highlight the benefit of learning
segmentation and structure simultaneously, and offer an experience-based explanation for L1–L2 differences that relates building blocks to learning outcomes.
showed better learning on an off-line measure, confirming the link between unit-size and learning outcomes. In the second study, we show this pattern does not hold when
the article conveys semantic information (animate vs. inanimate), illustrating the way unit size interacts with informativity during learning. The findings provide novel evidence for the advantage of learning grammar from multiword units, highlight the benefit of learning
segmentation and structure simultaneously, and offer an experience-based explanation for L1–L2 differences that relates building blocks to learning outcomes.