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Abstract Teaching a new concept through gestures—hand movements that accompany speech—facilitates learning above‐and‐beyond instruction through speech alone (e.g., Singer & Goldin‐Meadow,). However, the mechanisms underlying this phenomenon are still under investigation. Here, we use eye tracking to explore one often proposed mechanism—gesture's ability to direct visual attention. Behaviorally, we replicate previous findings: Children perform significantly better on a posttest after learning through Speech+Gesture instruction than through Speech Alone instruction. Using eye tracking measures, we show that children who watch a math lesson with gesturedoallocate their visual attention differently from children who watch a math lesson without gesture—they look more to the problem being explained, less to the instructor, and are more likely to synchronize their visual attention with information presented in the instructor's speech (i.e.,follow along with speech) than children who watch the no‐gesture lesson. The striking finding is that, even though these looking patterns positively predict learning outcomes, the patterns do notmediatethe effects of training condition (Speech Alone vs. Speech+Gesture) on posttest success. We find instead a complex relation between gesture and visual attention in which gesturemoderatesthe impact of visual looking patterns on learning—following along with speechpredicts learning for children in the Speech+Gesture condition, but not for children in the Speech Alone condition. Gesture's beneficial effects on learning thus come not merely from its ability to guide visual attention, but also from its ability to synchronize with speech and affect what learners glean from that speech.
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Language systematizes attention: How relational language enhances relational representation by guiding attention
Language can affect cognition, but through what mechanism? Substantial past research has focused on how labeling can elicit categorical representation during online processing. We focus here on a particularly powerful type of language—relational language—and show that relational language can enhance relational representation in children through an embodied attention mechanism. Four-year-old children were given a color-location conjunction task, in which they were asked to encode a two-color square, split either vertically or horizontally (e.g., red on the left, blue on the right), and later recall the same configuration from its mirror reflection. During the encoding phase, children in the experimental condition heard relational language (e.g., “Red is on the left of blue”), while those in the control condition heard generic non-relational language (e.g., “Look at this one, look at it closely”). At recall, children in the experimental condition were more successful at choosing the correct relational representation between the two colors compared to the control group. Moreover, they exhibited different attention patterns as predicted by the attention shift account of relational representation (Franconeri et al., 2012). To test the sustained effect of language and the role of attention, during the second half of the study, the experimental condition was given generic non-relational language. There was a sustained advantage in the experimental condition for both behavioral accuracies and signature attention patterns. Overall, our findings suggest that relational language enhances relational representation by guiding learners’ attention, and this facilitative effect persists over time even in the absence of language. Implications for the mechanism of how relational language can enhance the learning of relational systems (e.g., mathematics, spatial cognition) by guiding attention will be discussed.
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- Award ID(s):
- 2200781
- PAR ID:
- 10498216
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Cognition
- Volume:
- 243
- Issue:
- C
- ISSN:
- 0010-0277
- Page Range / eLocation ID:
- 105671
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.cognition.2023.105671
