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Flat vs. Expressive Storytelling: Young Children’s Learning and Retention of a Social Robot’s Narrative

Overview of attention for article published in Frontiers in Human Neuroscience, June 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

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5 news outlets
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6 X users

Citations

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79 Dimensions

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215 Mendeley
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Title
Flat vs. Expressive Storytelling: Young Children’s Learning and Retention of a Social Robot’s Narrative
Published in
Frontiers in Human Neuroscience, June 2017
DOI 10.3389/fnhum.2017.00295
Pubmed ID
Authors

Jacqueline M. Kory Westlund, Sooyeon Jeong, Hae W. Park, Samuel Ronfard, Aradhana Adhikari, Paul L. Harris, David DeSteno, Cynthia L. Breazeal

Abstract

Prior research with preschool children has established that dialogic or active book reading is an effective method for expanding young children's vocabulary. In this exploratory study, we asked whether similar benefits are observed when a robot engages in dialogic reading with preschoolers. Given the established effectiveness of active reading, we also asked whether this effectiveness was critically dependent on the expressive characteristics of the robot. For approximately half the children, the robot's active reading was expressive; the robot's voice included a wide range of intonation and emotion (Expressive). For the remaining children, the robot read and conversed with a flat voice, which sounded similar to a classic text-to-speech engine and had little dynamic range (Flat). The robot's movements were kept constant across conditions. We performed a verification study using Amazon Mechanical Turk (AMT) to confirm that the Expressive robot was viewed as significantly more expressive, more emotional, and less passive than the Flat robot. We invited 45 preschoolers with an average age of 5 years who were either English Language Learners (ELL), bilingual, or native English speakers to engage in the reading task with the robot. The robot narrated a story from a picture book, using active reading techniques and including a set of target vocabulary words in the narration. Children were post-tested on the vocabulary words and were also asked to retell the story to a puppet. A subset of 34 children performed a second story retelling 4-6 weeks later. Children reported liking and learning from the robot a similar amount in the Expressive and Flat conditions. However, as compared to children in the Flat condition, children in the Expressive condition were more concentrated and engaged as indexed by their facial expressions; they emulated the robot's story more in their story retells; and they told longer stories during their delayed retelling. Furthermore, children who responded to the robot's active reading questions were more likely to correctly identify the target vocabulary words in the Expressive condition than in the Flat condition. Taken together, these results suggest that children may benefit more from the expressive robot than from the flat robot.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 215 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 215 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 37 17%
Student > Ph. D. Student 36 17%
Student > Bachelor 25 12%
Researcher 17 8%
Lecturer 13 6%
Other 23 11%
Unknown 64 30%
Readers by discipline Count As %
Psychology 29 13%
Computer Science 28 13%
Social Sciences 21 10%
Linguistics 12 6%
Nursing and Health Professions 12 6%
Other 45 21%
Unknown 68 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 39. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 July 2023.
All research outputs
#976,630
of 24,099,692 outputs
Outputs from Frontiers in Human Neuroscience
#449
of 7,418 outputs
Outputs of similar age
#20,735
of 320,955 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#19
of 178 outputs
Altmetric has tracked 24,099,692 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.8. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,955 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 178 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.