首页> 美国卫生研究院文献>Frontiers in Human Neuroscience >Flat vs. Expressive Storytelling: Young Children’s Learning and Retention of a Social Robot’s Narrative
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Flat vs. Expressive Storytelling: Young Children’s Learning and Retention of a Social Robot’s Narrative

机译:扁平故事与富有表现力的故事讲述:幼儿对社交机器人叙事的学习和保留

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摘要

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.
机译:先前对学龄前儿童的研究已经确定,对话式或活动式阅读是扩大幼儿词汇量的有效方法。在这项探索性研究中,我们询问当机器人与学龄前儿童进行对话式阅读时,是否观察到类似的好处。考虑到主动阅读已确立的有效性,我们还询问这种有效性是否严格取决于机器人的表达特性。对于大约一半的孩子来说,机器人的主动阅读很有表现力。机器人的声音包括各种语调和情感(富有表现力)。对于其余的孩子,机器人以平直的声音阅读和交谈,听起来像经典的文本语音转换引擎,并且动态范围很小(Flat)。机器人的运动在各种情况下保持恒定。我们使用Amazon Mechanical Turk(AMT)进行了一项验证研究,以确认与Flat机器人相比,Expressive机器人被认为具有更高的表现力,更多的情感和更少的被动感。我们邀请了45名平均年龄为5岁的学龄前儿童,他们既是英语学习者(ELL),双语者,还是以英语为母语的人来参与机器人的阅读任务。机器人使用主动阅读技术,从图画书中讲述了一个故事,并在叙述中包含了一组目标词汇。对孩子的词汇进行了后测,还要求他们将故事讲给一个木偶。 34个孩子中有一个子集在4-6周后重演了第二个故事。孩子们表示,在表现力和平缓条件下,他们对机器人的喜好和学习程度相似。但是,与处于扁平状态的儿童相比,处于表情状态的儿童更加集中,并通过面部表情进行索引。他们在故事复述中更多地模仿了机器人的故事;在延迟重播期间,他们讲了更长的故事。此外,与“平直”条件相比,在“表现力”条件下回答机器人主动阅读问题的孩子更有可能正确识别目标词汇。综上所述,这些结果表明,与平板机器人相比,儿童可能从表现型机器人中受益更多。

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