Children use non-verbal cues to learn new words from robots as well as people

Westlund, Jacqueline M. Kory; Dickens, Leah; Jeong, Sooyeon; Harris, Paul L.; DeSteno, David; Breazeal, Cynthia

doi:10.1016/j.ijcci.2017.04.001

Cited by 74 publications

(61 citation statements)

References 26 publications

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“…This approach has been taken several times (e.g., References [13,50,61]). Although not common, this output may be processed after recording, for example by pitch shifting an adult voice to make it sound child-like [111,112].…”

Section: Voicementioning

confidence: 99%

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A Survey of Robot-Assisted Language Learning (RALL)

Randall

2019

J. Hum.-Robot Interact.

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Robot-assisted language learning (RALL) is becoming a more commonly studied area of human-robot interaction (HRI). This research draws on theories and methods from many different fields, with researchers utilizing different instructional methods, robots, and populations to evaluate the effectiveness of RALL. This survey details the characteristics of robots used-form, voice, immediacy, non-verbal cues, and personalizationalong with study implementations, discussing research findings. It also analyzes robot effectiveness. While research clearly shows that robots can support native and foreign language acquisition, it has been unclear what benefits robots provide over computer-assisted language learning. This survey examines the results of relevant studies from 2004 (RALL's inception) to 2017. Results suggest that robots may be uniquely suited to aid in language production, with apparent benefits in comparison to other technology. As well, research consistently indicates that robots provide unique advantages in increasing learning motivation and in-task engagement, and decreasing anxiety, though long-term benefits are uncertain. Throughout this survey, future areas of exploration are suggested, with the hope that answers to these questions will allow for more robust design and implementation guidelines in RALL.

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Section: Voicementioning

confidence: 99%

“…A more interesting question is: How do robots compare with other technologies in their ability to do so? Studies suggest that, at least for simple vocabulary teaching, robots perform on par with iPads [110], and for that matter, human teachers [110,112]. All three served equally well for transferring knowledge of rudimentary vocabulary.…”

Section: Vocabularymentioning

confidence: 99%

A Survey of Robot-Assisted Language Learning (RALL)

Randall

2019

J. Hum.-Robot Interact.

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“…Prior work has found evidence that children readily treat robots as social agents [6,16,18,23,24,36]. When children are given time to develop relationships with social agents, such as in long-term human-robot interaction studies, children display social behaviors such as sharing gaze, mirroring emotions, affection, helping behaviors, turn-taking, and disclosing information [11,22,26,29,41,42].…”

Section: Background Relationship Behaviorsmentioning

confidence: 99%

Measuring young children's long-term relationships with social robots

Westlund

Park

Williams

et al. 2018

Proceedings of the 17th ACM Conference on Interaction Design and Children

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Social robots are increasingly being developed for long-term interactions with children in domains such as healthcare, education, therapy, and entertainment. As such, we need to deeply understand how children's relationships with robots develop through time. However, there are few validated assessments for measuring young children's long-term relationships. In this paper, we present a pilot test of four assessments that we have adapted or created for use in this context with children aged 5-6: the Inclusion of Other in Self task, the Social-Relational Interview, the Narrative Description, and the Self-disclosure Task. We show that children can appropriately respond to these assessments with reasonably high internal reliability, and that the proposed assessments are able to capture child-robot relationship adjustments over a long-term interaction. Furthermore, we discuss gender and population differences in children's responses.

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“…The presence of the robot allowed for numerous opportunities for language and communication. Westlund () and Mazzoni and Benvenuti () both reported that the use of non‐humanoid robots was effective in helping students learn vocabulary in a natural and authentic manner. In the current study, the researchers observed additional opportunities for language and communication development using a humanoid robot.…”

Section: Discussionmentioning

confidence: 99%

“…Early findings show that the use of these robotic toys can be used as a catalyst for mathematical problem‐solving (Highfield, ). Using DragonBots, a fluffy, squash and stretch robot, children were able to acquire new vocabulary in a spontaneous and natural fashion (Westlund et al, ). Findings from the use of Roball, a robot encapsulated in a sphere, show that self‐propelled robots possess the potential to bring new and interesting research opportunities regarding the use of the robot in areas of language, motor, social and intellectual skills (Michaud, et al, ).…”

Section: Literature Reviewmentioning

confidence: 99%

Humanoid robots supporting children’s learning in an early childhood setting

Crompton¹,

Gregory²,

Burke³

2018

Brit J Educational Tech

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This qualitative study explored the affordances provided by the integration of the NAO humanoid robot in three preschool classrooms. Using the Head Start Early Learning Outcomes Framework as a lens, the researchers qualitatively analyzed data from focus groups, observations, field notes and student artifacts, using grounded coding to uncover language and communication, physical, cognitive and social–emotional learning experiences for children. The researchers also examined interactions between the robot, children and teachers to identify successes and challenges experienced during the integration. Findings indicate the robot provided opportunities for student development in all learning domains. Students were intellectually curious about the robot; data showed their eagerness to “talk with,” generate questions about, make eye contact with and learn more about the robot. Students viewed these interactions as two‐way. The presence of the robot created much enthusiasm and excitement, resulting in the opportunity for students to practice waiting their turn and cooperation. Challenges uncovered show that teachers lacked experience and knowledge in the integration and operation of the robot. Despite these challenges, findings show that teachers welcomed the robot as a tool in the classroom to align with curriculum requirements and meet the developmental needs of children.

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Children use non-verbal cues to learn new words from robots as well as people

Cited by 74 publications

References 26 publications

A Survey of Robot-Assisted Language Learning (RALL)

A Survey of Robot-Assisted Language Learning (RALL)

Measuring young children's long-term relationships with social robots

Humanoid robots supporting children’s learning in an early childhood setting

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