Exploring Different Types of Feedback in Preschooler and Robot Interaction

Haas, Mirjam de; Baxter, Peta; Jong, Chiara de; Krahmer, Emiel; Vogt, Paul

doi:10.1145/3029798.3038433

Cited by 13 publications

(11 citation statements)

References 4 publications

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“…When responsiveness was kept constant, the mode of controlling a robot neither influenced engagement [35] nor enjoyment [140]. While qualitative findings indicate that role was associated with engagement [28,98,111], quantitative findings were inconsistent [36,96,104]. Embodiment increased observed engagement [61,89] unless the interaction was more taskoriented [70,138].…”

Section: Experiential Statesmentioning

confidence: 95%

Child–Robot Relationship Formation: A Narrative Review of Empirical Research

Straten

Peter

Kühne

2019

Int J of Soc Robotics

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This narrative review aimed to elucidate which robot-related characteristics predict relationship formation between typically-developing children and social robots in terms of closeness and trust. Moreover, we wanted to know to what extent relationship formation can be explained by children's experiential and cognitive states during interaction with a robot. We reviewed 86 journal articles and conference proceedings published between 2000 and 2017. In terms of predictors, robots' responsiveness and role, as well as strategic and emotional interaction between robot and child, increased closeness between the child and the robot. Findings about whether robot features predict children's trust in robots were inconsistent. In terms of children's experiential and cognitive states during interaction with a robot, robot characteristics and interaction styles were associated with two experiential states: engagement and enjoyment/liking. The literature hardly addressed the impact of experiential and cognitive states on closeness and trust. Comparisons of children's interactions with robots, adults, and objects showed that robots are perceived as neither animate nor inanimate, and that they are entities with whom children will likely form social relationships. Younger children experienced more enjoyment, were less sensitive to a robot's interaction style, and were more prone to anthropomorphic tendencies and effects than older children. Tailoring a robot's sex to that of a child mainly appealed to boys.

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Section: Experiential Statesmentioning

confidence: 95%

Child–Robot Relationship Formation: A Narrative Review of Empirical Research

Straten

Peter

Kühne

2019

Int J of Soc Robotics

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“…To investigate how children experience feedback from a peer robot, we carried out an experiment among 85 3-year-old Dutch-speaking children at preschools in Netherlands (de Haas et al, 2016 , 2017 ). In this experiment, the children interacted with a NAO robot during which they received a short lesson on how to count from 1 to 4 in English.…”

Section: Designing Child-robot Interactionsmentioning

confidence: 99%

Child-Robot Interactions for Second Language Tutoring to Preschool Children

Vogt

Haas

Jong

et al. 2017

Front. Hum. Neurosci.

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In this digital age social robots will increasingly be used for educational purposes, such as second language tutoring. In this perspective article, we propose a number of design features to develop a child-friendly social robot that can effectively support children in second language learning, and we discuss some technical challenges for developing these. The features we propose include choices to develop the robot such that it can act as a peer to motivate the child during second language learning and build trust at the same time, while still being more knowledgeable than the child and scaffolding that knowledge in adult-like manner. We also believe that the first impressions children have about robots are crucial for them to build trust and common ground, which would support child-robot interactions in the long term. We therefore propose a strategy to introduce the robot in a safe way to toddlers. Other features relate to the ability to adapt to individual children’s language proficiency, respond contingently, both temporally and semantically, establish joint attention, use meaningful gestures, provide effective feedback and monitor children’s learning progress. Technical challenges we observe include automatic speech recognition (ASR) for children, reliable object recognition to facilitate semantic contingency and establishing joint attention, and developing human-like gestures with a robot that does not have the same morphology humans have. We briefly discuss an experiment in which we investigate how children respond to different forms of feedback the robot can give.

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“…While there have been many studies about robots for educating children, only few of these have investigated the effects that different types of feedback can have on children's engagement and learning performance (Gordon et al, 2016 ; De Haas et al, 2017 ; Ahmad et al, 2019 ). Usually, studies design feedback strategies for robot tutors based on results from educational studies involving only humans without investigating the effect that these strategies have on children's engagement and/or performance (e.g., Mazzoni and Benvenuti, 2015 ; Westlund and Breazeal, 2015 ; Gordon et al, 2016 ; Kennedy et al, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

“…Three studies that specifically investigated the effect that feedback has on learning and/or engagement are those by De Haas et al ( 2017 ), Resing et al ( 2019 ), and Ahmad et al ( 2019 ). De Haas et al ( 2017 ) conducted a between-subject study with 4-year-old pre-school children that compared the effect that three different feedback strategies (peer-like, adult-like, and no feedback) had on learning gain and engagement.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Feedback on Children's Engagement and Learning Outcomes in Robot-Assisted Second Language Learning

2020

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To investigate how a robot's use of feedback can influence children's engagement and support second language learning, we conducted an experiment in which 72 children of 5 years old learned 18 English animal names from a humanoid robot tutor in three different sessions. During each session, children played 24 rounds in an "I spy with my little eye" game with the robot, and in each session the robot provided them with a different type of feedback. These feedback types were based on a questionnaire study that we conducted with student teachers and the outcome of this questionnaire was translated to three within-design conditions: (teacher) preferred feedback, (teacher) dispreferred feedback and no feedback. During the preferred feedback session, among others, the robot varied his feedback and gave children the opportunity to try again (e.g., "Well done! You clicked on the horse.", "Too bad, you pressed the bird. Try again. Please click on the horse."); during the dispreferred feedback the robot did not vary the feedback ("Well done!", "Too bad.") and children did not receive an extra attempt to try again; and during no feedback the robot did not comment on the children's performances at all. We measured the children's engagement with the task and with the robot as well as their learning gain, as a function of condition. Results show that children tended to be more engaged with the robot and task when the robot used preferred feedback than in the two other conditions. However, preferred or dispreferred feedback did not have an influence on learning gain. Children learned on average the same number of words in all conditions. These findings are especially interesting for long-term interactions where engagement of children often drops. Moreover, feedback can become more important for learning when children need to rely more on feedback, for example, when words or language constructions are more complex than in our experiment. The experiment's method, measurements and main hypotheses were preregistered.

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Exploring Different Types of Feedback in Preschooler and Robot Interaction

Cited by 13 publications

References 4 publications

Child–Robot Relationship Formation: A Narrative Review of Empirical Research

Child–Robot Relationship Formation: A Narrative Review of Empirical Research

Child-Robot Interactions for Second Language Tutoring to Preschool Children

The Effects of Feedback on Children's Engagement and Learning Outcomes in Robot-Assisted Second Language Learning

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