Intricacies of Child–Robot Interaction

A special issue of Multimodal Technologies and Interaction (ISSN 2414-4088).

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 23336

Special Issue Editors


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Guest Editor
Division of Learning, Communication and IT, Department of Applied IT, University of Gothenburg, Gothenburg, Sweden
Interests: child–robot interaction; social robots; educational robots

E-Mail Website
Guest Editor
Social and Intelligent Robotics Research laboratory, University of Waterloo, Waterloo, ON, Canada
Interests: social robots; assistive robotics; educational robotics; long-term human-robot interaction; autonomous robots; interaction design; artificial Intelligence; machine learning
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Special Issue Information

Dear Colleagues,

In recent decades, there has been an upsurge in interest around child–robot interaction (CRI). The possibilities of using social robots for educational or therapeutic purposes in schools, hospitals, and domestic settings have captured the attention of researchers, institutions, and stakeholders alike. Much of the existing research seems to confirm the positive potential of using social robots: for example, robots as tutors or learning companions are seen as engaging devices to foster learning, able to alleviate some of the teacher’s workload; neurodiverse children are thought to benefit from social training with robots; children in need of remote education can benefit from utilizing telepresence robots for interacting with their peers in classrooms.

In recent years, however, voices have been raised that emphasize the need for critical and ethical perspectives on the study and use of social robots for children. The trajectory of technological change is never straightforward. While the potentials for CRI are high, so are the stakes. Like many other technologies targeting children, we are still unsure about the long-term effects of CRI on children’s mental, physical, and emotional wellbeing and development. Through our years of experience in this field, we know that researchers indeed confront several difficulties, challenges, and dilemmas in trying to make the interaction between children and robots work successfully. With this Special Issue, we aim to focus on the challenges of CRI that are widely known—but seldom reported—within the research field. These obstacles belong to a wide range of topics including technical, social, behavioral, user perceptions and expectations, evaluation, qualitative/quantitative data, and ethical issues, among others. 

We are pleased to invite you to contribute to this Special Issue on “Intricacies in Child–Robot Interaction”, which is a response to what we perceive as a lack of studies in CRI that specifically focus on the challenges and intricacies. Authors are encouraged to submit original research articles, case studies, reviews, position papers, and theoretical papers within the following topics of interest:

  • Challenges in CRI, including, e.g., design challenges, conducting long-term studies, or designing playful scenarios
  • Critical examinations of children’s or relevant stakeholders’ perceptions and expectations of robots
  • Breakdowns, errors, and/or deficits in CRI, both technical and social, intended and unintended
  • Qualitative studies of cases/children in previously published CRI experiments, excluded from analysis due to robot malfunction or interaction breakdowns
  • Ethics in CRI
  • Studies of CRI that are never published due to “insignificant or negative results”
  • Critical examinations of dominating methods or theories in CRI, and/or proposed methods or theories
  • Robot designs or applications that were for some reason abandoned as feasible options for CRI
  • Negative and/or undesirable effects of robots for children
  • Social and practical challenges of implementing robots in child-focused settings (e.g., classrooms, hospitals, or the home)
  • Cultural challenges in CRI
  • Critical perspectives on social robots in relation to neurodiverse children, e.g., therapeutic applications for children on the autism spectrum
  • Researcher responsibility in CRI

Dr. Sofia Serholt
Dr. Shruti Chandra
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Multimodal Technologies and Interaction is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • child–robot Interaction
  • challenges
  • ethics
  • intricacies

Published Papers (8 papers)

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Research

23 pages, 2500 KiB  
Article
Cognitive Learning and Robotics: Innovative Teaching for Inclusivity
by Nurziya Oralbayeva, Aida Amirova, Anna CohenMiller and Anara Sandygulova
Multimodal Technol. Interact. 2022, 6(8), 65; https://0-doi-org.brum.beds.ac.uk/10.3390/mti6080065 - 03 Aug 2022
Viewed by 2059
Abstract
We present the interdisciplinary CoWriting Kazakh project in which a social robot acts as a peer in learning the new Kazakh Latin alphabet, to which Kazakhstan is going to shift from the current Kazakh Cyrillic by 2030. We discuss the past literature on [...] Read more.
We present the interdisciplinary CoWriting Kazakh project in which a social robot acts as a peer in learning the new Kazakh Latin alphabet, to which Kazakhstan is going to shift from the current Kazakh Cyrillic by 2030. We discuss the past literature on cognitive learning and script acquisition in-depth and present a theoretical framing for this study. The results of word and letter analyses from two user studies conducted between 2019 and 2020 are presented. Learning the new alphabet through Kazakh words with two or more syllables and special native letters resulted in significant learning gains. These results suggest that reciprocal Cyrillic-to-Latin script learning results in considerable cognitive benefits due to mental conversion, word choice, and handwriting practices. Overall, this system enables school-age children to practice the new Kazakh Latin script in an engaging learning scenario. The proposed theoretical framework illuminates the understanding of teaching and learning within the multimodal robot-assisted script learning scenario and beyond its scope. Full article
(This article belongs to the Special Issue Intricacies of Child–Robot Interaction)
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17 pages, 1715 KiB  
Article
The Quantitative Case-by-Case Analyses of the Socio-Emotional Outcomes of Children with ASD in Robot-Assisted Autism Therapy
by Zhansaule Telisheva, Aida Amirova, Nazerke Rakhymbayeva, Aida Zhanatkyzy and Anara Sandygulova
Multimodal Technol. Interact. 2022, 6(6), 46; https://0-doi-org.brum.beds.ac.uk/10.3390/mti6060046 - 15 Jun 2022
Cited by 8 | Viewed by 2092
Abstract
With its focus on robot-assisted autism therapy, this paper presents case-by-case analyses of socio-emotional outcomes of 34 children aged 3–12 years old, with different cases of Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). We grouped children by the following characteristics: [...] Read more.
With its focus on robot-assisted autism therapy, this paper presents case-by-case analyses of socio-emotional outcomes of 34 children aged 3–12 years old, with different cases of Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). We grouped children by the following characteristics: ASD alone (n = 22), ASD+ADHD (n = 12), verbal (n = 11), non-verbal (n = 23), low-functioning autism (n = 24), and high-functioning autism (n = 10). This paper provides a series of separate quantitative analyses across the first and last sessions, adaptive and non-adaptive sessions, and parent and no-parent sessions, to present child experiences with the NAO robot, during play-based activities. The results suggest that robots are able to interact with children in social ways and influence their social behaviors over time. Each child with ASD is a unique case and needs an individualized approach to practice and learn social skills with the robot. We, finally, present specific child–robot intricacies that affect how children engage and learn over time as well as across different sessions. Full article
(This article belongs to the Special Issue Intricacies of Child–Robot Interaction)
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24 pages, 7122 KiB  
Article
Design, Development, and a Pilot Study of a Low-Cost Robot for Child–Robot Interaction in Autism Interventions
by Ilias A. Katsanis, Vassilis C. Moulianitis and Diamantis T. Panagiotarakos
Multimodal Technol. Interact. 2022, 6(6), 43; https://0-doi-org.brum.beds.ac.uk/10.3390/mti6060043 - 06 Jun 2022
Cited by 1 | Viewed by 2071
Abstract
Socially assistive robots are widely deployed in interventions with children on the autism spectrum, exploiting the benefits of this technology in social behavior intervention plans, while reducing their autistic behavior. Furthermore, innovations in modern technologies such as machine learning enhance these robots with [...] Read more.
Socially assistive robots are widely deployed in interventions with children on the autism spectrum, exploiting the benefits of this technology in social behavior intervention plans, while reducing their autistic behavior. Furthermore, innovations in modern technologies such as machine learning enhance these robots with great capabilities. Since the results of this implementation are promising, their total cost makes them unaffordable for some organizations while the needs are growing progressively. In this paper, a low-cost robot for autism interventions is proposed, benefiting from the advantages of machine learning and low-cost hardware. The mechanical design of the robot and the development of machine learning models are presented. The robot was evaluated by a small group of educators for children with ASD. The results of various model implementations, together with the design evaluation of the robot, are encouraging and indicate that this technology would be advantageous for deployment in child–robot interaction scenarios. Full article
(This article belongs to the Special Issue Intricacies of Child–Robot Interaction)
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16 pages, 1606 KiB  
Article
Parental Influence in Disengagement during Robot-Assisted Activities: A Case Study of a Parent and Child with Autism Spectrum Disorder
by SunKyoung Kim, Masakazu Hirokawa, Atsushi Funahashi and Kenji Suzuki
Multimodal Technol. Interact. 2022, 6(5), 39; https://0-doi-org.brum.beds.ac.uk/10.3390/mti6050039 - 18 May 2022
Viewed by 2189
Abstract
We examined the influence of a parent on robot-assisted activities for a child with Autism Spectrum Disorder. We observed the interactions between a robot and the child wearing a wearable device during free play sessions. The child participated in four sessions with the [...] Read more.
We examined the influence of a parent on robot-assisted activities for a child with Autism Spectrum Disorder. We observed the interactions between a robot and the child wearing a wearable device during free play sessions. The child participated in four sessions with the parent and interacted willingly with the robot, therapist, and parent. The parent intervened when the child did not interact with the robot, considered “disengagement with the robot”. The number and method of intervention were decided solely by the parent. This study adopted video recording for behavioral observations and specifically observed the situations before the disengagement with the robot, the child’s behaviors during disengagement, and the parent’s intervention. The results showed that mostly the child abruptly discontinued the interactions with the robot without being stimulated by the surrounding environment. The second most common reason was being distracted by various devices in the play sessions, such as the wearable device, a video camera, and a laptop. Once he was disengaged with the robot, he primarily exhibited inappropriate and repetitive behaviors accentuating the symptoms of autism spectrum disorder. The child could re-initiate the interaction with the robot with an 80% chance through the parent’s intervention. This suggests that engagement with a robot may differ depending on the parent’s participation. Moreover, we must consider types of parental feedback to re-initiate engagement with a robot to benefit from the therapy adequately. In addition, environmental distractions must be considered, especially when using multiple devices for therapy. Full article
(This article belongs to the Special Issue Intricacies of Child–Robot Interaction)
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14 pages, 2722 KiB  
Article
A Trustworthy Robot Buddy for Primary School Children
by Matthijs H. J. Smakman, Daniel F. Preciado Vanegas, Koen Smit, Sam Leewis, Youri Okkerse, Jesper Obbes, Thom Uffing, Marina Soliman, Tony van der Krogt and Lucas Tönjes
Multimodal Technol. Interact. 2022, 6(4), 29; https://0-doi-org.brum.beds.ac.uk/10.3390/mti6040029 - 14 Apr 2022
Cited by 8 | Viewed by 3811
Abstract
Social robots hold potential for supporting children’s well-being in classrooms. However, it is unclear which robot features add to a trustworthy relationship between a child and a robot and whether social robots are just as able to reduce stress as traditional interventions, such [...] Read more.
Social robots hold potential for supporting children’s well-being in classrooms. However, it is unclear which robot features add to a trustworthy relationship between a child and a robot and whether social robots are just as able to reduce stress as traditional interventions, such as listening to classical music. We set up two experiments wherein children interacted with a robot in a real-life school environment. Our main results show that regardless of the robotic features tested (intonation, male/female voice, and humor) most children tend to trust a robot during their first interaction. Adding humor to the robots’ dialogue seems to have a negative impact on children’s trust, especially for girls and children without prior experience with robots. In comparing a classical music session with a social robot interaction, we found no significant differences. Both interventions were able to lower the stress levels of children, however, not significantly. Our results show the potential for robots to build trustworthy interactions with children and to lower children’s stress levels. Considering these results, we believe that social robots provide a new tool for children to make their feelings explicit, thereby enabling children to share negative experiences (such as bullying) which would otherwise stay unnoticed. Full article
(This article belongs to the Special Issue Intricacies of Child–Robot Interaction)
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21 pages, 559 KiB  
Article
When Preschoolers Interact with an Educational Robot, Does Robot Feedback Influence Engagement?
by Mirjam de Haas, Paul Vogt and Emiel Krahmer
Multimodal Technol. Interact. 2021, 5(12), 77; https://0-doi-org.brum.beds.ac.uk/10.3390/mti5120077 - 01 Dec 2021
Cited by 3 | Viewed by 2949
Abstract
In this paper, we examine to what degree children of 3–4 years old engage with a task and with a social robot during a second-language tutoring lesson. We specifically investigated whether children’s task engagement and robot engagement were influenced by three different feedback [...] Read more.
In this paper, we examine to what degree children of 3–4 years old engage with a task and with a social robot during a second-language tutoring lesson. We specifically investigated whether children’s task engagement and robot engagement were influenced by three different feedback types by the robot: adult-like feedback, peer-like feedback and no feedback. Additionally, we investigated the relation between children’s eye gaze fixations and their task engagement and robot engagement. Fifty-eight Dutch children participated in an English counting task with a social robot and physical blocks. We found that, overall, children in the three conditions showed similar task engagement and robot engagement; however, within each condition, they showed large individual differences. Additionally, regression analyses revealed that there is a relation between children’s eye-gaze direction and engagement. Our findings showed that although eye gaze plays a significant role in measuring engagement and can be used to model children’s task engagement and robot engagement, it does not account for the full concept and engagement still comprises more than just eye gaze. Full article
(This article belongs to the Special Issue Intricacies of Child–Robot Interaction)
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9 pages, 1011 KiB  
Article
Pitch It Right: Using Prosodic Entrainment to Improve Robot-Assisted Foreign Language Learning in School-Aged Children
by Bo Molenaar, Breixo Soliño Fernández, Alessandra Polimeno, Emilia Barakova and Aoju Chen
Multimodal Technol. Interact. 2021, 5(12), 76; https://0-doi-org.brum.beds.ac.uk/10.3390/mti5120076 - 30 Nov 2021
Cited by 3 | Viewed by 2855
Abstract
Robot-assisted language learning (RALL) is a promising application when employing social robots to help both children and adults acquire a language and is an increasingly widely studied area of child–robot interaction. By introducing prosodic entrainment, i.e., converging the robot’s pitch with that of [...] Read more.
Robot-assisted language learning (RALL) is a promising application when employing social robots to help both children and adults acquire a language and is an increasingly widely studied area of child–robot interaction. By introducing prosodic entrainment, i.e., converging the robot’s pitch with that of the learner, the present study aimed to provide new insights into RALL as a facilitative method for interactive tutoring. It is hypothesized that pitch-level entrainment by a Nao robot during a word learning task in a foreign language will result in increased learning in school-aged children. The results indicate that entrainment has no significant effect on participants’ learning, contra the hypothesis. Research on the implementation of entrainment in the context of RALL is new. This study highlights constraints in currently available technologies for voice generation and methodological limitations that should be taken into account in future research. Full article
(This article belongs to the Special Issue Intricacies of Child–Robot Interaction)
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25 pages, 2182 KiB  
Article
Robot-Enhanced Language Learning for Children in Norwegian Day-Care Centers
by Till Halbach, Trenton Schulz, Wolfgang Leister and Ivar Solheim
Multimodal Technol. Interact. 2021, 5(12), 74; https://0-doi-org.brum.beds.ac.uk/10.3390/mti5120074 - 24 Nov 2021
Cited by 8 | Viewed by 3236
Abstract
In a case study, we transformed the existing learning program Language Shower, which is used in some Norwegian day-care centers in the Grorud district of Oslo municipality, into a digital solution using an app for smartphones or tablets with the option for further [...] Read more.
In a case study, we transformed the existing learning program Language Shower, which is used in some Norwegian day-care centers in the Grorud district of Oslo municipality, into a digital solution using an app for smartphones or tablets with the option for further enhancement of the presentation by a NAO robot. The solution was tested in several iterations and multiple day-care centers over several weeks. Measurements of the children’s progress across learning sessions indicated a positive impact of the program using a robot as compared to the program without a robot. In situ observations and interviews with day-care center staff confirmed the solution’s many advantages, but also revealed some important areas for improvement. In particular, the speech recognition needs to be more flexible and robust, and special measures have to be in place to handle children speaking simultaneously. Full article
(This article belongs to the Special Issue Intricacies of Child–Robot Interaction)
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