Analyzing children's expectations from robotic companions in educational settings

Blancas, Maria; Vouloutsi, Vasiliki; Fernando, Samuel; Sánchez-Fibla, Martí; Zucca, Riccardo; Prescott, Tony J.; Mura, Anna; Verschure, Paul F. M. J.

doi:10.1109/humanoids.2017.8246956

Cited by 10 publications

(5 citation statements)

References 24 publications

(25 reference statements)

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“…Through this investigation, we aim to develop a comprehensive questionnaire that will enable us to understand the needs and desires of students, who are the primary users of educational robots. Moreover, we aim to compare this study's findings with students' expectations and desires to identify any gaps between expectations and reality [21].…”

Section: Purpose and Methodologymentioning

confidence: 99%

“…Of Relevance to Morph. Morphology [26] Abstract [43] Quadruped [38] Puppet-like and Humanoid [44] Multimodal [27] Abstract-Insect-Like [29] Abstract-Soft [35] Humanoid [45] Multimodal [21] Machine-Like, Humanoid and Cartoon-Like [46] Humanoid and Abstract [23] Wheeled [25] Wheeled [31,32] Zoomorphic-Parrot-Like [30] Toy-Like and Machine-Like [47] Abstract-DIY [48] Machine-Like [39] Humanoid, Zoomorphic and Machine-Like [49] Humanoid [50] Wheeled and Drone [33] Humanoid…”

Section: Educational or Notmentioning

confidence: 99%

“…Senior-grade and undergraduate students, on the contrary, prefer larger-sized educational robots with non-repetitive responses, and undergraduate students prioritize the robots' functionalities. Blancas et al [21] conducted a study investigating children's expectations of robot characteristics for interacting with them as educators or social partners. To achieve this, three different robots were employed, including one of machine-like morphology (CodiBot) and two Humanoids, one of which was a cartoon-like character capable of expressing basic facial emotions (Zeno), and the other was an android robot (Nao) with basic human-like characteristics.…”

mentioning

confidence: 99%

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Engaging Learners in Educational Robotics: Uncovering Students’ Expectations for an Ideal Robotic Platform

et al. 2023

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Extensive research has been conducted on educational robotics (ER) platforms to explore their usage across different educational levels and assess their effectiveness in achieving desired learning outcomes. However, the existing literature has a limitation in regard to addressing learners’ specific preferences and characteristics regarding these platforms. To address this gap, it is crucial to encourage learners’ active participation in the design process of robotic platforms. By incorporating their valuable feedback and preferences and providing them with platforms that align with their interests, we can create a motivating environment that leads to increased engagement in science, technology, engineering and mathematics (STEM) courses and improved learning outcomes. Furthermore, this approach fosters a sense of absorption and full engagement among peers as they collaborate on assigned activities. To bridge the existing research gap, our study aimed to investigate the current trends in the morphology of educational robotics platforms. We surveyed students from multiple schools in Greece who had no prior exposure to robotic platforms. Our study aimed to understand students’ expectations of an ideal robotic companion. We examined the desired characteristics, modes of interaction, and socialization that students anticipate from such a companion. By uncovering these attributes and standards, we aimed to inform the development of an optimal model that effectively fulfills students’ educational aspirations while keeping them motivated and engaged.

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Section: Purpose and Methodologymentioning

confidence: 99%

Section: Educational or Notmentioning

confidence: 99%

mentioning

confidence: 99%

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Engaging Learners in Educational Robotics: Uncovering Students’ Expectations for an Ideal Robotic Platform

et al. 2023

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“…A promising solution appears to be the involvement of various stakeholders, and end-users of the SAR in particular, to define their requirements. Indeed, there is evidence for stakeholders' involvement in the participatory design of SARs for educational purposes [6][7][8][9][10]. However, these participatory design approaches are scattered and bewildering.…”

Section: Introductionmentioning

confidence: 99%

“…However, these participatory design approaches are scattered and bewildering. They usually focus on one aspect of SAR such as the social role [7] or the embodiment of the robot [6,[8][9][10], omitting other features such as the sophistication of interaction, which refers to interactive modalities employed in SAR such as speech or gestures. Hence, the existing evidence allows the developers to build a SAR for educational purposes considering the stakeholders' requirements only for a few design features.…”

Section: Introductionmentioning

confidence: 99%

Designing a Socially Assistive Robot for Education Through a Participatory Design Approach: Pivotal Principles for the Developers

Pnevmatikos

Fachantidis

2021

Int J of Soc Robotics

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Designing socially assistive robots (SARs) for educational purposes can be a challenging task for developers. Developers need to identify the combination of a particular set of features to include in the design of a SAR. Participatory design approaches can be a promising solution since stakeholders can suggest, through their involvement, the requirements that could meet their needs and expectations. Still, such approaches for designing a SAR for education are scattered and bewildering, focusing on aspects of the robot such as the role or the appearance. The current study aimed to map stakeholders' requirements regarding the design of a SAR exploited for educational purposes as well as to provide a set of guiding design principles for developers. A qualitative focus group discussion took place, and the participants were 127 (65 were female) stakeholders from five European countries, representing various affiliations in the field of education. A deductive qualitative content analysis approach revealed 121 themes of analysis, which fitted into 11 theory-driven categories regarding the use of the SARs in the class settings, their appearance, and their voice commands. Additionally, 46 themes of analysis were classified under five new categories following an inductive approach. The results of the deductive and inductive content analysis were further exploited in two Two-Step Cluster Analyses. The analyses revealed five tentative combinations of the dimensions exploited for the design of a SAR sketched by education stakeholders. The findings of the current study are discussed, providing pivotal guiding principles for the developers of SARs for education.

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When it is ok to give the Robot Less: Children’s Fairness Intuitions Towards Robots

Ayalon,

Hok,

Shaw

et al. 2023

Int J of Soc Robotics

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Children develop intuitions about fairness relatively early in development. While we know that children believe other humans care about distributional fairness, considerably less is known about whether they believe other agents, such as robots, do as well. In two experiments (N = 273) we investigated 4- to 9-year-old children’s intuitions about whether robots would be upset about unfair treatment as human children. Children were told about a scenario in which resources were being split between a human child and a target recipient: either another child or a robot across two conditions. The target recipient (either child or robot) received less than another child. They were then asked to evaluate how fair the distribution was, and whether the target recipient would be upset. Both Experiment 1 and 2 used the same design, but Experiment 2 also included a video demonstrating the robot’s mechanistic “robotic” movements. Our results show that children thought it was more fair to share unequally when the disadvantaged recipient was a robot rather than a child (Experiment 1 and 2). Furthermore, children thought that the child would be more upset than the robot (Experiment 2). Finally, we found that this tendency to treat these two conditions differently became stronger with age (Experiment 2). These results suggest that young children treat robots and children similarly in resource allocation tasks, but increasingly differentiate them with age. Specifically, children evaluate inequality as less unfair when the target recipient is a robot, and think that robots will be less angry about inequality.

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Analyzing children's expectations from robotic companions in educational settings

Cited by 10 publications

References 24 publications

Engaging Learners in Educational Robotics: Uncovering Students’ Expectations for an Ideal Robotic Platform

Engaging Learners in Educational Robotics: Uncovering Students’ Expectations for an Ideal Robotic Platform

Designing a Socially Assistive Robot for Education Through a Participatory Design Approach: Pivotal Principles for the Developers

When it is ok to give the Robot Less: Children’s Fairness Intuitions Towards Robots

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