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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Daniel Tozadore Anne-Marie Rusu Computer-Human Interaction in Learning and Instruction (CHILI) Lab EPFL Lausanne Switzerland

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Social robots are widely used for educational activities, especially to attract children’s attention. As a side effect, pupils’ excitement can suppress their focus on the tutors and the content being approached. A potential solution to tackle this issue is to equip the robot with storytelling strategies, which have been growing remarkably in recent years thanks to advances in Large Language Models. However, few studies are still addressing the resulting application in real-world conditions. In this work, we are exploring the GPT-3.5 model for story generation based on content to be approached in maker-space classes. To achieve our goals, we implemented a web application for content insertion that connects to the robot through ROS. The proposal was validated in two phases: a first phase of interviews with 5 tutors of maker-space to present our solution and get their feedback, and two 90-minute sessions with pupils for real-world validation. Results suggested the proposal has high potential for supporting multiple languages and generating suitable stories for diverse contexts. Furthermore, adding social behaviors, as encouragement and sentiment analysis, can help in the students’ expectation handling.

关键词： Sentiment analysis Large language models Social robots Pipelines Robot sensing systems Proposals Pupils Interviews

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Immediate effects of short-duration wellbeing practices on children’s handwriting and posture guided by a social robot

Immediate effects of short-duration wellbeing practices on c...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Daniel Carnieto Tozadore Melike Cezayirlioglu Chenyang Wang Barbara Bruno Pierre Dillenbourg Computer-Human Interaction in Learning and Instruction (CHILI) Lab EPFL Lausanne Switzerland

Handwriting practising, as any other repetitive task, often leads the practiser to an overconcentration state where their performance might be affected by postural and mental fatigue. Short breaks to perform unrelated activities, especially relaxation exercises, have shown to be a simple alternative to soften or postpone this phenomenon. Therefore, in this paper we are investigating the immediate effects of different types of short-duration relaxation exercises in the handwriting and posture of children aged from 8 to 10 in handwriting training. We divided 40 children in two groups performing the sessions, guided by a social robot, with small exercises of mindfulness or stretching in the middle of their training. Additionally, we analysed participants’ perceptions towards the robot leading these interactions. Results showed improvements in participants’ handwriting quality and posture maintenance regardless of the condition. Additionally, more positive feedback about the pause was reported from individuals in the mindfulness condition.

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Correction to: Many are the ways to learn: Identifying multi-modal behavioral profiles of collaborative learning in constructivist activities

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International Journal of computer-Supported Collaborative learning 2022年 1-2页

作者： Nasir, Jauwairia Kothiyal, Aditi Bruno, Barbara Dillenbourg, Pierre Computer‑Human Interaction in Learning and Instruction (CHILI) Lab Swiss Federal Institute of Technology in Lausanne (EPFL) Lausanne Switzerland

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Questioning Wizard of Oz: Effects of Revealing the Wizard behind the Robot

Questioning Wizard of Oz: Effects of Revealing the Wizard be...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Jauwairia Nasir Pierre Oppliger Barbara Bruno Pierre Dillenbourg Computer-Human Interaction in Learning and Instruction (CHILI) Lab Swiss Federal Institute of Technology in Lausanne (EPFL) Switzerland

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

Wizard of Oz, a very commonly employed technique in human-robot interaction, faces the criticism of being deceptive as the humans interacting with the robot are told, if at all, only at the end of their interaction that there was in fact a human behind the robot. What if the robot reveals the wizard behind itself very early in the interaction? We built a deep wizard of Oz setup to allow for a robot to play together with a human against a computer AI in the context of Connect 4 game. This cooperative game interaction against a common opponent is then followed by a conversation between the human and the robot. We conducted an exploratory user study with 29 adults with three conditions where the robot reveals the wizard, lies about the wizard, and does not say anything, respectively. We also split the data based on how the participants perceive the robot in terms of autonomy. Using different metrics, we evaluate how the users interact with and perceive the robot in both the experimental and perceived conditions. We find that while there is indeed a significant difference in the participants willingness to follow robots suggestions between the experimental conditions as well as in the effort they put to prove themselves as humans (reverse Turing test), there isn’t any significant difference in their robot perception. Additionally, how humans perceive whether the robot is tele-operated or autonomous seems to be indifferent to the robot revealing its identity, i.e., the pre-conceived notions may be uninfluenced even if the robot explicitly states otherwise. Lastly, interestingly in the perception based conditions, absence of statistical significance may suggest that, in certain contexts, wizard of oz may not require hiding the wizard after all.

关键词： Atmospheric measurements Sociology Social robots Games Oral communication Particle measurements Time measurement

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How a Social Robot’s Vocalization Affects Children’s Speech, learning, and interaction

How a Social Robot’s Vocalization Affects Children’s Speec...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Lauren L. Wright Aditi Kothiyal Kai O. Arras Barbara Bruno Computer-Human Interaction in Learning and Instruction (CHILI) Lab Swiss Federal Institute of Technology in Lausanne (EPFL) Switzerland Bosch Corporate Research Stuttgart

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

A wider incorporation of robots into classrooms is hampered by current technological limitations on full autonomy in social robots. Automated speech recognition, for example, a key enabler for vocal communication, is still unable to perform with sufficient accuracy. Past studies have shown that humans adjust their speech patterns to accommodate less skilled interlocutors. If such a response holds in human-robot interactions as well, we may be able to exploit it to lessen the burden on social robots and enable rich, autonomous vocal communication. In this paper we explore whether a robot’s speaking ability could have an impact on children’s speech patterns, learning, and engagement by designing an interaction where a child and a robot collaborate on a Tower of Hanoi puzzle. Sixteen children aged 7-14 completed this collaborative task partnered with a social robot that communicated with either high verbal (full sentences), low verbal (short phrases or single words), or nonverbal (sound-based utterances) vocalization. While we found no significant impact on children’s speech patterns or learning due to the robot’s method of vocalization, children in the non-verbal condition had a significantly lower perception of the robot’s intelligence along with higher rates of providing feedback and more instances of undoing its moves. This suggests that a link may exist between a robot’s perceived speaking ability and children’s confidence in that robot’s overall intelligence and capability in a collaborative task, as well as their empathy towards a peer they perceive as less skilled in the task.

关键词： Social robots Poles and towers Education Collaboration Speech recognition Aging Speech

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Designing Online Multiplayer Games with Haptically and Virtually Linked Tangible Robots to Enhance Social interaction in Therapy

Designing Online Multiplayer Games with Haptically and Virtu...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Arzu Guneysu Ozgur Hala Khodr Mehdi Akeddar Michael Roust Pierre Dillenbourg Computer Human Interaction in Learning and Instruction Lab (CHILI) EPFL Lausanne Switzerland Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

The social aspects of therapy and training are important for patients to avoid social isolation and must be considered when designing a platform, especially for home-based rehabilitation. We proposed an online version of the previously proposed tangible Pacman game for upper limb training with haptic-enabled tangible Cellulo robots. Our main objective is to enhance motivation and engagement through social integration and also to form a gamified multiplayer rehabilitation at a distance. Thus, allowing relatives, children, and friends to connect and play with their loved ones while also helping them with their training from anywhere in the world. As well as connecting therapists to their patients through haptically linking capabilities. This is especially relevant when there are social distancing measures which might isolate the elderly population, a majority of all rehabilitation patients.

关键词： Training Pediatrics Sociology Medical treatment Games human factors Social factors

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A game-based approach for evaluating and customizing handwriting training using an autonomous social robot

A game-based approach for evaluating and customizing handwri...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Daniel Carnieto Tozadore Chenyang Wang Giorgia Marchesi Barbara Bruno Pierre Dillenbourg Computer-Human Interaction in Learning and Instruction (CHILI) Lab EPFL Lausanne Switzerland MOBOTS Group EPFL Lausanne Switzerland Dept. DIBRIS University of Genova Italy

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

Handwriting learning is a long and complex process that takes about ten years to be fully mastered. Nearly one-third of all children aged 4-12 experiences handwriting difficulties and, sadly, most of them are left to fight them on their own, due to the scarcity of tools for the detection and remediation of such difficulties. Building on state-of-the-art digital solutions for automated handwriting assessment and the training of specific handwriting-related skills, in this article we discuss requirements, rationale, and architecture of a system for handwriting training, which relies on a social robot as a mediator agent, offering personalized training and suggestions. The system is envisioned to operate autonomously and to support long-term interactions via personalization. Preliminary validation of the system in an experiment with 31 children showed its potential not only for autonomously guiding handwriting training sessions, but also for its inclusion in the teachers’ practice.

关键词： Training Architecture Social robots Buildings Systems architecture computer architecture Aging

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An HMM-based Real-time Intervention Methodology for a Social Robot Supporting learning

An HMM-based Real-time Intervention Methodology for a Social...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Jauwairia Nasir Mortadha Abderrahim Barbara Bruno Pierre Dillenbourg Human-Centered Artificial Intelligence (HCAI) Lab University of Augsburg Germany Computer-Human Interaction in Learning and Instruction (CHILI) Lab Swiss Federal Institute of Technology in Lausanne (EPFL) Switzerland Socially Assistive Robotics with Artificial Intelligence (SARAI) Lab Karlsruhe Institute of Technology (KIT) Germany

To make social robots effective in education, they need to be autonomous both in terms of assessing the student’s engagement state as well as intervening effectively in soft real-time when necessary. Hidden Markov Model (HMM) is an interpretable machine learning technique for modeling temporal data that is commonly used post-hoc to analyse latent learning processes. In this paper, we contribute by proposing an HMM-based intervention methodology for assessing and classifying the state of the student as either productive or unproductive in soft real-time. The system identifies and tracks states and patterns not conducive to learning, and a robot intervention is triggered whenever a too-high non-productive engagement is detected. In a pilot study with 22 children, we evaluate this methodology in terms of both 1) the effectiveness of the interventions on the students’ learning gains and on behaviors found conducive to learning, and 2) the students’ perception of the robotic interventions. Results suggest that the robot interventions have a positive effect on the post-test scores relative to the baseline robot, although there isn’t a significant difference in the learning gains. Moreover, interventions that try to induce reflective behaviors are most effective in inducing the required learning behavior, followed by communication-inducing interventions. Lastly, students’ perception of intervention usefulness does not reflect their actual effectiveness.

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Correction: How are primary school computer science curricular reforms contributing to equity? Impact on student learning, perception of the discipline, and gender gaps

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International Journal of STEM Education 2023年第1期10卷 1-3页

作者： El‑Hamamsy, Laila Bruno, Barbara Audrin, Catherine Chevalier, Morgane Avry, Sunny Zufferey, Jessica Dehler Mondada, Francesco MOBOTS Group EPFL Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland LEARN Center for Learning Sciences EPFL Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland Computer Human Interaction in Learning and Instruction (CHILI) Laboratory EPFL Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland University of Teacher Education (Haute Ecole Pédagogique) Vaud Lausanne Switzerland

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Design of Dynamic Tangible Workspaces for Games: Application on Robot-Assisted Upper Limb Rehabilitation

Design of Dynamic Tangible Workspaces for Games: Application...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Arzu Guneysu Ozgur Barbara Bruno Victor Taburet Ayberk Özgür Pierre Dillenbourg Computer Human Interaction in Learning and Instruction Laboratory (CHILI) MOBOTS Swiss Federal Institute of Technology (EPFL) Lausanne Switzerland

ISBN: (数字)9781728160757

ISBN: (纸本)9781728160764

A key element for the success of any game is its ability to produce a different experience at each round, thus keeping the player engagement high. This is particularly important for those games that also have a serious objective, such as gamified rehabilitation systems, aiming at encouraging patients in performing home rehabilitation exercises. In all cases, a game element which is typically static is the workspace, i.e. the "floor" upon which the game takes place. This is especially true for robot-assisted rehabilitation games, where the workspace must satisfy the requirements given by the robot's locomotion and localization systems, as well as the patient's exercise motion *** this article we present a simple yet effective solution for designing dynamic and customizable tangible workspaces, which relies on hexagonal tiles and our previously proposed Cellulo localization system. These "hextiles" can be easily tangibly rearranged at each game round to yield a desired workspace shape and configuration, allowing tabletop mobile robots to move continuously within each new workspace. We ground our solution in the context of robot-assisted rehabilitation, where high adaptability is crucial for the efficacy of the solution, and propose a dynamic extension of our "tangible Pacman" rehabilitation *** show that the proposed solution allows for adaptation in range of motions, exercise types, physical and cognitive difficulty, besides reducing repetitiveness.

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