R4L @HRI2017

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Proceedings

Program

Room Hinterbühne (2nd Floor)

9:00 – 9:10

Introduction

9:10 – 9:40

Keynote by Pierre Dillenbourg

9:40 – 10:30

SESSION 1

A Humanoid Robot as a Language Tutor

Johanna Hemminki and Anne Erkinheimo-Kyllönen

 

A Persuasive Storyteller Robot: Pilot Study

Raul Paradeda, Maria José Ferreira, Carlos Martinho, João Dias and Ana Paiva

 

Comparing L2 Word Learning through a Tablet or Real Objects: What Benefits Learning Most?

Rianne Vlaar, Josje Verhagen, Ora Oudgenoeg-Paz and Paul Leseman

 

Exploring the Effect of Gestures and Adaptive Tutoring on Children’s Comprehension of L2 Vocabularies

Jan de Wit, Thorsten Schodde, Bram Willemsen, Kirsten Bergmann, Mirjam de Haas, Stefan Kopp, Emiel Krahmer and Paul Vogt

10:30 – 11:00

Coffee Break + poster session 1
Pillared Hall first floor

11:00 – 12:00

SESSION 2

Robot-Based Learning Design for Young Children

Yanghee Kim and Diantha Smith

 

Teaching Assistant Robot Development by PRINTEPS

Chihiro Nishimoto, Shunsuke Akashiba, Takeshi Morita and Takahira Yamaguchi

 

Towards Designing a Socially Assistive Robot for Adaptive and Personalized Cognitive Training

Konstantinos Tsiakas, Cheryl Abellanoza, Maher Abujelala, Michalis Papakostas, Tasnim Makada and Fillia Makedon

 

ProCRob Architecture for Personalized Social Robotics

Pouyan Ziafati, Francisco J Rodríguez Lera, Andreia Pinto Costa, Aida Nazarikhorram and Leon Van Der Torre

 

Has Uncanny Valley Feeling an Impact on Learning: A preliminary Experiment performed in a French Elementary School

Bertrand Tondu

12:00 – 13:00

Lunch

13:00 – 14:15

Panel Session

14:15 – 15:00

Semi-structured group discussions

15:00 – 15:30

Coffee Break + poster session 2

Pillared Hall first floor

15:30 – 17:00

Plenary discussion & Wrap up

Overview

An increasing amount of HRI research focuses on the development of social robots acting as tutors. While robots have been popular as a focus for STEM teaching (see Lego Mindstorms or Thymio), the use of robots as tutors is novel. The field of HRI has started reporting on how to make effective robot tutors and how to measure their efficacy. These studies have shown that the potential of robots in educational settings is inarguable: robot can provide educational content tailored to the individual, something which is missing from current educational settings. They also have the potential to enhance learning via kinesthetic interaction, can improve the learner’s self-esteem and can provide empathic feedback. Finally, robots have been shown to engage the learner, to motivate her in the learning task or to enhance collaboration in a group.
However, many questions still remain. For instance, what interaction strategies aid learning, and which hamper learning? How can we deal with the current technical limitations of robots? How should effective lessons be developed and implemented on a robot? Answering these and other questions requires a multidisciplinary effort, including contributions from pedagogy, developmental psychology, (computational) linguistics, artificial intelligence and HRI, among others.
The aim of this workshop is to engage scholars who aim to gain expertise in education and in robotics (from instructional design to inverse kinematics, ROS to ZPD, Markov to Piaget) into a new  interdisciplinary community working on educational robotics. Participants will benefit from hearing from the forefront of field and from discussions on how to move from fundamental research towards the development of market-ready educational robots.
 

Topics include (but are not limited to) the following

  • Adaptive mechanisms for robot tutors, personalization and adaptation algorithms for tutoring interactions
  • Theories and methods for tutoring (pedagogical and  language acquisition)
  • Engagement in educational human-robot interaction   
  • Gain in learning vs fun in learning with a robot   
  • Kinesthetic and non-verbal communication in human-robot interaction   
  • Attachment and learning with a social robot (social and cognitive development)
  • Impact of embodiment on learning  
  • Shared knowledge and knowledge modelling in HRI  
  • Technical innovation in learning or teaching robots
  • Rehabilitation and reeducation
  • Long term learning interactions, design and methodologies for repeated human-robot encounters
  • Human-robot collaborative learning
  • Human-robot creativity              
  • Design of autonomous systems for tutoring interactions
  • Privacy and ethical issues in robot tutoring applications

Format and Submission

We invite contributions spanning the areas of education and robotics. We explicitly encourage the submission of papers describing work in progress, or containing preliminary results to discuss with the community. Submission papers should range from 4 to 6 pages (including references) . The accepted papers will be published on the workshop website.
Templates (sigconf):
http://www.acm.org/sigs/publications/proceedings-templates

The maximum file size is 2 MB.  Submissions should be in PDF format through Easy Chair:
https://easychair.org/conferences/?conf=r4lhri2017

Organization Committee

Wafa Johal, École Polytechnique Fédérale Lausanne, Switzerland, wafa.johal@epfl.ch.
Paul Vogt
, Tilburg University, Netherlands, p.a.vogt@uvt.nl.
James Kennedy, Plymouth University, U.K., james.kennedy@plymouth.ac.uk.
Mirjam de Haas, Tilburg University, the Netherlands, Mirjam.dehaas@uvt.nl.
Ana Paiva, IST, University of Lisbon, Portugal, ana.paiva@inesc-id.pt.
Ginevra Castellano, Uppsala University, Sweden, ginevra.castellano@it.uu.se.
Sandra Okita, Teachers College – Columbia University, United States, Okita@exchange.tc.columbia.edu.
Fumihide Tanaka, University of Tsukuba, tanaka@iit.tsukuba.ac.jp.
Tony Belpaeme, Plymouth University, U.K. and Ghent University, tony.belpaeme@plymouth.ac.uk.
Pierre Dillenbourg, École Fédérale Polytechnique Lausanne, Switzerland, pierre.dillenbourg@epfl.ch.

Acknowledgements

nccrrobtics Swiss National Science Foundation National Centre of Competence in Research Robotics
L2tor EU H2020 L2TOR project (grant no. 688014)