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Ayberk Özgür Doctoral Student Other, EPFL Funding: Matching funds ayberk.ozgur@epfl.ch +41 21 693 29 83

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Cellulo: Versatile Handheld Robots for Education

  • Authors: Ozgur, Ayberk; Lemaignan, Séverin; Johal, Wafa; Beltran, Maria; Briod, Manon; Pereyre, Léa; Mondada, Francesco; Dillenbourg, Pierre

In this article, we present Cellulo, a novel robotic platform that investigates the intersection of three ideas for robotics in education: designing the robots to be versatile and generic tools; blending robots into the classroom by designing them to be pervasive objects and by creating tight interactions with (already pervasive) paper; and finally considering the practical constraints of real classrooms at every stage of the design. Our platform results from these considerations and builds on a unique combination of technologies: groups of handheld haptic-enabled robots, tablets and activity sheets printed on regular paper. The robots feature holonomic motion, haptic feedback capability and high accuracy localization through a microdot pattern overlaid on top of the activity sheets, while remaining affordable (robots cost about EUR 125 at the prototype stage) and classroom-friendly. We present the platform and report on our first interaction studies, involving about 230 children.

Posted on: January 9, 2017

Iterative Design and Evaluation of a Tangible Robot-Assisted Handwriting Activity for Special Education

Authors: Guneysu Ozgur, A.; Özgür, A.; Asselborn, T.; Johal, W.; Yadollahi, E.; Bruno, B.; Skweres, M.; Dillenbourg, P.

Abstract

In this article we investigate the role of interactive haptic-enabled tangible robots in supporting the learning of cursive letter writing for children with attention and visuomotor coordination issues. We focus on the two principal aspects of handwriting that are linked to these issues: Visual perception and visuomotor coordination. These aspects, respectively, enhance two features of letter representation in the learner’s mind in particular, namely the shape (grapheme) and the dynamics (ductus) of the letter, which constitute the central learning goals in our activity. Building upon an initial design tested with 17 healthy children in a preliminary school, we iteratively ported the activity to an occupational therapy context in 2 different therapy centers, in the context of 3 different summer school camps involving a total of 12 children having writing difficulties. The various iterations allowed us to uncover insights about the design of robot-enhanced writing activities for special education, specifically highlighting the importance of ease of modification of the duration of an activity as well as of adaptable frequency, content, flow and game-play and of providing a range of evaluation test alternatives. Results show that the use of robot-assisted handwriting activities could have a positive impact on the learning of the representation of letters in the context of occupational therapy (V = 1, 449, p < 0.001, r = 0.42). Results also highlight how the design changes made across the iterations affected the outcomes of the handwriting sessions, such as the evaluation of the performances, monitoring of the performances, and the connectedness of the handwriting.

Reference

  • Published in: Frontiers in Robotics and AI (Volume: 7 Issue: 29, 2020)
  • DOI: 10.3389/frobt.2020.00029
  • Read paper
  • https://www.frontiersin.org/articles/10.3389/frobt.2020.00029/full

  • Date: 2020
Posted on: May 10, 2020

Towards an Adaptive Upper Limb Rehabilitation Game with Tangible Robots

  • Authors: Güneysu Özgür, Arzu; Faucon, Louis P.; Maceira-Elvira, Pablo; Wessel, Maximilian J.; Johal, Wafa; Ozgur, Ayberk; Cadic-Melchior, Andeol; Hummel, Friedhelm C.; Dillenbourg, Pierre

A key feature of a successful game is its ability to provide the player with an adequate level of challenge. However, the objective of difficulty adaptation in serious games is not only to maintain the player’s motivation by challenging, but also to ensure the completion of training objectives. This paper describes our proposed upper-limb rehabilitation …

Posted on: October 20, 2019

Windfield: Demonstrating Wind Meteorology with Handheld Haptic Robots

  • Authors: Ozgur, Ayberk; Johal, Wafa; Mondada, Francesco; Dillenbourg, Pierre

One of the main issues with the acceptance of robotic tools in schools is the extracurricular aspect of the learning activities using these robots. In the Cellulo project, we developed a novel robotic platform that aims to provide a ubiquitous, versatile and practical tool for teachers with subjects varying among the different topics at their respective school curricula. In order to show the potential of Cellulo in the classroom as part of standard curricular activities, we designed a learning activity called Windfield that aims to teach the atmospheric formation mechanism of wind to early middle school children.

Posted on: June 9, 2017

Windfield: Learning Wind Meteorology with Handheld Haptic Robots

  • Authors: Ozgur, Ayberk; Johal, Wafa; Mondada, Francesco; Dillenbourg, Pierre

This article presents a learning activity and its user study involving the Cellulo platform, a novel versatile robotic tool designed for education. In order to show the potential of Cellulo in the classroom as part of standard curricular activities, we designed a learning activity called Windfield that aims to teach the atmospheric formation mechanism of wind to early middle school children. The activity involves a didactic sequence, introducing the Cellulo robots as hot air balloons and enabling children to feel the wind force through haptic feedback. We present a user study, designed in the form of a real hour-long lesson, conducted with 24 children in 8 groups who had no prior knowledge in the subject. Collaborative metrics within groups and individual performances about the learning of key concepts were measured with only the hardware and software integrated in the platform in a completely automated manner. The results show that almost all participants showed learning of symmetric aspects of wind formation while about half showed learning of asymmetric vectorial aspects that are more complex.

Posted on: January 9, 2017