Literature DB >> 33501198

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

Arzu Guneysu Ozgur1, Ayberk Özgür1, Thibault Asselborn1, Wafa Johal2, Elmira Yadollahi1, Barbara Bruno1,3, Melissa Skweres4, Pierre Dillenbourg1.   

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.
Copyright © 2020 Guneysu Ozgur, Özgür, Asselborn, Johal, Yadollahi, Bruno, Skweres and Dillenbourg.

Entities:  

Keywords:  handwriting; haptic devices; interactive learning; iterative design; occupational therapy; robots for education; special education; tangible robots

Year:  2020        PMID: 33501198      PMCID: PMC7805874          DOI: 10.3389/frobt.2020.00029

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


  9 in total

1.  Handwriting and perceptual-motor skills in clumsy, dysgraphic, and 'normal' children.

Authors:  A F Maeland
Journal:  Percept Mot Skills       Date:  1992-12

2.  Haptics in teaching handwriting: the role of perceptual and visuo-motor skills.

Authors:  Florence Bara; Edouard Gentaz
Journal:  Hum Mov Sci       Date:  2011-01-26       Impact factor: 2.161

3.  Fine motor deficiencies in children diagnosed as DCD based on poor grapho-motor ability.

Authors:  B C Smits-Engelsman; A S Niemeijer; G P van Galen
Journal:  Hum Mov Sci       Date:  2001-03       Impact factor: 2.161

Review 4.  Handwriting development, competency, and intervention.

Authors:  Katya P Feder; Annette Majnemer
Journal:  Dev Med Child Neurol       Date:  2007-04       Impact factor: 5.449

5.  Development, reliability, and validity of the Handwriting Proficiency Screening Questionnaire (HPSQ).

Authors:  Sara Rosenblum
Journal:  Am J Occup Ther       Date:  2008 May-Jun

6.  Children's first handwriting productions show a rhythmic structure.

Authors:  Elena Pagliarini; Lisa Scocchia; Mirta Vernice; Marina Zoppello; Umberto Balottin; Sana Bouamama; Maria Teresa Guasti; Natale Stucchi
Journal:  Sci Rep       Date:  2017-07-17       Impact factor: 4.379

7.  Automated human-level diagnosis of dysgraphia using a consumer tablet.

Authors:  Thibault Asselborn; Thomas Gargot; Łukasz Kidziński; Wafa Johal; David Cohen; Caroline Jolly; Pierre Dillenbourg
Journal:  NPJ Digit Med       Date:  2018-08-31

8.  Haptic guidance improves the visuo-manual tracking of trajectories.

Authors:  Jérémy Bluteau; Sabine Coquillart; Yohan Payan; Edouard Gentaz
Journal:  PLoS One       Date:  2008-03-12       Impact factor: 3.240

Review 9.  Basic and supplementary sensory feedback in handwriting.

Authors:  Jérémy Danna; Jean-Luc Velay
Journal:  Front Psychol       Date:  2015-02-20
  9 in total
  2 in total

1.  "It Is Not the Robot Who Learns, It Is Me." Treating Severe Dysgraphia Using Child-Robot Interaction.

Authors:  Thomas Gargot; Thibault Asselborn; Ingrid Zammouri; Julie Brunelle; Wafa Johal; Pierre Dillenbourg; Dominique Archambault; Mohamed Chetouani; David Cohen; Salvatore M Anzalone
Journal:  Front Psychiatry       Date:  2021-02-23       Impact factor: 4.157

2.  Machine Teaching for Human Inverse Reinforcement Learning.

Authors:  Michael S Lee; Henny Admoni; Reid Simmons
Journal:  Front Robot AI       Date:  2021-06-30
  2 in total

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