Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Supporting Therapists’ Assessment in Parent-Mediated Training through Autonomous Data Collection
 
conference poster not in proceedings

Supporting Therapists’ Assessment in Parent-Mediated Training through Autonomous Data Collection

Tozadore, Daniel C.  
•
Tozadore, Michele C.
•
Gill, Maria S. C. A.
July 27, 2022
23rd International Conference on Artificial Intelligence in Education

Parental Training is a methodology where therapists teach caregivers how to train their kids in specific behaviors practicing. It can be used in verbal behavior acquisition for children with autism mediated by the parents. In this paper, we are presenting an innovative software that aids the assessment of children’s tact acquisition where therapists can design interactive activities to support the remote measurement of the parental training progress. The developed software stores in its server the child's answers and autonomously compute, in run time, the child's face deviation through an Artificial Intelligence algorithm. The therapists have access to such data and can assess children’s performance by that without watching the interaction. The performed experiment presents initial validation of the proposed system utilization by one therapist and one dyad of a child with autism and the mother. The system was applied to the child’s evaluation phase of an entire parental training cycle in the Brazilian Portuguese language context. Through the interviews and questionnaires, all users claimed they considered our solution adequate and robust for its purposes. After comparing the child's performance in a baseline activity and an activity after the training session, the software was able to provide to the therapist the data to confirm an enhancement in the child’s tact acquisition.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

AIED_2022_Extended_Abstract.pdf

Type

Postprint

Version

http://purl.org/coar/version/c_ab4af688f83e57aa

Access type

openaccess

License Condition

copyright

Size

236.33 KB

Format

Adobe PDF

Checksum (MD5)

57f70efe82a47457ed3dd91e2fbffe83

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés