Engendering Trust in Automated Feedback: A Two Step Comparison of Feedbacks in Gesture Based Learning

Sameena Hossain, Azamat Kamzin, Venkata Naga Sai Apurupa Amperayani, Prajwal Paudyal, Ayan Banerjee, Sandeep K.S. Gupta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Advances in AI and Visual Recognition have paved the pathway for cutting edge research in Gesture Recognition. While automated feedback is able to open doors for newer opportunities in gesture based learning and practice, the effectiveness of these feedback as compared to manual feedback remains as a question in the minds of the users. For learners of American Sign Language (ASL), automated feedback generated by an application often causes a sense of apprehension because: a) learners are unaware of the automated feedback generation process, and b) learners fear that they can not trust the automated feedback as it may not be as good as the manual feedback. We use an ASL learning application that provides fine grained explainable feedback and follow a two step process to present a comparison between the automated feedback and the manual feedback provided by experts.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 22nd International Conference, AIED 2021, Proceedings
EditorsIdo Roll, Danielle McNamara, Sergey Sosnovsky, Rose Luckin, Vania Dimitrova
PublisherSpringer Science and Business Media Deutschland GmbH
Pages190-202
Number of pages13
ISBN (Print)9783030782917
DOIs
StatePublished - 2021
Externally publishedYes
Event22nd International Conference on Artificial Intelligence in Education, AIED 2021 - Virtual, Online
Duration: Jun 14 2021Jun 18 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12748 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Artificial Intelligence in Education, AIED 2021
CityVirtual, Online
Period6/14/216/18/21

Keywords

  • Automated feedback
  • Gesture based learning
  • Inclusion

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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