@inproceedings{a9c89b2d38874e59b0c431053b640dc7,
title = "Quantifying Semantic Congruence to Aid in Technical Gesture Generation in Computing Education",
abstract = "Generation of gestures that conform to the syntax of a gestural language (such as American Sign Language (ASL)) and are congruent with the meaning of a technical term, has significant impact on enhancing the participation of people with hearing disabilities in Technical Higher Education. In this paper, we present a semantic congruity metric formulated to aid in generation of new gestures conforming to the syntax of ASL while being congruent with the meaning of the technical word and show the usage and validity of the metric using 70 ASL gestures.",
keywords = "Accessible computing education, Gesture learning, Semantic congruity",
author = "Sameena Hossain and Ayan Banerjee and Gupta, {Sandeep K.S.}",
note = "Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.; 23rd International Conference on Artificial Intelligence in Education, AIED 2022 ; Conference date: 27-07-2022 Through 31-07-2022",
year = "2022",
doi = "10.1007/978-3-031-11647-6_63",
language = "English (US)",
isbn = "9783031116469",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "329--333",
editor = "Rodrigo, {Maria Mercedes} and Noburu Matsuda and Cristea, {Alexandra I.} and Vania Dimitrova",
booktitle = "Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners{\textquoteright} and Doctoral Consortium - 23rd International Conference, AIED 2022, Proceedings",
address = "Germany",
}