Document Type
Conference Proceeding
Publication Title
Proceedings of the Annual Meeting of the Association for Computational Linguistics
Abstract
As the world regains its footing following the COVID-19 pandemic, academia is striving to consolidate the gains made in students’ education experience. New technologies such as video-based learning have shown some early improvement in student learning and engagement. In this paper, we present ORBITS predictive engine at YOURIKA company, a video-based student support platform powered by knowledge tracing. In an exploratory case study of one master’s level Speech Processing course at the Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, half the students used the system while the other half did not. Student qualitative feedback was universally positive and compared the system favorably against current available methods. These findings support the use of artificial intelligence techniques to improve the student learning experience.
First Page
100
Last Page
107
DOI
10.18653/v1/2023.bea-1.8
Publication Date
7-13-2023
Keywords
Artificial intelligence, Computational linguistics, Speech processing
Recommended Citation
S. Shehata et al., "Enhancing Video-based Learning Using Knowledge Tracing: Personalizing Students’ Learning Experience with ORBITS," Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp. 100 - 107, Jul 2023.
The definitive version is available at https://doi.org/10.18653/v1/2023.bea-1.8
Additional Links
DOI link: https://doi.org/10.18653/v1/2023.bea-1.8
Comments
Archived thanks to ACL Anthology
License: CC by 4.0 DEED
Uploaded: April 03, 2024