Abstract—2020 has been a challenging year for the
educational field due to the COVID-19 virus. Changing to online
learning was not easy for both the students and the educators.
In an attempt to address the problems of online learning to help
educators around the world, this paper proposes unravel
application to facilitate the job of educators and give them a
smooth experience while providing educational materials to
their students. Unravel is a web-based solution that enables
educators from all backgrounds to upload their lectures to an
online cloud video hosting service. Using cutting-edge Speech to
Text Technology and NLP tools, video files are transcribed, and
a timeline is provided by the application which allows the user
to manipulate the file using the generated text. It facilitates the
video editing process for users with no video editing experience
via an intuitive graphical user interface. The platform will also
enable educators to monitor the students and get analytics from
the system about the views and will enable an anonymous
feedback system so educators can get reviews from their
students. The objective of the proposed approach is to build a
comprehensive platform that fills the gap between educators
and students while unraveling the complex educational
problems in online learning.
Index Terms—AI, NLP, web services, online learning, web application.
Dalia Mohamed Sobhy is with Computer Engineering Department, Arab Academy of Science and Technology and Maritime Transport, Alexandria, Egypt (e-mail: email@example.com).
Khalid Khalil is with Facebook, London, UK (e-mail: firstname.lastname@example.org).
Ahmed Nabil is with Incorta Company, San Mateo, California, USA (e-mail: email@example.com).
Aly Barakat is with Minly Company, Cairo, Egypt (e-mail: firstname.lastname@example.org).
Cite: Dalia Mohamed Sobhy, Khalid Khalil, Ahmed Nabil, and Aly Barakat, "Unravel: AI-Driven Educational Platform," International Journal of Information and Education Technology vol. 12, no. 11, pp. 1185-1190, 2022.Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).