Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/2954
Title: | Remotify: The Emergency Remote Learning Solution using Learning Analytics |
Authors: | Amarasinghe, S. N. Thalakumbura, T. M. D. D Wijewardena, M. D. N. K. Perera, D. H. Manathunga, K Senaweera, O |
Keywords: | Remotify Emergency Remote Learning Solution Learning Analytics |
Issue Date: | 18-Jul-2022 |
Publisher: | IEEE |
Citation: | S. N. Amarasinghe, T. M. D. D. Thalakumbura, M. D. N. K. Wijewardena, D. H. Perera, K. Manathunga and O. Senaweera, "Remotify: The Emergency Remote Learning Solution using Learning Analytics," 2022 IEEE 7th International conference for Convergence in Technology (I2CT), 2022, pp. 1-8, doi: 10.1109/I2CT54291.2022.9824707. |
Series/Report no.: | 2022 IEEE 7th International conference for Convergence in Technology (I2CT); |
Abstract: | Current pandemic situation has manipulated people to adapt to a new normal forcefully and due to the same reason education system is also evolving but the actual question is how productive the new methodologies utilized are. E-learning is not a novel concept but is becoming a necessity and the proposed platform could be identified as a direct response to the current emergency. This can also be known as an "ERT" situation; a shift of instructional delivery to an alternate delivery method in response to a crisis situation. The main intention in these situations is not to recreate a robust educational system but to provide access to institutions in a manner that is easy to set up and is dependable during an emergency while outperforming both E-learning & traditional classroom methods. To provide a solution to overcome barriers faced in a pandemic situation in a virtual classroom, the implemented system is encapsulated with a dashboard centralizing facts gathered from audio & video analyzing components which are analyzed against student performance utilizing personalized assessing techniques to deliver learning analytics. |
URI: | http://rda.sliit.lk/handle/123456789/2954 |
ISBN: | 978-1-6654-2168-3 |
Appears in Collections: | Department of Computer Science and Software Engineering Research Papers - Dept of Computer Science and Software Engineering Research Papers - IEEE Research Papers - SLIIT Staff Publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Remotify_The_Emergency_Remote_Learning_Solution_using_Learning_Analytics.pdf Until 2050-12-31 | 1.47 MB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.