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

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