Premadasa, H. K. Salinda (2023) Securely Compressed Extensive Text Messages: The Interactive Mobile Learning for Distance Education in the COVID – 19 Pandemic. Asian Journal of Research in Computer Science, 16 (3). pp. 181-196. ISSN 2581-8260
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Abstract
The COVID-19 pandemic has made a massive impact on the higher education system in the present globe. Universities had to close abruptly due to keeping up social distancing to prevent the spread of the Coronavirus in the world community. As a result, the existing face-to-face education style is rapidly shifting to distance education environment through the mobile technology. Here, an extensive text messages, one of the most popular applications, make a significant contribution on higher education. However, in this scenario, the single text message is not sufficient in various academic activities such as sending short lecture summaries, feedbacks, assessment timetables, useful web links, detailed news, notices, and examination results to achieve educational prospects to obtain better results in distance education. Moreover, standard SMSs do not provide message confidentiality when sending sensitive data, such as examination results. Here, we propose a novel technique for extensive text message compression to create an interactive mobile learning environment for distance education in the present pandemic situation. This proposed secure mechanism provides message confidentiality, authenticity, and integrity with cryptographic protection. Initially, the teacher inserts academic-related information as an extensive text message. The extensive text message is then compressed and secured with the initialization vector and the secret key in the proposed mechanism. Finally, the securely compressed single text message transmits to students who will decompress it into its original form on their mobile devices. The result shows that students' extrinsic motivation in their distance learning environment effectively and efficiently in the COVID-19 pandemic.
Item Type: | Article |
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Subjects: | EP Archives > Computer Science |
Depositing User: | Managing Editor |
Date Deposited: | 22 Sep 2023 04:03 |
Last Modified: | 22 Sep 2023 04:03 |
URI: | http://research.send4journal.com/id/eprint/2648 |