Research Publications Authored by SLIIT Staff
Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4195
This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Embargo The Impact Of Social Media On The Academic Development Of School Students(Institute of Electrical and Electronics Engineers, 2022-09-18) Perera, U,D,H,L; Harshanath, S.M.BWhile social media has reached the peak of its popularity, the addiction to social media become a major issue. With the present pandemic the authorities are forced to close the schools and to shift to virtual classrooms. The students must therefore use a connected devise to participate to the classes which has contributed to the increased addiction to social media among the youth. Inappropriate or excessive usage social media may affect the studies as well as mental and physical health of the user. Spread of fake news through social media has also been a big problem. Mainly, due to its convenience of usage, social media, has become a daily necessity, especially among the youth. So, the primary goal of this study project is to determine the impact of social media on school students' academic performance and to suggest a separate social media platform which will meet their needs.Publication Embargo Student and Lecturer Performance Enhancement System using Artificial Intelligence(IEEE, 2020-12-03) Seneviratne, I. K; Perera, B. A. S. D; Fernando, R. S. D; Siriwardana, L. K. B; Rajapaksha, S, KThe proposed research work develops a system to enhance the performance of university students and lecturers by providing an excellent statistical insight. Already existing research works have attempted to solve independent classroom challenges that are related to measuring the student attention and marking student attendance but the existing research works have not combined theimportant aspects into one system. Hence, the proposed research wor has been carried out on various main aspects such as attendance register, monitoring student behavior as well as lecturer performance and lecture summarization. The system will incorporate tools and technologies in the different domains of artificial intelligence, machine learning, and natural language processing. After implementing and testing the proposed method it has been concluded that the student activity recognition process has been performed much better than the other emotion and gaze components by providing 94.5% results. The proposed system can determine the lecturer's physical activities and the quality of the lecture content with a reasonable accuracy. The summarized lecture has showed 70% similarity to actual lecture content and student attendance by using Face Recognition was marked with 83% accuracy. This research concludes that the automation of major classroom activities will impact the students and lecturers positively. Also, this system yields valuable results and increases the productivity of higher education institutions in the future.