SLIIT Conference and Symposium Proceedings

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Systematic Review: The Role of Data Analytics in Enhancing Academic Performance Classroom interaction, Learning Analytics in Higher Education
(ICSDB 2024 and SLIIT Business School, 2024-12-10) Sithumini, J.H.C.; Sanjuka, A.N.E.; Ranawaka, P. S.; Hasaranga, H.G. D.; Samarakkody, T.; Pathirana, G
The field of data analytics has seen substantial growth, particularly within the education sector. With the recent expansion of e-learning due to the COVID-19 pandemic, the ability to make data-driven decisions in education has become more important than ever. This review synthesizes existing research on the role of data analytics in enhancing academic performance and decisionmaking in higher education. The key objectives are to examine the influence of data analytics on student performance, explore learning analytics’ role in institutional decision-making, and assess the effect of data analytics on e-learning systems, particularly during the COVID-19 pandemic.
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E-Learning Assistive System for Deaf and Mute Students
(IEEE, 2022-12-09) Ranasinghe, P; Akash, K; Nanayakkara, L; Perera, H; Chandrasiri, S; Kumari, S
E-learning has become a popular digital platform among both students and teachers. When using an e-learning system, deaf-mute students can get significant benefits. It allows students to better grasp their studies by providing additional details. The major problem that the deaf and mute community encounters in the e-learning environment is that they are no longer attempting to enroll in normal institutions, which do not provide many facilities for them due to a lack of resources, a lack of learning facilities, and some social disturbances. To achieve that problem this system will translate the lecturer’s voice into text, map words with pre-created sign language animations, generate subtitles for lecture videos, clearly identify the face position of the lecturer, detect difficult words, track the hand gestures, and practice sign language so that it will increase learning resources, facilities, usability and help teachers to execute their teaching process through this platform. Therefore, normal institutions can use this system as their learning management system. It will approach deaf and mute students to enroll in normal institutions and do their studies as typical students.
Embargo
E-Learn Detector: Smart Behaviour MonitoringSystem to Analyze Student Behaviours DuringOnline Educational Activities
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Bamunuge, H.K.T.; Perera, H.M.; Kumarage, S.; Savindri, P.A.P.; Kasthurirathna, D.; Kugathasan, A.
With the rise of online education more attention is being paid to the deficiencies in online learning platforms. Online Learning environments aim to deliver efficacious instructions, but rarely take providing a conventional classroom experience to the students into consideration. Efficient detection of students’ learning situations can provide information to teachers to help them identify students having trouble in real-time. This idea has been exploited several times for Intelligent Tutoring Systems, but not yet in other types of learning environments that are less structured. “E-Learn Detector is a web application solution to these existing issues in online learning which consists of unique features such as verifying the user during logging procedure and throughout an examination, detecting suspicious behaviors and presence of multiple users during online examinations and detecting low engagement levels of students during online lectures. “E-Learn Detector” is developed with the aim to provide guidance to students to improve their academic performance and behavior during classroom activities and to induce the best out of the educational activities.

SLIIT Conference and Symposium Proceedings

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