Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3329
Title: E-tutor: Comprehensive Student Productivity Management System for Education
Authors: Silva, K
Induwara, R
Wimukthi, M
Poornika, S
Samaratunge Arachchillage, U.S.S
Jayalath, T
Keywords: E-tutor
Comprehensive Student
Student Productivity
Management System
Education
Issue Date: 9-Dec-2022
Publisher: IEEE
Citation: K. Silva, R. Induwara, M. Wimukthi, S. Poornika, U. S. S. S. Arachchillage and T. Jayalath, "E-tutor: Comprehensive Student Productivity Management System for Education," 2022 4th International Conference on Advancements in Computing (ICAC), Colombo, Sri Lanka, 2022, pp. 108-113, doi: 10.1109/ICAC57685.2022.10025237.
Series/Report no.: 2022 4th International Conference on Advancements in Computing (ICAC);
Abstract: With the advancement of technology, e-learning has emerged as predominant in the education sector. As students, parents, and educators acknowledged, adopting e-learning can offer several benefits over traditional learning techniques. Since more individuals are becoming acclimated to online learning platforms, these online platforms can provide a simple, instructive, and efficient mode of delivery. This novel approach could be improved with the aid of Artificial Intelligence (AI) to comprehend consumers more thoroughly and provide valuable and better-suited services. Most sectors in education, including universities, swiftly adapted to new educational methodologies because of their flexibility and productivity. Nevertheless, there are some downsides that young demography experiences, such as less instructiveness, distraction due to the absence of teachers, and poor IT literacy. Consequently, these drawbacks would recede the capability of students to assimilate content during the lecture. Therefore, the main objective of this research is to implement an E-learning platform with AI learning analytics to enhance students’ performance regularly while reducing the significant drawbacks of the E-learning platforms. This research consists of students’ focus detection, essay-based answer evaluation, note summarization, mind map generation, and personalized guidance facilities.
URI: https://rda.sliit.lk/handle/123456789/3329
ISBN: 979-8-3503-9809-0
Appears in Collections:4th International Conference on Advancements in Computing (ICAC) | 2022
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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