Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/961
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dc.contributor.authorSilva, P.H.D.D.-
dc.contributor.authorSudasinghe, S.A.V.D.-
dc.contributor.authorHansika, P.D.U.-
dc.contributor.authorGamage, M.P.-
dc.contributor.authorGamage, M.P.A.W.-
dc.date.accessioned2022-02-07T06:32:56Z-
dc.date.available2022-02-07T06:32:56Z-
dc.date.issued2021-12-09-
dc.identifier.issn978-1-6654-0862-2/21-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/961-
dc.description.abstractE-learning is a form of providing education by using electronic devices. Lack of proper mechanisms for encouraging and assisting students are key issues faced by many students in an e-learning environment. The ‘Vidu Mithuru’ is a question-based e-learning application which has been developed as a solution to overcome these problems. This mobile application will auto generate and categorize the questions, evaluate the answers and track the performance while providing motivational quotes by detecting the emotions of the student. This mobile application is based on Neural Networks, Natural Language Processing and Machine Learning concepts. In order to developing this application, the information provided by the primary education professionals was used to comply with the standards. The core objective of the proposed solution is to track the performance level and assist the students to improve in their studies while keeping them motivated. The trained Machine Learning models have achieved the accuracy of 75%, 78%, 99% and 86% for question categorization model, speech emotion detection model, facial emotion detection model and model to evaluate answers as respectively. We have received favorable responses as the results after testing the developed ‘Vidu Mithuru’ mobile applicationen_US
dc.description.sponsorshipCo-Sponsor:Institute of Electrical and Electronic Engineers (IEEE) Academic sponsor:SLIIT UNI Gold Sponsor :London Stock Exchange Group (LSEG)en_US
dc.language.isoenen_US
dc.publisher2021 3rd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.subjectemotion detectionen_US
dc.subjectgenerate questionsen_US
dc.subjecttrack performanceen_US
dc.subjectdeep learningen_US
dc.subjectmachine learningen_US
dc.titleAI Base E-Learning Solution to Motivate and Assist Primary School Studentsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC54203.2021.9671209en_US
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Department of Information Technology-Scopes
Research Papers - IEEE
Research Publications -Dept of Information Technology

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