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DC Field | Value | Language |
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dc.contributor.author | Wijayawardena, G. C. S | - |
dc.contributor.author | Subasinghe, S. G. T. S | - |
dc.contributor.author | Bismi, K. H. P | - |
dc.contributor.author | Gamage, A | - |
dc.date.accessioned | 2022-09-08T04:11:39Z | - |
dc.date.available | 2022-09-08T04:11:39Z | - |
dc.date.issued | 2022-07-18 | - |
dc.identifier.citation | W. G. C. S, S. S. G. T. S, B. K. H. P and A. Gamage, "AI and Machine Learning Based E – Learning System For Secondary Education," 2022 IEEE 7th International conference for Convergence in Technology (I2CT), 2022, pp. 1-6, doi: 10.1109/I2CT54291.2022.9824643. | en_US |
dc.identifier.issn | 978-1-6654-2168-3 | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/2972 | - |
dc.description.abstract | One of the key functions directly shifted to online platforms under COVID-19 is education. The paper is about an E-learning system for secondary education in Sri Lanka. Learners and teachers can access information, resources, and tools through an E-Learning system, which is a Learning Management System that integrates a number of online activities. The main functions provided through the proposed system are chatbot, final grade prediction and weak area prediction of the students. Chatbots are becoming increasingly popular in a wide range of applications, especially in those that provide intelligence support to the user, according to recent research. So, in order to speed up the aid process, these systems are often integrated with Chatbots, which can quickly and accurately read the user's questions. This paper describes the implementation of a Chatbot prototype in the educational domain: a system for providing support to students. In the beginning, the goal was to design a special architecture and communication model that would help students get the proper answers. The final grade prediction component plays major role in the system. Because when the students are graded by their marks, they can review which areas that they have to improve and work on them. This is helpful for students as well as teachers. Weak area prediction also plays a significant role, because it can help to find out the weak areas of each subject and generate Individual Student Progress Plans to predict the students’ weak subjects and the subject areas of the students. This motivates students to get higher marks easily because this part is mainly focused on weak areas of students and improve those weak areas by providing several learning activities. These are the major parts of this system to have a good E-learning system for both students and Teachers. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.relation.ispartofseries | 2022 IEEE 7th International conference for Convergence in Technology (I2CT); | - |
dc.subject | Machine Learning | en_US |
dc.subject | E – Learning System | en_US |
dc.subject | Secondary Education | en_US |
dc.subject | Based E – Learning | en_US |
dc.title | AI and Machine Learning Based E - Learning System For Secondary Education | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/I2CT54291.2022.9824643 | en_US |
Appears in Collections: | Department of Information Technology Research Papers - IEEE Research Papers - SLIIT Staff Publications Research Publications -Dept of Information Technology |
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File | Description | Size | Format | |
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AI_and_Machine_Learning_Based_E__Learning_System_For_Secondary_Education.pdf Until 2050-12-31 | 1.16 MB | Adobe PDF | View/Open Request a copy |
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