Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3304
Title: Assistant Zone – Homeschooling Assistance System based on Natural Language Processing
Authors: Premendran, K
Bopearachchi, S.B.D.D.
Senevirathna, S.D.M.
Giridaran, S
Archchana, K
Ganegoda, D
Thelijjagoda, S
Keywords: Assistant Zone
Homeschooling
Assistance System
System based
Natural Language Processing
Issue Date: 9-Dec-2022
Publisher: IEEE
Citation: K. Premendran et al., "Assistant Zone – Homeschooling Assistance System based on Natural Language Processing," 2022 4th International Conference on Advancements in Computing (ICAC), Colombo, Sri Lanka, 2022, pp. 13-17, doi: 10.1109/ICAC57685.2022.10025201.
Series/Report no.: 2022 4th International Conference on Advancements in Computing (ICAC);
Abstract: As a developing country, most people give their highest priority to education. When focusing on building an e-learning platform to improve the knowledge of students and teacher-student interactivity, the pandemic season can be mentioned as the main blocker which highly impacted the education field. Not only by considering the pandemic situation but also by addressing the concerns when it comes to teacher and student evaluation and psychological levels of students who are undergoing different difficulties, the “Home Schooling Assistance System” (Assistant Zone) has been introduced as a solution. The Assistant Zone has been initiated with three unique features which are valuable for both students and teachers. This system analyzes the strengths, weaknesses and evaluates the student performance, suggests study materials to improve themselves, provides solutions to the problems faced by the students, teachers, and parents and measures the performance of teachers based on their students, and recommends learning materials for the low-performing teachers. The Assistant Zone fulfills the targeted problems and introduces the above-mentioned three unique features with the use of Natural Language Processing (NLP) such as the BERT algorithm and Machine Learning models such as the Recurrent Neural Network, Forward Neural Network, and Gaussian Model.
URI: https://rda.sliit.lk/handle/123456789/3304
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 - Dept of Information of Management
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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