Assistant Zone – Homeschooling Assistance System based on Natural Language Processing

Kajathees Premendran, S.B.D.D. Bopearachchi, Str Senevirathna, Sithpavan Giridaran, K. Archchana, D. Ganegoda, S. Thelijjagoda
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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.
基于自然语言处理的辅助区-在家上学辅助系统
作为一个发展中国家,大多数人把教育放在首位。在重点建设电子学习平台,提高学生知识和师生互动时,疫情季节可以说是主要障碍,对教育领域的影响很大。考虑到大流行的情况,还考虑到对教师和学生的评价以及面临不同困难的学生的心理水平的担忧,引入了“家庭教育援助制度”(助理区)作为解决方案。助教区有三个独特的功能,对学生和老师都很有价值。该系统分析学生的优势和劣势,评价学生的学习成绩,提出提高自己的学习材料,为学生、教师和家长面临的问题提供解决方案,以学生为基础衡量教师的表现,并为表现不佳的教师推荐学习材料。助手区利用BERT算法等自然语言处理(NLP)和递归神经网络(Recurrent Neural Network)、前向神经网络(Forward Neural Network)、高斯模型(Gaussian Model)等机器学习模型,解决了目标问题,引入了上述三个独特的特征。
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