Students Engagement Detection in Online Learning During Covid-19 Pandemic Using R Programming Language

Informatica economica Pub Date : 2021-09-30 DOI:10.24818/issn14531305/25.3.2021.03

A. Kabir, Suraya Akter, Sriman Mitra

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引用次数: 3

Abstract

Nowadays, Covid-19 is a serious issue, which is outspread all over the world. As, this is a contagious illness, so people maintaining social distance to prevent it. Government of every country announced lockdown to the respective countries to stop its rapid spread. For this reason, most of the sectors especially the education sector is going through a crisis. Students cannot go to their institution because of this pandemic. Therefore, Government of every country decided to start online class in this pandemic situation. It is very much tough to continue study through online rather than intuitional class. Not only students but also the teachers also faced many problems to do the online class properly because this is a new process for both of them. In online class, teachers have to identify that the students are present or not. If the students turn on their webcam, then the teachers can take their attendance easily. In this research, researchers tried to develop a prototype using R programming language and machine learning tools that can detect and recognize students’ face easily that might help teachers to take attendance without any hassle. Researchers took help of Artificial Intelligence as well as used Machine Learning tools to complete this research. People using artificial intelligence because people do mistake but machine cannot do mistake so the in here the error rate is low. Machine learning is also important because it is time consuming, this machine have to trained up so that it is act as human and solve all the problems easily. That is why various types of programming language are needed to train up the machine. In here, Researchers mainly used OpenCV that is a built-in package of R programming language, which is used for real time face detection and so on. Keyword: Face Detection, Face Recognition, R Programming Language, Artificial Intelligence (AI), Machine Learning, OpenCV DOI: 10.24818/issn14531305/25.3.2021.03

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使用R编程语言检测Covid-19大流行期间在线学习的学生参与度

当前，新冠肺炎疫情是一个严重问题，向全球蔓延。由于，这是一种传染性疾病，所以人们保持社会距离来预防它。各国政府宣布对各自国家实施封锁，以阻止其迅速传播。因此，大部分部门特别是教育部门正在经历危机。由于这次大流行，学生们不能去他们的学校。因此，各国政府决定在这种大流行的情况下启动在线课程。通过网络而不是直观的课堂来继续学习是非常困难的。不仅是学生，而且教师也面临着许多问题，因为这对他们来说都是一个新的过程。在网络课堂上，老师必须确定学生是否在场。如果学生打开他们的网络摄像头，那么老师可以很容易地记录他们的出勤情况。在这项研究中，研究人员试图使用R编程语言和机器学习工具开发一个原型，它可以很容易地检测和识别学生的脸，这可能会帮助教师轻松出勤。研究人员借助人工智能以及机器学习工具来完成这项研究。人们使用人工智能，因为人会犯错，但机器不会犯错，所以这里的错误率很低。机器学习也很重要，因为它很耗时，机器必须经过训练，才能像人类一样轻松解决所有问题。这就是为什么需要不同类型的编程语言来训练机器。在这里，研究人员主要使用了OpenCV，它是R编程语言的内置包，用于实时人脸检测等。关键词:人脸检测，人脸识别，R编程语言，人工智能，机器学习，OpenCV DOI: 10.24818/issn14531305/25.3.2021.03

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来源期刊

Informatica economica

自引率

0.00%

发文量

审稿时长

8 weeks