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

Author

Listed:
  • Ahmed Imran KABIR
  • Suraya AKTER
  • Sriman MITRA

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.

Suggested Citation

  • Ahmed Imran KABIR & Suraya AKTER & Sriman MITRA, 2021. "Students Engagement Detection in Online Learning During Covid-19 Pandemic Using R Programming Language," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 25(3), pages 26-37.
    • Handle: RePEc:aes:infoec:v:25:y:2021:i:3:p:26-37
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    References listed on IDEAS

    as
    1. Ahmed Imran KABIR & Ridoan KARIM & Shah NEWAZ & Muhammad Istiaque HOSSAIN, 2018. "The Power of Social Media Analytics: Text Analytics Based on Sentiment Analysis and Word Clouds on R," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 22(1), pages 25-38.
    2. Sylvia Tippmann, 2015. "Programming tools: Adventures with R," Nature, Nature, vol. 517(7532), pages 109-110, January.
    3. Ahmed Imran KABIR & Koushik AHMED & Ridoan KARIM, 2020. "Word Cloud and Sentiment Analysis of Amazon Earphones Reviews with R Programming Language," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 24(4), pages 55-71.
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