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Students Live Behaviour Monitoring in Online Classes Using Artificial Intelligence

EasyChair Preprint no. 12780

5 pagesDate: March 27, 2024


Many universities turned to virtual education

as a solution to the health emergency that prevented

them from utilising their centres for instruction.

impacting students' learning processes, which has made

many of them more used to this new method of learning

and increased the usage of virtual platforms. A lot of

educational institutions now depend heavily on digital

platforms like Zoom, Microsoft Team, Google Meet,

Discord, and Skype. Reporting on the effects of student

learning via the usage of the previously described

videoconferencing tools is the aim of the study. Teachers

and students were surveyed, and the results showed that

66% of them felt no impact on their educational

progress. The majority of them grew acquainted with

the platforms; yet, fewer than 24% of them indicated

that their academic performance had improved. Some

teachers continue to have psychological challenges as a

result of this new teaching approach. In conclusion, both

educators and learners concur that these resources are

very beneficial for online learning.

This project's main goal is to develop an independent

agent that can provide instructors and students with

information. Important academic outcomes like critical

thinking and grades are closely correlated with the

degree of student participation in a subject

Keyphrases: Attention Assessment, deep learning, face recognition, student behavior

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Manam Kowshik and Konakanchi Eswar Rao and Nithin Chowdary Bollu and Vadlamudi Siddhardha},
  title = {Students Live Behaviour Monitoring in Online Classes Using Artificial Intelligence},
  howpublished = {EasyChair Preprint no. 12780},

  year = {EasyChair, 2024}}
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