AI Proctor: AI-Based Platform for Remote Learning


Abstract views: 88 / PDF downloads: 56

Authors

  • Jack Mueller Austin Highschool, Austin, USA

DOI:

https://doi.org/10.31039/ljss.2023.6.112

Keywords:

AI, Synchronous, Asynchronous, On-site Proctoring

Abstract

Progressions in technology give headway to remote exams as a good alternative to on-site proctoring. Due to the COVID-19 pandemic, educators and institutions have been forced to rely on remote synchronous and asynchronous operations. The rapid change left weaknesses in the old systems to surface. Furthermore, it is questionable that they are equal in function to on-site proctoring. Grounded on thorough research, I determined the operation requirements for AI Proctor, a solution that solves many of the concerns with remote proctoring.

 

References

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Classroomscreen https://classroomscreen.com

ActivTrak https://www.googleadservices.com

Speed Exam https://www.googleadservices.com

EXAM Builder https://exambuilder.com/exam-software-features/scheduling

Chegg https://www.chegg.com

Apple https://support.apple.com/en-us/HT208108

Inflectra https://www.inflectra.com

GoGuardian https://www.googleadservices.com

Veriff https://www.veriff.com

CMU Sphinx https://cmusphinx.github.io

LinkSquares https://linksquares.com

Zyte https://www.zyte.com

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Published

2023-09-18

How to Cite

Jack Mueller. (2023). AI Proctor: AI-Based Platform for Remote Learning. London Journal of Social Sciences, (6), 130–135. https://doi.org/10.31039/ljss.2023.6.112

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Section

Articles