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During online learning, machine learning algorithm can identify when student engagement falls, nudging students and helping teachers to intervene

11.10.21 | PLOS

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During online learning, machine learning algorithm can identify when student engagement falls, nudging students and helping teachers to intervene

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Article Title: A new ML-based approach to enhance student engagement in online environment

Author Countries: Saudi Arabia

Funding: The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number PNU-DRI-RI-20-002.

Article URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0258788

PLOS ONE

10.1371/journal.pone.0258788

A new ML-based approach to enhance student engagement in online environment

10-Nov-2021

The authors declare that they have no conflicts of interest to report regarding the present study.

Keywords

Article Information

Contact Information

Hanna Abdallah
PLOS
onepress@plos.org

How to Cite This Article

APA:
PLOS. (2021, November 10). During online learning, machine learning algorithm can identify when student engagement falls, nudging students and helping teachers to intervene. Brightsurf News. https://www.brightsurf.com/news/LRDD9GR8/during-online-learning-machine-learning-algorithm-can-identify-when-student-engagement-falls-nudging-students-and-helping-teachers-to-intervene.html
MLA:
"During online learning, machine learning algorithm can identify when student engagement falls, nudging students and helping teachers to intervene." Brightsurf News, Nov. 10 2021, https://www.brightsurf.com/news/LRDD9GR8/during-online-learning-machine-learning-algorithm-can-identify-when-student-engagement-falls-nudging-students-and-helping-teachers-to-intervene.html.