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Analysis of student sentiment during video class with multi-layer deep learning approach

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 4 (2022)

DOI
10.11591/ijece.v12i4.pp3981-3993
ISSN
2722-2578, 2088-8708
Published
2022-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The modern education system is an essential part of the rise of technology. The E-learning education system is not just an experimental system; it is a vital learning system for the whole world over the last few months. In our research, we have developed our learning method in a more effective and modern way for students and teachers. For significant implementation, we are implementing convolutions neural networks and advanced data classifiers. The expression and mood analysis of a student during the onlineclass is the main focus of our study. For output measure, we divide the final output result as attentive, inattentive, understand, and neutral. Showing the output in real-time online class and for sensory analysis, we have used support vector machine (SVM) and OpenCV. The level of 5*4 neural network is created for this work. An advanced learning medium is proposed through our study. Teachers can monitor the live class and different feelings of a student during the class period through this system.

Collaboration network of the authors

22 authors · 93 co-authorship links · 14 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Daffodil International University
  • University of Notre Dame
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Fernaz Narin NurUniversity of Notre Dame6
Masuma ParvinDaffodil International University5
Mohd. SaifuzzamanDaffodil International University4
Susanta Chandra DebnathDaffodil International University4
Refath Ara HossainDaffodil International University3
Md. Shahriar ShakilDaffodil International University2
Mahmudul HassanDaffodil International University2
Israt JahanDaffodil International University1
Shihab UddinDaffodil International University1
Lamisha Haque PoushyDaffodil International University1
Salauddin Ahmed BhuiyanDaffodil International University1
Jarin NooderDaffodil International University1
Ashrarfi MahbubaDaffodil International University1
Mohammad Monirul IslamDaffodil International University1
Asma MariamDaffodil International University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Analysis of student sentiment during video class with multi-layer deep learning approach</dc:title><dc:creator>Salehin, Imrus</dc:creator><dc:creator>Moon, Nazmun Nessa</dc:creator><dc:creator>Talha, Iftakhar Mohammad</dc:creator><dc:creator>Hasan, Md. Mehedi</dc:creator><dc:creator>Hasan, Farnaz Narin Nur</dc:creator><dc:creator>Hakim, Md. Azizul</dc:creator><dc:creator>Al Haque, A S M Farhan</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;The modern education system is an essential part of the rise of technology. The E-learning education system is not just an experimental system; it is a vital learning system for the whole world over the last few months. In our research, we have developed our learning method in a more effective and modern way for students and teachers. For significant implementation, we are implementing convolutions neural networks and advanced data classifiers. The expression and mood analysis of a student during the onlineclass is the main focus of our study. For output measure, we divide the final output result as attentive, inattentive, understand, and neutral. Showing the output in real-time online class and for sensory analysis, we have used support vector machine (SVM) and OpenCV. The level of 5*4 neural network is created for this work. An advanced learning medium is proposed through our study. Teachers can monitor the live class and different feelings of a student during the class period through this system.&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2022-08-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v12i4.pp3981-3993</dc:identifier><dc:identifier>10.11591/ijece.v12i4.pp3981-3993</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 12 No 4 (2022); 3981</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/26434/15803</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>