dc.contributor.advisor | Rhaman, Dr. Md. Khalilur | |
dc.contributor.author | Siddique, Saadman Omar | |
dc.contributor.author | Alam, M. Shafiul | |
dc.contributor.author | Alam, Mahmud | |
dc.contributor.author | Hasan, Nabil | |
dc.contributor.author | Tajwar, M. M. Hasan | |
dc.date.accessioned | 2024-01-10T03:37:23Z | |
dc.date.available | 2024-01-10T03:37:23Z | |
dc.date.copyright | 2023 | |
dc.date.issued | 2023-01 | |
dc.identifier.other | ID: 19301180 | |
dc.identifier.other | ID: 19301194 | |
dc.identifier.other | ID: 19301214 | |
dc.identifier.other | ID: 19301222 | |
dc.identifier.other | ID: 19301240 | |
dc.identifier.uri | http://hdl.handle.net/10361/22093 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 41-42). | |
dc.description.abstract | The COVID-19 pandemic has brought about a significant change in the way educa tion is delivered worldwide. Restrictions have forced schools, colleges, and universi ties to hold classes online using video communication services. While this method of
teaching has its advantages, one major challenge is determining student engagement
during virtual sessions. In traditional classrooms, it is easier to observe student’s
interest and engagement through body language and movements. However, this is
not the case in an online setting, where monitoring engagement requires more re sources. To address this issue, we have undertaken research to develop a system
called ”Online Engage-Measurement” that automates the process of monitoring en gagement by measuring attention and detecting screen sharing. This system will be
faster, more efficient, and accessible to educators everywhere. It uses screen sharing
detection, face recognition, head position, and eye gaze estimation, as well as an
algorithm called ”AttentionEstimator” to determine engagement levels. The system
detects the attentiveness of both students and teachers and generates a report for
analysis. Besides, our research is unique as this field has not yet been implemented,
and our system is the result of our research contributions, which will help us to
be a part of the Fourth Industrial Revolution. This initiative has the potential to
improve the future of education and solve many problems, such as the development
of proctor-less examination system. Utilizing such attention measuring system in
online education can provide valuable insights for educators to adapt and refine
their teaching methods to align with the needs of their students. It allows for the
assessment of the effectiveness of instruction and detection of areas for improvement
in student performance, thus providing valuable information to enhance the educa tional experience for students. Thus, the system we have built has the potential to
improve student learning experiences and boost tutoring session efficiency. | en_US |
dc.description.statementofresponsibility | Saadman Omar Siddique | |
dc.description.statementofresponsibility | M. Shafiul Alam | |
dc.description.statementofresponsibility | Mahmud Alam | |
dc.description.statementofresponsibility | Nabil Hasan | |
dc.description.statementofresponsibility | M. M. Hasan Tajwar | |
dc.format.extent | 42 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | Online engage-measurement | en_US |
dc.subject | Screen sharing detection | en_US |
dc.subject | Face recognition | en_US |
dc.subject | Head pos | en_US |
dc.subject | Eye gaze estimation | en_US |
dc.subject | AttentionEstimator | en_US |
dc.subject | System | en_US |
dc.subject | Proctor-less | en_US |
dc.subject | Attentiveness | en_US |
dc.subject | Unique | en_US |
dc.subject.lcsh | Pattern recognition. | |
dc.subject.lcsh | Internet in education. | |
dc.title | Online engage-measurement in tutoring session | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B.Sc. in Computer Science | |