Analyzing students’ concentration in online courses through Webcam
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
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Brac University
2024
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| Linkit: | http://hdl.handle.net/10361/22892 |
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10361-228922024-05-20T21:00:31Z Analyzing students’ concentration in online courses through Webcam Asif, Md. Hossain, Md. Imtiaj Sharkar, Fouzia Islam, Md. Mohaimenul Alam, Md. Golam Rabiul Reza, Md Tanzim Department of Computer Science and Engineering, Brac University CNN VGG16 Concentration levels MobileNetV2 ResNet50 InceptionV3 Internet in education Distance education Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 54-55). Online learning is growing in popularity these days. As a result, students typically contribute millions of course-related responses to discussion forums and exchange some learning experiences. This study focuses on online courses offered through MOOC platforms and identifies the variables that affect students’ ability to stay focused. We suggest a unique method to address this issue by evaluating students’ levels of concentration using the CNN architecture, MobileNetV2, VGG16, ResNet50, and InceptionV3 models. Our goal is to determine whether the issue is with students’ concentration, the course material, or both. Measurement of concentration levels, evaluation of video data, comparison of model performances, and provision of class-based concentration levels (attentive, inattentive, and sleepy) are the goals of our research. The dataset underwent pre-processing, which included resizing for analysis, frame extraction, and annotation for classification. Our research offers educators insightful information that will help them to increase the overall efficacy of online learning. Furthermore, the study advances the area by offering a methodical technique for assessing and evaluating students’ concentration on online courses. Md. Asif Md. Imtiaj Hossain Fouzia Sharkar Md. Mohaimenul Islam B.Sc in Computer Science 2024-05-20T09:19:24Z 2024-05-20T09:19:24Z ©2024 2024-01 Thesis ID: 19201096 ID: 19201031 ID: 19201094 ID: 19201095 http://hdl.handle.net/10361/22892 en 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. 61 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
CNN VGG16 Concentration levels MobileNetV2 ResNet50 InceptionV3 Internet in education Distance education Neural networks (Computer science) |
| spellingShingle |
CNN VGG16 Concentration levels MobileNetV2 ResNet50 InceptionV3 Internet in education Distance education Neural networks (Computer science) Asif, Md. Hossain, Md. Imtiaj Sharkar, Fouzia Islam, Md. Mohaimenul Analyzing students’ concentration in online courses through Webcam |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. |
| author2 |
Alam, Md. Golam Rabiul |
| author_facet |
Alam, Md. Golam Rabiul Asif, Md. Hossain, Md. Imtiaj Sharkar, Fouzia Islam, Md. Mohaimenul |
| format |
Thesis |
| author |
Asif, Md. Hossain, Md. Imtiaj Sharkar, Fouzia Islam, Md. Mohaimenul |
| author_sort |
Asif, Md. |
| title |
Analyzing students’ concentration in online courses through Webcam |
| title_short |
Analyzing students’ concentration in online courses through Webcam |
| title_full |
Analyzing students’ concentration in online courses through Webcam |
| title_fullStr |
Analyzing students’ concentration in online courses through Webcam |
| title_full_unstemmed |
Analyzing students’ concentration in online courses through Webcam |
| title_sort |
analyzing students’ concentration in online courses through webcam |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/22892 |
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| _version_ |
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