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Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Dmitry Temnov
Video-Based Prediction of Student Engagement in Online Course Using Deep Learning Technologies
Business Informatics
(Bachelor’s programme)
2019
The main goal of this work is to develop a prototype of the application that is able to measure the engagement level of the subject on video using deep neural networks.

The purpose of the research is to develop a high-performance neural network and an application based on it to provide the engagement estimation service for online educational platforms such as Coursera or traditional universities. Such a product can help to increase the amount of time spent watching the recommended content and to assist the course’s authors since they would indeed benefit from the feedback on their endeavours to create better instructional material.

During the research process, two high-quality datasets of video materials with the subjects watching educational content will be studied on the topic of engagement estimation.

The general task from a mathematical perspective is to create a regression model using the Mean Squared Error(MSE) as a metric. It is expected to achieve the targeted results of MSE=0.10.

Neural Networks Architectures, obtained from experiments, have to to provide sustainable estimations even on videos recorded in poor conditions by amateurs, thus proving the ability to generalize the content and extract the most important features from every frame.

The application should have a user-friendly interface providing the ability to upload a recorded video and then display the analysed frames where subjects lose their interest in educational material.

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