Automatic detection for students behaviors in a group presentation
Conference paper
Fekry, A., Dafoulas, G. and Ismail, M. 2019. Automatic detection for students behaviors in a group presentation. ICCES 2019. Cairo, Egypt 17 Dec 2019 Institute of Electrical and Electronics Engineers. pp. 11-15 https://doi.org/10.1109/ICCES48960.2019.9068128
Type | Conference paper |
---|---|
Title | Automatic detection for students behaviors in a group presentation |
Authors | Fekry, A., Dafoulas, G. and Ismail, M. |
Abstract | This paper suggests a model for automatic detection of student behavior to be used in student presentations. The proposed approach is based on the combined use of computer vision libraries and machine learning algorithms to help and support in student assessment using video content. This paper is a part of a research study focusing on investigating and analysing, human behaviours and finding relations between human behaviours and their personal modalities using pattern recognition techniques. For the purpose of this study a group of specific behaviours expressed by students during group presentations in higher education level, are selected. The study proceeds with the detection of the occurrences of those behaviours and comparative analysis of the model's suggested behavioural patterns against those observed through the manual analysis of observations. Both approaches are based on the same set of video files. |
Research Group | Research Group on Development of Intelligent Environments |
Conference | ICCES 2019 |
Page range | 11-15 |
ISBN | |
Electronic | 9781728152608 |
Paperback | 9781728152615 |
Publisher | Institute of Electrical and Electronics Engineers |
Publication dates | |
17 Dec 2019 | |
Online | 16 Apr 2020 |
Publication process dates | |
Deposited | 09 Apr 2021 |
Accepted | 15 Oct 2019 |
Output status | Published |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ICCES48960.2019.9068128 |
Language | English |
Book title | 14th International Conference on Computer Engineering and Systems |
https://repository.mdx.ac.uk/item/894v5
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