Abstract: Big Data technologies and their analytical methods can help improve the quality of education. They can be used to process and analyze classroom video streams to predict student attention, this would greatly improve the learning-teaching experience. With the increasing number of students and the expansion of educational institutions, processing and analyzing video streams in real-time become a complicated issue. In this paper, we have reviewed the existing systems of student attention detection, open-source real-time data stream processing technologies, and the two major data stream processing architectures. We also proposed a new Big Data architecture for real-time student attention detection.

Tarik Hachad, Abdelalim Sadiq and Fadoua Ghanimi, “A New Big Data Architecture for Real-Time Student Attention Detection and Analysis” International Journal of Advanced Computer Science and Applications(IJACSA), 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110831

@article{Hachad2020,
title = {A New Big Data Architecture for Real-Time Student Attention Detection and Analysis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110831},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110831},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {8},
author = {Tarik Hachad and Abdelalim Sadiq and Fadoua Ghanimi}
}