A New Big Data Architecture for Real-Time Student Attention Detection and Analysis

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.

Events Sourcing and Command Query Responsibility Segregation Based Fast Data Architecture

“…In their architecture, the data source is replaced by the new data to be used for predictions thanks to an already trained machine learning model. Their proposal was used to detect the level of attention of students be it in a batch context as well as in a real time application [3].…”

“…This architecture is still widely used in Big Data industrialization activities in companies and organizations. However, real-time application requirements, particularly with the advent of the Internet of Things, have led to the proposal of smack architectures as the first viable industrial approach [3]. Thus, the lambda and smack architectures are intended to be references in the development of applications exploiting Big Data in particular, data integration applications.…”

The Big Data and Machine Learning in Managing Global Health Crises : The Case of the Covid-19 Pandemic

“…Instead, various technologies, including Machine Learning techniques, have been employed for many years to analyze data. Early data analysis primarily relied on statistical methods to gain insights into the situation at hand, such as understanding public opinions on social media platforms [26]. Alongside traditional data analysis, problem-specific data mining methods were utilized to extract meaningful patterns and knowledge from the collected data.…”

Towards a new method of estimating the student attention based on the eye gaze

“…Indeed, an eye points to the object to be analyzed during a recognition or learning operation, pointing to an interlocutor expresses an interest in the discussion. Based on this reality, and with the objective of improving the teaching and learning experience, we have chosen to analyze an aspect of the human eye which is the direction of gaze to extract information on the attention of students in the class during the course [1]. The operation must be carried out under normal course conditions, so the used devices must to be not distractive or invasive for the students [2].…”