The Role of Digital Twin Technology in Engagement Detection of Learners in Online Learning Platforms

Abstract

During and after the pandemic, online learning has been a part of various educational activities. Online educators must precisely detect the learner's engagement to provide pedagogical support. “Student engagement” refers to how much students participate intellectually and emotionally in their classwork and must be evaluated. Defining a straightforward procedure for assessing and comprehending patterns in engagement measurement can improve the figures significantly. Digital twin technology has become the centre of attention in many industries, such as manufacturing, academia, etc. This chapter presents a comprehensive analysis of all the previous approaches to quantify the degree of user involvement and the role of digital twin technology in online learner engagement. More concrete methods, such as multimodal methods, have been combined with abstract methods, such as simple face expression identification on the real-time data set. It also presents how the digital twin models are utilized to accelerate models' efficiency in various sectors of artificial intelligence applications.