Author(s)

Yuchen Zhang

Corresponding Author

Yuchen Zhang

ABSTRACT

In the pandemic era, more and more schools or institutions have begun to choose or be forced to conduct education activities online. In China, the current mainstream online teaching model is that teachers are talking endlessly, while most students passively listen. Some educators require cameras to be turned on, while others do not. This makes many people question the effectiveness and quality of online teaching compared to offline teaching since teachers can no longer monitor students' performance in real time. In fact, low-efficiency in online teaching is also a problem that educational institutions are trying to solve. The majority of scholars believe that the relatively low quality of online teaching may be caused by the limitations of current softwares and hardwares monitoring ability. Some researcher in the area Human-Computer Interaction (HCI) dived deep into the problem and tried to develop solutions and supporting systems to facilitate quality online education. In this paper, I conducted a systematic literature review of HCI research applied to detection of learners’ attention and engagement on online education settings. Based on the literatures, I discuss the current solutions and future directions from a macro perspective.

KEYWORDS

Human-computer interaction, Online teaching, Systematic literature review, Eye tracking, Facial recognition, Neural network