The Attention of Students in Online Education

Abstract

The level of attention of students who receive classes through videoconferencing platforms is troubling. Different throughout an entire lecture, the instructor can perceive the participants' behavior, while in an online class, it is difficult to determine if they are attentive to the instructions given. An innovative method that helps solve this problem is the use of computer vision algorithms, with methods such as face detection, facial landmarks, face recognition, and head pose detection based on deep learning networks. In this paper, a neural network was trained using facial landmarks to estimate head position and thus attention levels. The model was applied in five classes using different videoconferencing platforms in the Intelligent Systems subject of a private university in Ecuador. Some limitations, such as lighting and video quality, affected the level of accuracy. The number of registered participants was 12, of which between 30% and 80% attended. The maximum level of attention detected was 91.9%, while the minimum level was 86.6%. This case study proves that the head position detection function employed by many videoconferencing platforms is a useful parameter that aids the instructor in this type of context.

Application of Computer Vision and Mobile Systems in Education: A Systematic Review

“…An extensive selection of mobile applications pertaining to computer vision are presently available for free installation from the Google Play Store [7], enabling students to conveniently access them. A concentration on a variety of subjects, including attendance tracking, educational robots, medical training, online proctoring, perception monitoring, and OC, has been identified through our investigation of current research trends [8], [10], [11][12][13][14], [36][37][38], and [52]. However, it is crucial to acknowledge that the implementation of CV-assisted teaching may also present obstacles or ethical concerns that require attention.…”

“…With the rise of online learning, the demand for proctoring examinations has increased. Researchers have taken an interest in using CVs to monitor student activity during online tests, and several studies have emerged in this area [11][12][13] and [14][15][16]. Additionally, CV can assist in checking documents for plagiarism.…”

Influence of Blockchain Implementation for Virtual Meetings at Home Learning Indonesia

“…In addition, online learning that has been carried out so far received many negative responses for its incapability to meet the participants expectation, which resulted in the participant's final score not being optimal. This is due to several obstacles such as the lack of reliable teachers mastering the platform [3] causing lack of face-to-face interaction whilst interaction plays a fundamental role in online education [4]. Online learning, that brings together teachers and participants everywhere, cannot be separated from the need for virtual meet as a mean of learning.…”