The purpose of this work is to be able to identify the levels of attention and meditation at the time the virtual classes are held, as a result of the COVID-19 pandemic; the conventional way of studying change considerably, and to a greater extent the physical place where the classes are held. Faced with this situation, children tend to be distracted by many distracting agents such as television. The proposed methodology allows evaluating the levels of attention and meditation in children when they are in their virtual classes, it is evaluated using a device for measuring brain signals better known as the brain-computer interface, which provides us with a level of attention and of meditation from 0 to 100%. The results that are presented are related to average values of the measurements made, to demonstrate the methodology was evaluated by two situations, the first is the measurement of a 6-year-old child and the second that of a 15-year-old, each of them With totally different situations in the realization of virtual classes, the measurements show that the 6-year-old child tends more to be distracted with values of 20% of attention and meditation when he is preparing for the class, achieving levels of attention of 72% When they are concentrated on the completion of the tasks, the results in the 15-year-old student show that they are less likely to be distracted, registering levels of attention of 30% when they are entering their classes and reaching high levels of attention above from 90% to 100% when they are solving math problems, the study concludes that students, depending on their age, pay different attention to virtual classes, recommending eliminating distraction agents to improve the attention of students when they are in virtual classes.
|Number of pages||10|
|Journal||CEUR Workshop Proceedings|
|State||Published - 2021|
|Event||2021 Workshop on Technological Innovations in Education and Knowledge Dissemination, WTEK 2021 - Virtual, Goa, India|
Duration: 30 Apr 2021 → 1 May 2021
- Class activities
- Online class