=Paper=
{{Paper
|id=Vol-2869/PAPER_06
|storemode=property
|title=Methodology to evaluate the levels of attention and meditation in the development of virtual classes through BCI devices
|pdfUrl=https://ceur-ws.org/Vol-2869/PAPER_06.pdf
|volume=Vol-2869
|authors=Wilver Auccahuasi,Christian Ovalle,Zoila Ayvar,Justiniano Aybar,Rubén Quispe,Denny Lovera,Angel Tongo,Luis Romero,Monica Diaz,Iván Perez
}}
==Methodology to evaluate the levels of attention and meditation in the development of virtual classes through BCI devices==
https://ceur-ws.org/Vol-2869/PAPER_06.pdf
Methodology to evaluate the levels of attention and
meditation in the development of virtual classes through BCI
devices
Wilver Auccahuasia, Christian Ovalleb, Zoila Ayvarc, Justiniano Aybard, Rubén Quispee,
Denny Loveraf, Angel Tongog, Luis Romeroh, Monica Diazi and Iván Perezj
abcdefghij
Universidad Continental, Huancayo, Perú
Abstract
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.
Keywords 1
Attention, meditation, registration, online class, students, class activities.
1. Introduction
The pandemic product of COVID-19 has changed the way we carry out most of the activities, the
educational issue is not the exception and to a greater extent, it is the activity where the greatest
changes are taking place and we are learning to be able to adapt our activities to be able to carry out
educational activities in the best way possible. In a normal situation, in the process of choosing
schools, parents make the decision in their facilities that is where their children will receive their
classes. In this new normal, students have to adapt to a home environment to be able to receive their
classes, with which, depending on the place chosen, distracting agents begin to appear, such as radio,
television, toys among others. With all these new ways of developing online classes, papers are
presented where different factors are studied in order to solve the problem as well as the consequences
of these classes.
WTEK-2021: Workshop on Technological Innovations in Education and Knowledge Dissemination, May 01, 2021, Chennai, India.
EMAIL: wauccahuasi@continental.edu.pe (Wilver Auccahuasi)
ORCID: 0000-0001-8820-4013 (Wilver Auccahuasi)
© 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
51
The topic of studying how students concentrate at the time of playing video games in order to
recommend certain aspects that are developed in video games and can be applied in classes, as a
mechanism to improve attention levels. The use of devices related to measuring brain activity, such as
the known BCI, are being used very frequently in different activities such as health to know the
degree of concentration when physical therapy exercises are being performed [1][2][3].
We are not adapting in all aspects and children with disabilities are not alien to their therapies, so
in this context many applications have been developed to continue with the therapies of these children
[4]. In the use of BCIs, they are also being used in the treatment of dependencies in games, managing
to measure certain reactions when conventional games are being performed with the games that are
being affected by children [5]. The BCIs are being used in multiple applications such as in the case of
knowing the way in which educational and learning processes are carried out, in multiple applications
where inter-preter is involved as the brain works in each of the processes [6]. Not only the BCIs are
dedicated to evaluating the processes, but also from the analysis of the EEG signals analyzing the
Alga, beta and Gamma signals mainly in each of the educational processes, with the intention of
analyzing the type of signal that what is commonly called neurolearning are presented [7][10].
On the subject of the use of BCIs, the works are not only focused on being able to analyze the
signals, but also on being able to learn how these interfaces are used in the different uses and
applications to optimize and improve their results [8]. The CO-VID-19 caused the change in the
behavior of many students, in the development of online classes, with which papers are presented
where these changes and the relationship that exist with parents are presented, because normally the
Parents are monitoring the development of classes and are perceiving these changes in students
[11][12]. Information and communication technologies are causing many changes in the way of
learning, including the use of Augmented Reality as an educational agent and BCI as an element for
measuring educational processes [13] [14]. Mental images are being used to test the use and
applications of BCI in the framework of being able to understand the behavior of neurons [15] [16]
[17].
Remote teaching is gaining importance in the continuity of education, at all levels educational
institutions are adapting with the help of technology in order to continue providing their services
[16][18][20][21]. We can indicate that BCIs are being used as a computer element in the evaluation of
educational applications with the intention of measuring how the brain performs learning functions
[19]. Higher studies are not alien to this reality, so it is necessary to evaluate in courses, where
laboratory practices were normally carried out and now they are carried out online as are those
dedicated to health [22].
Finally one of the consequences that are causing him are at home most of the day, as well as the
realization of classes, they are affecting the mental health of people and with greater emphasis on
children, he is unable to leave causes stress in children complicating their mental health [23]. In the
present work we describe a methodology to be able to evaluate the level of attention and meditation in
children in the realization of diverse activities that correspond to the realization of the virtual classes.
2. Materials and Methods
In the development of the methodology, it is proposed to measure and explain the levels of
attention and meditation of the students in the realization of the classes in lines, we can understand
how attention, the mechanism by which the brain is attentive to the actions that the individual
performs, paying the greatest possible concentration to the action he is performing, to understand
meditation, we can indicate that it is the mechanism by which the brain is relaxed without demanding
much, sometimes when it is resting or not paying much attention high levels of meditation are present.
52
In figure 1 a block diagram of the methodology that is proposed is presented with the intention of
being able to analyze each of the processes that was used for the development of the research and
achieve the results, then each of them is described the processes:
Figure 1: Block diagram of the proposed methodology.
2.1. BCI equipment configuration
The equipment that is required to be able to evaluate the levels of attention and meditation, is
characterized by being easy to use and apply, which is why the chosen one is the BCI of the Minwave
brand, which is configured as a headband that is placed on the student's head, has an active sensor that
must be placed on the forehead, port to the subject is easy to use and does not require another
additional device.
Figure 2: BCI device used to demonstrate the methodology.
One of the characteristics that the BCI device has, is the wireless connection, which is not
necessary to condition any cable, the transmission of the signal is carried out via the Bluetooth
communication protocol, in figure 3, the connection form of the device in its three different states,
disconnected, searching and connected, as well as the way to place the positive god on people.
Figure 3: Wireless connection of the BCI device.
The final configuration is the placement of the device on the student's head, it must be borne in
mind that the device must be connected to the computer and that the sensor is just placed on the
student's forehead, Figure 4 shows the placement of the device, ready for evaluation.
53
Figure 4: Device placement ready for evaluation.
2.2. Record of concentration and meditation levels
The following procedure in the block diagram of the methodology is the presentation of the levels
of attention and meditation provided by the application of the device, in it we can describe the levels
from 0% to 100%, the application takes care of analyze the signals of the brain and present us with
these values that correspond to each of the activities that is carried out when the device is being used,
in the demonstration of the methodology it is considered several moments in which the student is
developing activities that correspond to virtual classes.
Figure 5: Sample of the levels of attention and meditation presented by the application of the
device
2.3. Analysis and evaluation of the results
The analysis and evaluation of the results of the measurements of the levels of care and
measurement, will be developed by explaining the scenario where the measurement was carried out
and the factors that have influenced the measured value, between the scenario we can identify the
place where the measurement was carried out. I carry out the measurement, such as the living room of
the house, the room or an office, as distracting agents we can mention if the television was on, a radio
or other electronic object that causes distraction of the student.
3. Results
The results that are presented in the realization of the measurements are presented in two cases, the
first corresponds to a 6-year-old child where different moments in the realization of the online classes
are evaluated. The second case is the evaluation of a 15-year-old student, where the measurements are
also presented at different times when the online classes are being carried out, in both cases the place
54
of the classes as the distraction agents are the same, because both students are in the same physical
place, which is the living room of the house.
3.1. First case: 6-year-old student
In this first case, the student is in the living room of the house and is getting ready to enter his
online class, he has the device installed in his head and connected to the computer ready to record the
levels of attention and meditation.
Figure 6: The student is in the process of entering the online clase.
In figure 7, the results of the measurements of the levels of attention and meditation are presented
when the student is getting ready to enter the online classes, it can be seen that the level of attention is
on average 10%, which indicates Because the student is distracted, the level of meditation is 40%,
which indicates that he pays little attention to the process of starting classes. We can indicate that the
environment where the measurement is carried out is the living room, the television is turned off and
the only distracting agent is the 15-year-old student who is located at the same table, with which this
scene is very common in houses where there are more than two students taking classes online.
Figure 7: Measurements when the student is in the process of entering the online classes
A second moment in the development of the online classes, the student has to solve an exercise
and send the activity, it is at this moment that the student is at the maximum point of concentration, so
that he can perform the activity well and that you can send it, in image 8, you can see how the child is
attentive to the activity he is doing.
55
Figure 8: The student is doing the class activities online.
Figure 9 shows the measurements at the time the student performs online activities, it can be seen
that the level of attention increases considerably, reaching 72% as a result of the student doing the
activities that are considered mandatory, the Meditation level is considered an average of 50% this
value is important because because the student is attentive to the activity he is doing, he is a little
distracted, which means that his attention does not present 100%.
Figure 9: Measurements of the levels of attention and meditation in the process of carrying out
online activities
3.2. Second case: 15-year-old student
In this second case, the evaluations will be carried out on the 15-year-old student, the measurement
conditions indicate that they are in the same environment of the first case, at the same study table,
located in the living room of the house, affected by the same agents distractors.
In a first measurement, the measurement is carried out when the student is browsing the internet in
search of the link of his class on lines, the attention values are at 0% because he does not pay much
attention to the activity that he is doing because it is from daily retina, and otherwise it presents a
level of almost 100% in the level of meditation, product that is calm without any worry or stress, as
can be presented in figure 10.
Figure 10: Measurements when the 15-year-old student is looking for the link to his class online.
56
A next moment of the measurement in the 15-year-old student, is the process of entering his virtual
class, we can observe that the level of attention begins to present an increase close to 30% because the
student is paying attention to his Online class, consequently the value of the meditation begins to fall
to 80% due to the action of the concern of in their online class, as can be seen in figure 11.
Figure 11: Measurements when the 15-year-old student enters his online class.
A third moment is the one in which the student is in his math class, where he presents levels on
average of 60%, where the student is attentive to the teacher's instructions, the value of meditation
begins to decline by 40% product of concern for the theme of the class, as can be seen in figure 12.
Figure 12: 15-year-old student measurements when paying attention in math class.
A fourth moment is the one in which the student is analyzing the mathematics exercises, the
attention values begin to have the maximum peaks with values between 90% product of the attention
that is being made to the exercises, the value of the Meditation decreases by almost 15% as a result of
the completion of the task, as shown in figure 13.
Figure 13: Measurements of the 15-year-old student when he is solving homework in his math class.
A fifth moment and the end of the record is at the time of the task where the student pays attention
to the exercises he is doing, achieving a maximum attention of 100%, with a level of meditation of
approximately 50%, such as presented in figure 14.
57
Figure 14: Measurements of the 15-year-old student when he is attentive in solving the exercises.
4. Conclusions
The discussions of the results after having carried out the evaluations of the levels of attention and
meditation in two students of different ages, but who share the same study environment, as the table
located in the living room of their house, being influenced by them distraction agents. We can indicate
that the levels of attention are different in both students when they are carrying out similar tasks, in
the case of the 6-year-old student, no matter how much they are doing the online class activities, they
present a maximum attention level of 72% reaching 100% due to the fact that the student at that age
of 6 years tend to be very distracted, compared to the 15-year-old student who presents a maximum of
100% attention when doing class activities. We can end by discussing that the students, depending on
their age, present different levels of attention to the activities they are doing.
The main conclusions of the study may be presented in a short Conclusions section, which may
stand alone or form a subsection of a Discussion or Results and Discussion section. Conclusions
should provide a summary of important findings and their implicants to the area of research that is the
forms of the article.
We can conclude at the end of this investigation, first that the environments of the house are not
adequate to carry out school activities, but due to the effects of the pandemic produced by COVID-19,
it is necessary to prepare and ensure the best conditions for Take advantage of the classes, being at
home the students will always present distracting agents, such as the television, the toys among
others, a second conclusion is related to the number of students who are at home, in most cases, the
brothers share the same workbench, consequently as the brother in his online class, is also part of a
distracting agent. A third conclusion is related to the difference in ages and its relationship with the
level of attention they present, at a younger age the students tend to be distracted, in the realization of
normal classes, the teachers of the students aged between 6 and 9 years old, they fight for their
students to pay attention, in most cases the teachers require assistants to be able to attend the students;
In this same scenario, students of those ages, being in their online classes at home, tend to be more
distracted, because they are at home accompanied by parents, siblings or a relative, added to the
proximity of their toys or other objects that they are of interest to him, compared to older students
such as 15-year-olds who concentrate better. The measurements that were managed to register the
levels of concentration and meditation can serve both teachers and parents in being able to better
adapt the conditions where the students carry out their classes as well as the activities of the class in
favor of the students. Can pay more attention to online classes.
5. References
[1] Auccahuasi, W., Díaz, M., Sernaque, F., Flores, E., Aiquipa, G., Rojas, G., ... & Moggiano, N.
(2019, November). Analysis of the comparison of the levels of concentration and meditation in
the realization of academic activities and activities related to videogames, based on brain
58
computer interface. In Proceedings of the 5th International Conference on Communication and
Information Processing (pp. 154-157).
[2] Auccahuasi, W., Diaz, M., Sandivar, J., Flores, E., Sernaque, F., Bejar, M., ... & Moggiano, N.
(2019, November). Design of a mechanism based on virtual reality to improve the ability of
graduated motor imagery, using the brain computer interface. In Proceedings of the 5th
International Conference on Communication and Information Processing (pp. 119-123).
[3] Auccahuasi, W., Flores, E., Sernaqué, F., Sandivar, J., Castro, P., Gutarra, F., & Moggiano, N.
(2019, November). Technique for the comparison of concentration and meditation levels in the
performance of rehabilitation exercises in bicycle, using virtual reality techniques and brain
computer interface. In 2019 E-Health and Bioengineering Conference (EHB) (pp. 1-4). IEEE.
[4] Battistin, T., Mercuriali, E., Zanardo, V., Gregori, D., Lorenzoni, G., Nasato, L., & Reffo, M. E.
(2020). Distance support and online intervention to blind and visually impaired children during
the pandemic COVID-19. Research in Developmental Disabilities, 103816
https://doi.org/10.1016/j.ridd.2020.103816
[5] Bonfiglio, NS, Renati, R. y Pessa, E. (2019). El uso de la interfaz cerebro-computadora (BCI)
combinado con juegos serios para el tratamiento de la dependencia patológica. En Sistémicos de
incompletitud y cuasi-sistemas (págs. 317-324). Springer, Cham.
[6] Burgos, D. (2020). Experimento de imágenes motoras con BCI: un enfoque de tecnología
educativa. Soluciones radicales y análisis del aprendizaje: aprendizaje y enseñanza
personalizados a través de Big Data , 81.
[7] Chae, Y. (2020). Neuroaprendizaje adaptativo: una nueva estrategia educativa que utiliza
interfaces pasivas cerebro-computadora basadas en EEG (tesis doctoral, 한양 대학교).
[8] Crawford, CS, Gardner-McCune, C. y Gilbert, JE (2018, febrero). Interfaz cerebro-computadora
para programadores novatos. En Actas del 49º Simposio Técnico de ACM sobre Educación en
Ciencias de la Computación (págs. 32-37).
[9] Crawford, CS y Gilbert, JE (2019). Cerebros y bloques: Introducción a los programadores
novatos al desarrollo de aplicaciones de interfaz cerebro-computadora. ACM Transactions on
Computing Education (TOCE) , 19 (4), 1-27.
[10] Daza, CAO, Garrido, FB y Burgos, D. (2020). Experimento de imágenes motoras con BCI: un
enfoque de tecnología educativa. En Radical Solutions and Learning Analytics (págs. 81-
98). Springer, Singapur.
[11] Dong, C., Cao, S., & Li, H. (2020). Young children’s online learning during COVID-19
pandemic: Chinese parents’ beliefs and attitudes. Children and Youth Services Review, 118.
https://doi.org/10.1016/j.childyouth.2020.105440
[12] Eyimaya, A. O., & Irmak, A. Y. Relationship between parenting practices and children's screen
time during the COVID-19 Pandemic in Turkey. Journal of pediatric nursing, 56, 24-29.
[13] Gang, P., Hui, J., Stirenko, S., Gordienko, Y., Shemsedinov, T., Alienin, O., ... y González, EA
(2018, abril). Interfaz inteligente impulsada por el usuario sobre la base de la realidad aumentada
multimodal y la interacción cerebro-computadora para personas con discapacidades
funcionales. En Future of Information and Communication Conference (págs. 612-
631). Springer, Cham.
59
[14] Hernandez-Cuevas, B., Egbert, W., Denham, A., Mehul, A. y Crawford, CS (2020,
abril). Mentes cambiantes: exploración de experiencias de interfaz cerebro-computadora con
estudiantes de secundaria. En resúmenes extendidos de la Conferencia CHI de 2020 sobre
factores humanos en sistemas informáticos (págs. 1-10).
[15] Naufel, S. y Klein, E. (2020). Perspectivas de los investigadores de la interfaz cerebro-
computadora (BCI) sobre la propiedad y privacidad de los datos neuronales. Revista de
ingeniería neuronal , 17 (1), 016039.
[16] Peñuelas, S. A. P., Pierra, L. I. C., González, Ó. U. R., & Nogales, O. I. G. (2020). Enseñanza
remota de emergencia ante la pandemia Covid-19 en Educación Media Superior y Educación
Superior. Propósitos y Representaciones, 8(SPE3), 589.
[17] Pillette, L., Jeunet, C., N'Kambou, R., N'Kaoua, B. y Lotte, F. (2019). Hacia compañeros de
aprendizaje artificiales para interfaces cerebro-computadora basadas en imágenes
mentales. preimpresión de arXiv arXiv: 1905.09658 .
[18] Pombo, A., Luz, C., Rodrigues, L. P., Ferreira, C., & Cordovil, R. (2020). Correlates of
children’s physical activity during the COVID-19 confinement in Portugal. Public Health, 189,
14–19. https://doi.org/10.1016/j.puhe.2020.09.009
[19] Spüler, M., Krumpe, T., Walter, C., Scharinger, C., Rosenstiel, W. y Gerjets, P.
(2017). Interfaces cerebro-computadora para aplicaciones educativas. En entornos
informativos (págs. 177-201). Springer, Cham.
[20] Qazi, J., Naseer, K., Qazi, A., AlSalman, H., Naseem, U., Yang, S.,… Gumaei, A.
(2020). Evolución de la educación en línea en todo el mundo durante una pandemia de
coronavirus SARS-CoV-2 (COVID-19): ¿los desarrollados y los subdesarrollados se enfrentan
por igual? Revisión de servicios para niños y jóvenes,
105582. https://doi.org/10.1016/j.childyouth.2020.105694
[21] Wlodarczyk, J. R., Alicuben, E. T., Hawley, L., Sullivan, M., Ault, G. T., & Inaba, K. (2020).
Development and emergency implementation of an online surgical education curriculum for a
General Surgery program during a global pandemic: The University of Southern California
experience. American Journal of Surgery. https://doi.org/10.1016/j.amjsurg.2020.08.045
[22] Yang, X., Li, D., Liu, X., & Tan, J. (2020). Learner behaviors in synchronous online
prosthodontic education during the 2020 COVID-19 pandemic. Journal of Prosthetic Dentistry.
https://doi.org/10.1016/j.prosdent.2020.08.004
[23] Yeasmin, S., Banik, R., Hossain, S., Hossain, M. N., Mahumud, R., Salma, N., & Hossain, M. M.
(2020). Impact of COVID-19 pandemic on the mental health of children in Bangladesh: A cross-
sectional study. Children and Youth Services Review, 117.
https://doi.org/10.1016/j.childyouth.2020.105277
60