Analysis of stress, attention, interest, and engagement in onsite and online higher education: A neurotechnological study

 David Juárez-Varón, University of Valencia (Spain)

 Isabel Bellido-García, Polytechnic University of Valencia (Spain)

 Brij-B. Gupta, Asia University (Taiwan)

https://doi.org/10.3916/C76-2023-02

Keywords

Learning, classroom teaching, online teaching, university, educational innovation, neuroeducation

Abstract

The aim of this work is to register and analyse, using neurotechnology, in onsite onsite and online university educational context, the effect on relevant variables in the learning process. This represents an innovation in the current academic literature in this field. In this study, neuroscience technology has been used to measure the cognitive processing of stimuli designed for an academic experience in a university master's degree class. The neurotechnologies employed were galvanic skin response (GSR), electroencephalography (EEG) and eye tracking. After the analysis of the brain recordings, based on attention, interest, stress and engagement in an onsite educational context and their comparative analysis with the online monitoring, the results indicated that the levels of emotional intensity of the students who followed the class in person were higher than those who attended online. At the same time, the values of positive brain activity (attention, interest and engagement) were higher in the onsite group, and the negative variable stress was also higher, which could be explained by the fact that the online students did not activate the camera. The brain recordings of students who were distance learning show less interest and attention, as well as less emotional intensity, demonstrating that distance (online) learning is less effective than classroom learning, in terms of brain signals, for a theoretical university master's degree class.

References

Anand, K., Ruchika, K., Ram, S.K., Iqbal, A., & Puneet, W. (2014). Alternative healing therapies in todays era. International Journal of Research in Ayurveda and Pharmacy, 5(3), 394-396. https://doi.org/10.7897/2277-4343.05381

Link DOI | Link Google Scholar

Ber?ík, J., Horská, E., Gálová, J., & Margianti, E.S. (2016). Consumer neuroscience in practice: The impact of store atmosphere on consumer behavior. Periodica Polytechnica Social and Management Sciences, 24(2), 96-101. https://doi.org/10.3311/PPso.8715

Link DOI | Link Google Scholar

Bernal, I.M. (2022). El examen oral como promotor del aprendizaje activo. Revista Científica Estudios e Investigaciones, 11(1), 130-134. https://doi.org/10.26885/rcei.11.1.130

Link DOI | Link Google Scholar

Bittencourt, T., & Willetts, A. (2018). Negotiating the tensions: A critical study of international schools’ mission statements. Globalisation, Societies and Education, 16(4), 515-525. https://doi.org/10.1080/14767724.2018.1512047

Link DOI | Link Google Scholar

Bowers, J.S. (2016). The practical and principled problems with educational neuroscience. Psychological Review, 123(5), 600. https://doi.org/10.1037/rev0000025

Link DOI | Link Google Scholar

Bueno-i-Torrens, D., & Forés-Miravalles, A. (2018). 5 principles of neuroeducation that families should know to put in practice. Revista Iberoamericana de Educacion, 78(1), 13-25. https://doi.org/10.35362/rie7813255

Link DOI | Link Google Scholar

Bueno-i-Torrens, D., & Forés-Miravalles, A. (2021). Neuroscience applied to education: How the brain learns and what consequences this has. Llengua Societat I Comunicació, 19, 37-45. https://doi.org/10.1344/LSC-2021.19.5

Link DOI | Link Google Scholar

Campbell, S.R. (2011). Educational Neuroscience: Motivations, methodology, and implications. Educational Philosophy and Theory, 43(1), 7-16. https://doi.org/10.1111/j.1469-5812.2010.00701.x

Link DOI | Link Google Scholar

Carew, T.J., & Magsamen, S.H. (2010). Neuroscience and education: An ideal partnership for producing evidence-based solutions to guide 21st century learning. Neuron, 67(5), 685-688. https://doi.org/10.1016/j.neuron.2010.08.028

Link DOI | Link Google Scholar

Chávez-Miyauchi, T.E., Benitez-Rico, A., Alcántara-Flores, M., Vergara-Castañeda, A., & Ogando-Justo, A.B. (2021). Personal motivation and learning self-management in students, as result of the transition to online courses during COVID-19 pandemic. Nova scientia, 13. https://doi.org/10.21640/ns.v13ie.2739

Link DOI | Link Google Scholar

Clark, D.B. Tanner-Smith, E.E., & Killingsworth, S.S. (2016). Digital games, design, and learning: A systematic review and meta-analysis. Review of Educational Research, 86(1), 79-122. https://doi.org/10.3102/0034654315582065

Link DOI | Link Google Scholar

Cuesta-Cambra, U., Niño-González, J., & Rodríguez-Terceño, J. (2017). The cognitive processing of an educational app with EEG and ’Eye Tracking’. [El procesamiento cognitivo en una app educativa con electroencefalograma y «Eye Tracking»]. Comunicar, 52, 41-50. https://doi.org/10.3916/C52-2017-04

Link DOI | Link Google Scholar

da-Silva, F.L., Slodkowski, B.K., da Silva, K.K.A., & Cazella, S.C. (2023). A systematic literature review on educational recommender systems for teaching and learning: Research trends, limitations and opportunities. Education and Information Technologies, 28, 3289-3328. https://doi.org/10.1007/s10639-022-11341-9

Link DOI | Link Google Scholar

Doyle, A., Seery, N., Canty, D., & Buckley, J. (2019). Agendas, influences, and capability: Perspectives on practice in design and technology education. International Journal of Technology and Design Education, 29(1), 143-159. https://doi.org/10.1007/s10798-017-9433-0

Link DOI | Link Google Scholar

Duchowski, A.T. (2007). Eye tracking techniques. In A.T. Duchowski (Ed.), Eye tracking methodology (pp. 51-59). Springer. https://doi.org/10.1007/978-3-319-57883-5

Link DOI | Link Google Scholar

Ferrari, M. (2011). What can neuroscience bring to education? Educational Philosophy and Theory, 43(1), 31-36. https://doi.org/10.1111/j.1469-5812.2010.00704.x

Link DOI | Link Google Scholar

Ghergulescu, I., & Hava-Muntean, C. (2016). ToTCompute: A novel EEG-based TimeOnTask threshold computation mechanism for engagement modelling and monitoring. International Journal of Artificial Intelligence in Education, 26(3), 821-854. https://doi.org/10.1007/s40593-016-0111-2

Link DOI | Link Google Scholar

Hillman, T. (2011). The inscription, translation and re-inscription of technology for mathematical learning. Technology, Knowledge and Learning, 16, 103-124. https://doi.org/10.1007/s10758-011-9182-1

Link DOI | Link Google Scholar

Horn, C., Snyder, B. P., Coverdale, J. H., Louie, A. K., & Roberts, L. W. (2009). Educational Research Questions and Study Design. Academic Psychiatry, 33, 261-267. https://doi.org/10.1176/appi.ap.33.3.261

Link DOI | Link Google Scholar

Howard-Jones, P.A. (2014). Neuroscience and education: Myths and messages. Nature Reviews Neuroscience, 15, 817-824. https://doi.org/10.1038/nrn3817

Link DOI | Link Google Scholar

Huamán-Romaní, Y.L., Estrada-Pantía, J. L., Olivares-Rivera, O., Rodas-Guizado, E., & Fuentes-Bernedo, F. E. (2021). Use of technological equipment for e-learning in Peruvian university students in times of Covid-19. International Journal of Emerging Technologies in Learning, 16(20), 119-133. https://doi.org/0.3991/ijet.v16i20.24661

Link DOI | Link Google Scholar

Isen, A.M., & Reeve, J. (2005). The influence of positive affect on intrinsic and extrinsic motivation: Facilitating enjoyment of play, responsible work behavior, and self-control. Motivation and Emotion, 29(4), 295-323. https://doi.org/10.1007/s11031-006-9019-8

Link DOI | Link Google Scholar

Juarez, D., Tur-Viñes, V., & Mengual, A. (2020). Neuromarketing Applied to Educational Toy Packaging. Frontiers in Psychology, 11, 2077. https://doi.org/10.3389/fpsyg.2020.02077

Link DOI | Link Google Scholar

Klingner, J. K., & Boardman, A.G. (2011). Addressing the “research gap” in special education through mixed methods. Learning Disability Quarterly, 34(3), 208-218. https://doi.org/10.1177/0731948711417559

Link DOI | Link Google Scholar

Lai, J.W.M., & Bower, M. (2019). How is the use of technology in education evaluated? A systematic review. Computers & Education, 133, 27-42. https://doi.org/10.1016/j.compedu.2019.01.010

Link DOI | Link Google Scholar

Lee, C., Yeung, A.S., & Cheung, K.W. (2019). Learner perceptions versus technology usage: A study of adolescent English learners in Hong Kong secondary schools. Computers & Education, 133, 13-26. https://doi.org/10.1016/j.compedu.2019.01.005

Link DOI | Link Google Scholar

Lin, J.S., & Hsieh, C.H. (2016). A wireless BCI-controlled integration system in smart living space for patients. Wireless Personal Communications, 88(2), 395-412. https://doi.org/10.1007/s11277-015-3129-0

Link DOI | Link Google Scholar

Morgado-Bernal, I. (2005). The psychobiology of learning and memory fundamentals and recent advances [Review]. Revista De Neurologia, 40(5), 289-297. https://doi.org/10.33588/rn.4005.2005004

Link DOI | Link Google Scholar

Morgan, J. (2015). Online Versus face-to-face accounting education: A comparison of CPA exam outcomes across matched institutions. Journal of Education for Business, 90(8), 420-426. https://doi.org/10.1080/08832323.2015.1087371

Link DOI | Link Google Scholar

Plassmann, H., Zoëga-Ramsøy, T., & Milosavljevic, M.(2012). Branding the brain: A critical review and outlook. Journal of Consumer Psychology, 22(1), 18-36. https://doi.org/10.1016/j.jcps.2011.11.010

Link DOI | Link Google Scholar

Price, L., Richardson, J.T.E., & Jelfs, A. (2007). Face-to-face versus online tutoring support in distance education. Studies in Higher Education, 32(1), 1-20. https://doi.org/10.1080/03075070601004366

Link DOI | Link Google Scholar

Prinzel, L.J., Freeman, F.G., Scerbo, M.W., Mikulka, P.J., & Pope, A.T. (2009). A closed-loop system for examining psychophysiological measures for adaptive task allocation. The International journal of aviation psychology, 10(4), 393-410. https://doi.org/10.1207/S15327108IJAP1004_6

Link DOI | Link Google Scholar

Ramele, R., Villar, A.J., & Santos, J.M. (2012). EPOC Emotiv EEG Basics. https://bit.ly/3FrQKPH

Link Google Scholar

Ramírez-Montoya, M., & Lugo-Ocando, J. (2020). Systematic review of mixed methods in the framework of educational innovation. [Revisión sistemática de métodos mixtos en el marco de la innovación educativa]. Comunicar, 65, 9-20. https://doi.org/10.3916/C65-2020-01

Link DOI | Link Google Scholar

Rikkerink, M., Verbeeten, H., Simons, R.S., & Ritzen, H. (2016). A new model of educational innovation: Exploring the nexus of organizational learning, distributed leadership, and digital technologies. Journal of Educational Change, 17, 223-249. https://doi.org/10.1007/s10833-015-9253-5

Link DOI | Link Google Scholar

Saeed, S., & Zyngier, D. (2012). How motivation influences student engagement: A qualitative case study. Journal of Education and Learning, 1(2), 252-267. https://doi.org/10.5539/jel.v1n2p252

Link DOI | Link Google Scholar

Sánchez-Mendiola, M., Martínez-Hernández, A.M.P., Torres-Carrasco., Agüero-Servín, M.M., Hernández-Romo, A.K., Benavides-Lara, M.A., Rendón-Cazales, V.J., & Jaímes-Vergara, C.A. (2020). Retos educativos durante la pandemia de COVID-19: Una encuesta a profesores de la UNAM. Revista digital universitaria, 21(3), 1-24. https://doi.org/10.22201/codeic.16076079e.2020.v21n3.a12

Link DOI | Link Google Scholar

Serrano-Díaz, N., Aragón-Mendizábal, E., & Mérida-Serrano, R. (2022). Families’ perception of children’s academic performance during the COVID-19 lockdown. [Percepción de las familias sobre el desempeño escolar durante el confinamiento por COVID-19]. Comunicar, 70, 59-68. https://doi.org/10.3916/C70-2022-05

Link DOI | Link Google Scholar

Sevimli, E. (2022). Evaluation of the didactic transposition process in teaching integral: Face-to-Face versus online education. International Journal for Technology in Mathematics Education, 29(1), 37-48. https://doi.org/10.1564/tme_v29.1.04

Link DOI | Link Google Scholar

Talmi, D., Anderson, A., Riggs, L., Caplan, J.B., & Moscovitch, M. (2008). Immediate memory consequences of the effect of emotion on attention to pictures. Learning & Memory, 15(3), 172-182. https://doi.org/10.1101/lm.722908

Link DOI | Link Google Scholar

Thomas, M.S.C., Ansari, D., & Knowland, V.C.P. (2019). Annual Research Review: Educational neuroscience: progress and prospects [Review]. Journal of Child Psychology and Psychiatry, 60(4), 477-492. https://doi.org/10.1111/jcpp.12973

Link DOI | Link Google Scholar

Torras, M., Portell, I., & Morgado-Bernal, I. (2001). The amygdaloid body: Functional implications. Revista de Neurologia, 33(5), 471-476. https://doi.org/10.33588/rn.3305.2001125

Link DOI | Link Google Scholar

Van-Ameringen, M., Mancini, C., & Favorlden, P. (2003). The impact of anxiety disorders on educational achievement. Journal of Anxiety disorders, 17(5), 561-571. https://doi.org/10.1016/S0887-6185(02)00228-1

Link DOI | Link Google Scholar

Van-Doorn, J., Lemon, K.N., Mittal, V., Nass, S., Pick, D., Pirner, P., & Verhoef, P.C. (2010). Customer engagement behavior: Theoretical foundations and research directions. Journal of Service Research, 13(3), 253-266. https://doi.org/10.1177/1094670510375599

Link DOI | Link Google Scholar

Varma, S., McCandliss, B.D., & Schwartz, D.L. (2008). Scientific and pragmatic challenges for bridging education and neuroscience. Educational Researcher, 37(3), 140-152. https://doi.org/10.3102/0013189X08317687

Link DOI | Link Google Scholar

Villardón-Gallego, L., García-Carrión, R., Tánez-Marquina., & Estévez, A. (2018). Impact of the interactive learning environments in children’s prosocial behavior. Sustainability, 10(7), 2138. https://doi.org/10.3390/su10072138

Link DOI | Link Google Scholar

Wang, C.C., & Hsu, M.C. (2014). An exploratory study using inexpensive electroencephalography (EEG) to understand flow experience in computer-based instruction. Information & Management, 51(7), 912-923. https://doi.org/10.1016/j.im.2014.05.010

Link DOI | Link Google Scholar

Waxman, H.C., Wirr-Boriack, A., Lee, Y.H., & MacNeil, A. (2013). Principals' perceptions of the importance of technology in schools. Contemporary Educational Technology, 4(3), 187-196. https://doi.org/10.30935/cedtech/6102

Link DOI | Link Google Scholar

Xu, J., & Zhong, B. (2018). Review on portable EEG technology in educational research. Computers in Human Behavior, 81, 340-349. https://doi.org/10.1016/j.chb.2017.12.037

Link DOI | Link Google Scholar

Yadava, M., Kumar, P., Saini, R., Pratim-Roy, P., & Prosad-Dogra, D. (2017). Analysis of EEG signals and its application to neuromarketing. Multimedia Tools and Applications, 76(18), 19087-19111. https://doi.org/10.1007/s11042-017-4580-6

Link DOI | Link Google Scholar

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Technical information

Received: 25-12-2022

Revised: 22-01-2023

Accepted: 23-02-2023

OnlineFirst: 30-05-2023

Publication date: 01-07-2023

Article revision time: 28 days | Average time revision issue 76: -6 days

Article acceptance time: 60 days | Average time of acceptance issue 76: 72 days

Preprint editing time: 143 days | Average editing time preprint issue 76: 155 days

Article editing time: 188 days | Average editing time issue 76: 200 days

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