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Cardoso, K., & Zaro , M. A. (2024). Monitorización del aprendizaje en enfermería mediante el electroencefalograma y el Inventario de Motivación Intrínseca - IMI. International Journal of Psychological Research, 17(2), 76–83. https://doi.org/10.21500/20112084.7361
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The editorial board reserves the right of amendments deemed necessary in the application of the rules of publication.
To give up copyright, the authors allow that, International Journal of Psychological Research, distribute the work more broadly, check for the reuse by others and take care of the necessary procedures for the registration and administration of copyright; at the same time, our editorial board represents the interests of the author and allows authors to re-use his work in various forms. In response to the above, authors transfer copyright to the journal, International Journal of Psychological Research. This transfer does not imply other rights which are not those of authorship (for example those that concern about patents). Likewise, preserves the authors rights to use the work integral or partially in lectures, books and courses, as well as make copies for educational purposes. Finally, the authors may use freely the tables and figures in its future work, wherever make explicit reference to the previous publication in International Journal of Psychological Research. The assignment of copyright includes both virtual rights and forms of the article to allow the editorial to disseminate the work in the manner which it deems appropriate.
The editorial board reserves the right of amendments deemed necessary in the application of the rules of publication.
Resumen
Resumen — Los objetivos de este estudio fueron desarrollar el Laboratorio de Aprendizaje Inmersivo en Salud y Enfermería - LIASE, basado en los principales temas de bioseguridad en salud, y evaluar el proceso de aprendizaje de estudiantes de enfermería de pregrado de una universidad pública federal a través del Electroencefalograma (EEG) portátil Emotiv Insight 2.0, observación e Inventario de Motivación Intrínseca. La presente investigación contiene una metodología cualitativa-cuantitativa, exploratoria y experimental a partir de un laboratorio virtual piloto, desarrollado en el Mundo Virtual Inmersivo - IVW, representado en este estudio por Second Life - SL. La muestra estuvo compuesta por 17 estudiantes que estuvieron de acuerdo con los criterios de inclusión del estudio. Entre ellos, 9 estudiantes tenían señales EEG estables. Esos estudiantes fueron observados durante el monitoreo de la actividad cerebral por el EEG, y al final de la ruta de aprendizaje propuesta, llenaron el Inventario de Motivación Intrínseca. Inventario de Motivación Intrínseca (IMI). Los resultados se obtuvieron a través de la triangulación de los diferentes instrumentos de recolección y las variables - Estrés, Entusiasmo/Excitación,
Compromiso, Enfoque/atención y Relajación, medidas y verificadas mediante el análisis de ondas cerebrales del algoritmo Emotiv, algoritmo que corresponde a las métricas de rendimiento cerebral.
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Referencias
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Langroudi, G., Jordanous, A., Li, L. (2018). Music Emotion Capture: emotion- based generation of music using EEG. In: Emotion Modelling and Detection in social media and Online Interaction symposium at the AISB 2018 Convention, (5), Liverpool.
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Mcauley, E., Duncan, T., Tammen, V. (1989). Psychometric Properties of the Intrinsic Motivation Inventory in a Competitive Sport Setting: A Confirmatory Factor Analysis. Research Quarterly for Exercise and Sport, (60), 1, 48–58.
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Nunes, W. Zaro, M. A. (2019). Neuroempreendedorismo: como o cérebro identifica oportunidades de negócios inovadores. São Luís: EDUFARMA, 212 p.
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Tokuhama-Espinosa, T. N. (2008). The scientifically substantiated art of teaching: A study in the development of standards in the new academic field of neuroeducation (mind, brain, and education science). Tese de Doutorado, Programa de Pós-Graduação em Educação, Capella University, Minneapolis, Minesota.
Tsai, Y. C.; Lin, G. L.; Cheng, C. C. (2021). . Work-in-Progress-Development of Immersive Nursing Skills Learning System and Evaluation of Learning Effectiveness. In: International Conference of the Immersive Learning Research Network (iLRN), 7 ed., 1-3.
Wang, Q.; Sourina, O. (2013). Real-time mental arithmetic task recognition from EEG signals. IEEE Transactions on Neural Systems and Rehabilitation Engineering, (21), 2, 225–232.
Xu, J.; Zhong, B. (2018). Review on portable EEG technology in educational research. Computers in Human Behavior, (81), 340-349.
Yang, X.; Li, Y. ; Wang, L.; Li, D. (2018). Development and Application of Nursing Operation Virtual Simulation Training System. In: International Conference on Engineering Simulation and Intelligent Control (ESAIC), 2018.
Zaro, M. A.; Arosat, R. M., Meireles, L. R .O., Marilda, S., AZEVEDO, A. (2010). Emergência da Neuroeducação: a hora e a vez da neurociência para agregar valor à pesquisa educacional. Ciências & Cognição, (15), 1, 199-210.
Bell, M. W. (2008). Rumo a uma definição de "mundos virtuais". Journal of Virtual Worlds Research, (1),1.
Cardoza, M. P. (2011). Neuroscience and simulation: An evolving theory of brain-based education. Clinical Simulation in Nursing, (7), 6, e205- e208.
Charland, P., Léger, P. M., Sénécal, S., Courtemanche, F., Mercier, J., Skelling, Y., Labonté-Lemoyne, E. (2015). Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective. J. Vis. Exp., (101), e52627J.
Corredor Camargo, J. A., Peña Cortés, C. A., Pardo García, A. (2019). Avaliação das emoções de usuários em tarefas com feedback háptico utilizando o dispositivo Emotiv Insight. INGE CUC, (15), 1, 9–16.
Feiler, J. B.; Stabio, M. E. (2018). Three pillars of educational neuroscience from three decades of literature. Trends in neuroscience and education, (13), 17-25.
Flick, U. (2013). Introdução à metodologia de pesquisa. Porto Alegre: Penso.
Fonseca, V. (2016). Importância das emoções na aprendizagem: uma abordagem neuropsicopedagógica. Rev. psicopedag, (33), 102, 365-384. http://pepsic.bvsalud.org/scielo.php?script=sci_arttext&pid=S0103-84862016000300014&lng= pt&nrm=iso.
Griol, D.; Molina J.M., Callejas, Z. (2014). An approach to develop intelligent learning environments by means of immersive virtual worlds. J. Ambient Intell. Smart Environ, (6), 2, 237–255.
Harrison, T. (2013). The Emotiv mind: investigating the accuracy of the Emotiv EPOC in identifying emotions and its use in an intelligent tutoring system. Honours Report, University of Canterbury, New Zealand.
Langroudi, G., Jordanous, A., Li, L. (2018). Music Emotion Capture: emotion- based generation of music using EEG. In: Emotion Modelling and Detection in social media and Online Interaction symposium at the AISB 2018 Convention, (5), Liverpool.
M. P. E, Rocha. F. A. C. E.; Timmg, M. I. (2010). Emergência da Neuroeducação: a hora e a vez da neurociência para agregar valor à pesquisa educacional. Ciências & Cognição, (15), 1, 199-210.
Mcauley, E., Duncan, T., Tammen, V. (1989). Psychometric Properties of the Intrinsic Motivation Inventory in a Competitive Sport Setting: A Confirmatory Factor Analysis. Research Quarterly for Exercise and Sport, (60), 1, 48–58.
Murad, S.S. (2020). Brain involvement in the use of games in nursing education. Journal of Nursing Education and Practice, (7), 6. http://www.sciedupress.com/journal/index.php/jnep/article/view/7977/6684 Accessed on: 20 Jun 2020.
Ng, B., Ong, A.K.K. (2018). Neurociência e ambiente de aprendizagem digital nas universidades: O que a pesquisa atual nos diz? Revista da Bolsa de Ensino e Aprendizagem, (18), 3, 116-131.
Nunes, W. Zaro, M. A. (2019). Neuroempreendedorismo: como o cérebro identifica oportunidades de negócios inovadores. São Luís: EDUFARMA, 212 p.
Sloan, D. Norrgran, C. (2020). A Neuroscience Perspective on Learning. Chem. Eng. (50), 1, 29, 2016. https://journals.flvc.org/cee/article/view/87714/84511. Accessed on: 10 May.
Soto, V. J. (2013). Which instructional design models are educators using to design virtual world instruction? Journal of Online Learning and Teaching, (9), 3, 364.
Sportsman, S. (2021). Student engagement and the brain. Collaborative Momentum Consulting. https://collaborativemomentum.com/2018/05/22/student- engagement- and-thebrain/#more-230 1/.
Strmiska, M., Koudelková, Z., Žabčíková, M. (2018). Measuring brain signals using Emotiv devices, WSEAS Trans. Syst. Control, (3), p. 537–542.
Tarouco, L. M. R.; Da Silva, P.F. ; Herpich f. (2020). Cognição e aprendizagem em mundo virtual imersivo [recurso eletrônico] Liane Margarida Rockenbach Tarouco, Patrícia Fernanda da Silva [e] Fabrício Herpich (Orgs.); coordenado pela SEAD/UFRGS. 2. ed. Porto Alegre: Editora da UFRGS, 355 p.
Tokuhama-Espinosa, T. N. (2008). The scientifically substantiated art of teaching: A study in the development of standards in the new academic field of neuroeducation (mind, brain, and education science). Tese de Doutorado, Programa de Pós-Graduação em Educação, Capella University, Minneapolis, Minesota.
Tsai, Y. C.; Lin, G. L.; Cheng, C. C. (2021). . Work-in-Progress-Development of Immersive Nursing Skills Learning System and Evaluation of Learning Effectiveness. In: International Conference of the Immersive Learning Research Network (iLRN), 7 ed., 1-3.
Wang, Q.; Sourina, O. (2013). Real-time mental arithmetic task recognition from EEG signals. IEEE Transactions on Neural Systems and Rehabilitation Engineering, (21), 2, 225–232.
Xu, J.; Zhong, B. (2018). Review on portable EEG technology in educational research. Computers in Human Behavior, (81), 340-349.
Yang, X.; Li, Y. ; Wang, L.; Li, D. (2018). Development and Application of Nursing Operation Virtual Simulation Training System. In: International Conference on Engineering Simulation and Intelligent Control (ESAIC), 2018.
Zaro, M. A.; Arosat, R. M., Meireles, L. R .O., Marilda, S., AZEVEDO, A. (2010). Emergência da Neuroeducação: a hora e a vez da neurociência para agregar valor à pesquisa educacional. Ciências & Cognição, (15), 1, 199-210.
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