Optimizing Learning Environments Through the Lens of Neuroscience: A Study on the Role of Emotion, Motivation, and Brain Plasticity.

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Ahmad Roisuddin Ritonga
Ahmad Lahmi
Rosniati Hakim
Dasrizal Dahlan

Abstract

This study aims to optimize learning environments through the integration of neuroscience principles, focusing on the roles of emotion, motivation, and brain plasticity in enhancing learning outcomes. Based on theoretical and conceptual analyses, this research demonstrates that the human brain is a dynamic organ capable of adaptation through neuroplasticity, which can be stimulated by mental, physical, and multisensory inputs. Emotions are shown to play a central role in learning, with the activation of the amygdala and hippocampus influencing memory consolidation, while intrinsic motivation triggered by autonomy and task relevance significantly increases student engagement. Modern technologies such as augmented reality (AR), virtual reality (VR), and adaptive algorithms offer significant opportunities to create immersive and personalized learning experiences. However, the implementation of these technologies still faces challenges related to accessibility and ethical considerations. This study emphasizes the importance of collaboration among neuroscientists, educators, and policymakers to create adaptive, inclusive, and sustainable learning environments. The findings provide new insights into how neuroscience can be utilized as a tool to transform education, while taking into account social, cultural, and individual student needs

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Roisuddin Ritonga, A., Lahmi, A., Hakim, R., & Dahlan , D. (2025). Optimizing Learning Environments Through the Lens of Neuroscience: A Study on the Role of Emotion, Motivation, and Brain Plasticity. Edu Global : Jurnal Pendidikan Islam, 6(1), 12-19. https://doi.org/10.56874/eduglobal.v6i1.2183
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References

[1] K. Pradeep, R. Sulur Anbalagan, A. P. Thangavelu, S. Aswathy, V. G. Jisha, and V. S. Vaisakhi, “Neuroeducation: understanding neural dynamics in learning and teaching,” Front. Educ., vol. 9, 2024, doi: 10.3389/feduc.2024.1437418.
[2] D. Rajgor and J. G. Hanley, “The ins and outs of miRNA-mediated gene silencing during neuronal synaptic plasticity,” Non-coding RNA, vol. 2, no. 1, 2016, doi: 10.3390/ncrna2010001.
[3] M. Kossut, “Basic mechanism of neuroplasticity,” Neuropsychiatr. i Neuropsychol., vol. 14, no. 1–2, pp. 1–8, 2019, doi: 10.5114/nan.2019.87727.
[4] R. E. Brown, “Donald O. Hebb and the Organization of Behavior: 17 years in the writing,” Mol. Brain, vol. 13, no. 1, 2020, doi: 10.1186/s13041-020-00567-8.
[5] R. Der, “In search for the neural mechanisms of individual development: Behavior-driven differential Hebbian learning,” Front. Robot. AI, vol. 2, no. JAN, 2016, doi: 10.3389/frobt.2015.00037.
[6] S. J. Cooper, “Donald O. Hebb’s synapse and learning rule: A history and commentary,” Neurosci. Biobehav. Rev., vol. 28, no. 8, pp. 851–874, 2005, doi: 10.1016/j.neubiorev.2004.09.009.
[7] P. Li, J. Legault, and K. A. Litcofsky, “Neuroplasticity as a function of second language learning: Anatomical changes in the human brain,” Cortex, vol. 58, pp. 301–324, 2014, doi: 10.1016/j.cortex.2014.05.001.
[8] K. Hötting and B. Röder, “Beneficial effects of physical exercise on neuroplasticity and cognition,” Neurosci. Biobehav. Rev., vol. 37, no. 9, pp. 2243–2257, 2013, doi: 10.1016/j.neubiorev.2013.04.005.
[9] B. S. McEwen, “A life-course, epigenetic perspective on resilience in brain and body,” in Stress Resilience: Molecular and Behavioral Aspects, 2020, pp. 1–21. doi: 10.1016/B978-0-12-813983-7.00001-X.
[10] E. Wenger and S. Kühn, “Neuroplasticity,” in Cognitive Training: An Overview of Features and Applications: Second Edition, 2020, pp. 69–83. doi: 10.1007/978-3-030-39292-5_6.
[11] V. Farmer-Dougan and L. A. Alferink, “Brain development, early childhood, and brain-based education: A critical analysis,” in Early Childhood and Neuroscience - Links to Development and Learning, 2013, pp. 55–76. doi: 10.1007/978-94-007-6671-6_5.
[12] E. Acosta-Gonzaga and A. Ramirez-Arellano, “The Influence of Motivation, Emotions, Cognition, and Metacognition on Students’ Learning Performance: A Comparative Study in Higher Education in Blended and Traditional Contexts,” SAGE Open, vol. 11, no. 2, 2021, doi: 10.1177/21582440211027561.
[13] T. Panskyi, S. Biedroń, K. Grudzień, and E. Korzeniewska, “The comparative estimation of primary students’ programming outcomes based on traditional and distance out-of-school extracurricular informatics education in electronics courses during the challenging COVID-19 period,” Sensors, vol. 21, no. 22, 2021, doi: 10.3390/s21227511.
[14] K. Oatley and S. Nundy, “Rethinking the Role of Emotions in Education,” in The Handbook of Education and Human Development: New Models of Learning, Teaching and Schooling, 2008, pp. 247–262. doi: 10.1111/b.9780631211860.1998.00013.x.
[15] I. Ahmad, R. Gul, and M. Zeb, “A Qualitative Inquiry of University Student’s Experiences of Exam Stress and Its Effect on Their Academic Performance,” Hum. Arenas, vol. 7, no. 4, pp. 778–788, 2024, doi: 10.1007/s42087-022-00285-8.
[16] P. S. Kudachi, R. G. Latti, and S. S. Goudar, “Effect of examination stress on the academic performance of first year medical students,” Biomedicine, vol. 28, no. 2, pp. 142–144, 2008, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-58349093546&partnerID=40&md5=404d850e4fed389a10a92584f8b186d1
[17] M. Ramesh Bhat, M. K. Sameer, and B. Ganaraja, “Eustress in education: Analysis of the perceived stress score (PSS) and blood pressure (BP) during examinations in Medical Students,” J. Clin. Diagnostic Res., vol. 5, no. 7, pp. 1331–1335, 2012, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84861555149&partnerID=40&md5=363fb30fe5a15f51a5e5f3c18f8c7eef
[18] E. Das, A. Shil, S. Saha, A. Das, S. Ghosh, and M. K. Singh, “Effect of stress during exam time on immunity-A Survey based study,” J. Exp. Biol. Agric. Sci., vol. 12, no. 3, pp. 498–510, 2024, doi: 10.18006/2024.12(3).498.510.
[19] S. S. Wadikar, P. A. Muley, and P. P. Muley, “A comparative study of gender difference in reaction time in response to exam stress among first-year medical students,” Natl. J. Physiol. Pharm. Pharmacol., vol. 7, no. 2, pp. 209–213, 2017, doi: 10.5455/njppp.2017.7.0822429082016.
[20] C. D. Conrad, R. L. Wright, and K. J. McLaughlin, “Stress and Vulnerability to Brain Damage,” in Encyclopedia of Neuroscience, 2009, pp. 481–488. doi: 10.1016/B978-008045046-9.00093-0.
[21] M. M. Rahman, C. K. Callaghan, C. M. Kerskens, S. Chattarji, and S. M. O’Mara, “Early hippocampal volume loss as a marker of eventual memory deficits caused by repeated stress,” Sci. Rep., vol. 6, 2016, doi: 10.1038/srep29127.
[22] A. Tomar, D. Polygalov, S. Chattarji, and T. J. McHugh, “Stress enhances hippocampal neuronal synchrony and alters ripple-spike interaction,” Neurobiol. Stress, vol. 14, 2021, doi: 10.1016/j.ynstr.2021.100327.
[23] E. Gkintoni, C. Halkiopoulos, and H. Antonopoulou, “Contributions of Neuroscience to Educational Praxis: A Systematic Review,” Emerg. Sci. J., vol. 7, pp. 146–158, 2023, doi: 10.28991/esj-2023-sied2-012.
[24] S. Eom, “The Effects of Student Motivation and Self-regulated Learning Strategies on Student’s Perceived E-learning Outcomes and Satisfaction,” J. High. Educ. Theory Pract., vol. 19, no. 7, pp. 29–42, 2019, doi: 10.33423/jhetp.v19i7.2529.
[25] Y. Liu, K.-T. Hau, H. Liu, J. Wu, X. Wang, and X. Zheng, “Multiplicative effect of intrinsic and extrinsic motivation on academic performance: A longitudinal study of Chinese students,” J. Pers., vol. 88, no. 3, pp. 584–595, 2020, doi: 10.1111/jopy.12512.
[26] K. E. Leong, P. P. Tan, P. L. Lau, and S. L. Yong, “Exploring the relationship between motivation and science achievement of secondary students,” Pertanika J. Soc. Sci. Humanit., vol. 26, no. 4, pp. 2243–2258, 2018, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060014682&partnerID=40&md5=afa84d318b59549c2cac6652763aad60
[27] C. Varazzani, A. San-Galli, S. Gilardeau, and S. Bouret, “Noradrenaline and dopamine neurons in the reward/effort trade-off: A direct electrophysiological comparison in behaving monkeys,” J. Neurosci., vol. 35, no. 20, pp. 7866–7877, 2015, doi: 10.1523/JNEUROSCI.0454-15.2015.
[28] J. Salamone and M. Correa, “The Mysterious Motivational Functions of Mesolimbic Dopamine,” Neuron, vol. 76, no. 3, pp. 470–485, 2012, doi: 10.1016/j.neuron.2012.10.021.
[29] S. Esumi, Y. Kawasaki, Y. Gomita, Y. Kitamura, and T. Sendo, “Characteristics of the runway model of intracranial self-stimulation behavior and comparison with other motivated behaviors,” Acta Med. Okayama, vol. 68, no. 5, pp. 255–262, 2014, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910006260&partnerID=40&md5=47f5ac6aeb00ffb259de21ec45edbb77
[30] J. S. G. A. Balushi, M. I. A. A. Jabri, S. Palarimath, P. Maran, K. Thenmozhi, and C. Balakumar, “Incorporating Artificial Intelligence Powered Immersive Realities to Improve Learning using Virtual Reality (VR) and Augmented Reality (AR) Technology,” in Proceedings of the 3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024, 2024, pp. 760–765. doi: 10.1109/ICAAIC60222.2024.10575046.
[31] S. Vashisht, “Enhancing Learning Experiences Through Augmented Reality and Virtual Reality in Classrooms,” in 2nd IEEE International Conference on Recent Advances in Information Technology for Sustainable Development, ICRAIS 2024 - Proceedings, 2024, pp. 12–17. doi: 10.1109/ICRAIS62903.2024.10811732.
[32] J. Kubr, A. Lochmannová, and P. Hořejší, “Immersive Virtual Reality Training in Industrial Settings: Effects on Memory Retention and Learning Outcomes,” IEEE Access, vol. 12, pp. 168270–168282, 2024, doi: 10.1109/ACCESS.2024.3496760.
[33] G. Yildirim, S. Yildirim, and E. Dolgunsoz, “The effect of VR and traditional videos on learner retention and decision making,” World J. Educ. Technol. Curr. Issues, vol. 11, no. 1, pp. 21–29, 2019, doi: 10.18844/wjet.v11i1.4005.
[34] H. Champeaux, L. Mangiavacchi, F. Marchetta, and L. Piccoli, “Child development and distance learning in the age of COVID-19,” Rev. Econ. Househ., vol. 20, no. 3, pp. 659–685, 2022, doi: 10.1007/s11150-022-09606-w.
[35] A. I. Kennedy and R. Strietholt, “School closure policies and student reading achievement: evidence across countries,” Educ. Assessment, Eval. Account., vol. 35, no. 4, pp. 475–501, 2023, doi: 10.1007/s11092-023-09415-4.
[36] K. M. Jackson and M. K. Szombathely, “Holistic Online Learning, in a Post COVID-19 World,” Acta Polytech. Hungarica, vol. 19, no. 11, pp. 125–144, 2022, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148750013&partnerID=40&md5=7c3f6a4a6ad7bd32f546708c58918e59
[37] C. Frasson and P. Chalfoun, “Managing learner’s affective states in intelligent tutoring systems,” Stud. Comput. Intell., vol. 308, pp. 339–358, 2010, doi: 10.1007/978-3-642-14363-2_17.
[38] M. Habib, Emotional processes in learning situations. 2022. doi: 10.1002/9781394150458.
[39] S. Chaffar and C. Frasson, “Predicting learners’ emotional response in intelligent distance learning systems,” in FLAIRS 2006 - Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, 2006, pp. 383–388. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-33746104092&partnerID=40&md5=d80a65c5530cdebd8646e4bbda2c9581
[40] S. L. Grams and R. Jurowetzki, “Emotions in the classroom: The powerful role of classroom relationships,” in Dealing with Emotions: A Pedagogical Challenge to Innovative Learning, 2015, pp. 81–98. doi: 10.1007/978-94-6300-064-2_5.
[41] C. Rajamanickam, J. Kayarathya, and M. Oumagandan, “Analysing the Impact of Emotional Learning on Student Well-Being: An Empirical Study,” J. Inf. Knowl. Manag., 2025, doi: 10.1142/S0219649225500042.
[42] Z. G. Baker and J. L. Bryan, “The road to good psychological health: Basic psychological need satisfaction,” in Psychological Health and Needs Research Developments, 2015, pp. 1–10. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84956740976&partnerID=40&md5=f014290d8a0b4a030ece8bd5450e304b
[43] T. J. Ten Cate, R. A. Kusurkar, and G. C. Williams, “How self-determination theory can assist our understanding of the teaching and learning processes in medical education. AMEE Guide No. 59,” Med. Teach., vol. 33, no. 12, pp. 961–973, 2011, doi: 10.3109/0142159X.2011.595435.
[44] T. G. Calvo, E. Cervelló, R. Jiménez, D. Iglesias, and J. A. M. Murcia, “Using self-determination theory to explain sport persistence and dropout in adolescent athletes,” Span. J. Psychol., vol. 13, no. 2, pp. 677–684, 2010, doi: 10.1017/S1138741600002341.
[45] M. S. Alvarez, I. Balaguer, I. Castillo, and J. L. Duda, “Coach autonomy support and quality of sport engagement in young soccer players,” Span. J. Psychol., vol. 12, no. 1, pp. 138–148, 2009, doi: 10.1017/S1138741600001554.
[46] I. E. Johnson et al., “Comparing the Academic Achievement of Students Taught Educational Technology with Doodly-designed Multimedia Instructions in Classroom and Online Learning Environments,” Ianna J. Interdiscip. Stud., vol. 6, no. 2, pp. 161–177, 2024, doi: 10.5281/zenodo.12189075.
[47] A. Alanazi, N. F. Binti Elias, H. B. Mohamed, and N. Sahari, “The critical success factors influencing the use of mobile learning and its perceived impacts in students education: A systematic literature review,” KSII Trans. Internet Inf. Syst., vol. 18, no. 3, pp. 610–632, 2024, doi: 10.3837/tiis.2024.03.005.
[48] C. Gillan, C. Palmer, and A. Bolderston, “Qualitative methodologies and analysis,” in Research for the Radiation Therapist: From Question to Culture, 2014, pp. 127–152. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054208035&partnerID=40&md5=adc14e465f46c26e67f99db85e02bd70
[49] C. Herzog, C. Handke, and E. Hitters, “Analyzing Talk and Text II: Thematic Analysis,” in The Palgrave Handbook of Methods for Media Policy Research, 2019, pp. 385–401. doi: 10.1007/978-3-030-16065-4_22.
[50] N. Toufan, A. Omid, and F. Haghani, “The double-edged sword of emotions in medical education: A scoping review,” J. Educ. Health Promot., vol. 12, no. 1, p. 52, 2023, doi: 10.4103/jehp.jehp_644_21.
[51] I. Cea, “The somatic roots of affect: Toward a body-centered education,” in Affectivity and Learning: Bridging the Gap Between Neurosciences, Cultural and Cognitive Psychology, 2023, pp. 555–583. doi: 10.1007/978-3-031-31709-5_29.
[52] R. F. Mustafina, M. S. Ilina, and I. A. Shcherbakova, “Emotions and their effect on learning,” Utop. y Prax. Latinoam., vol. 25, no. Extra 7, pp. 318–324, 2020, doi: 10.5281/zenodo.4009736.
[53] E. L. Deci and R. M. Ryan, “Self-determination theory: A macrotheory of human motivation, development, and health,” in Canadian Psychology, 2008, pp. 182–185. doi: 10.1037/a0012801.
[54] R. M. Ryan, The Oxford Handbook of Self-Determination Theory. 2023. doi: 10.1093/oxfordhb/9780197600047.001.0001.
[55] M. Khramova, A. Hramov, and A. Fedorov, “Current Trends in the Development of Neuroscientific Research in Education,” Vopr. Obraz. / Educ. Stud. Moscow, vol. 2023, no. 4, pp. 275–316, 2023, doi: 10.17323/vo-2023-16701.
[56] C. H. Meydan and H. Akkaş, “The role of triangulation in qualitative research: Converging perspectives,” in Principles of Conducting Qualitative Research in Multicultural Settings, 2024, pp. 98–129. doi: 10.4018/979-8-3693-3306-8.ch006.
[57] N. H. Mokhtar, M. F. A. Halim, and S. Z. S. Kamarulzaman, “The effectiveness of storytelling in enhancing communicative skills,” in Procedia - Social and Behavioral Sciences, 2011, pp. 163–169. doi: 10.1016/j.sbspro.2011.05.024.
[58] B. McCaffrey, “What can teachers learn from the stories children tell?: The nurturing, evaluation and interpretation of storytelling by children with language and learning difficulties,” in Using Storytelling to Support Children and Adults with Special Needs: Transforming Lives through Telling Tales, 2012, pp. 25–32. doi: 10.4324/9780203080924-9.
[59] V. V Sruthy, A. Saju, and A. G. Hari Narayanan, “Predictive methodology for child behavior from children stories,” J. Eng. Appl. Sci., vol. 13, no. Specialissue5, pp. 4597–4599, 2018, doi: 10.3923/jeasci.2018.4597.4599.
[60] T. J. Schoenfeld, H. C. McCausland, H. D. Morris, V. Padmanaban, and H. A. Cameron, “Stress and Loss of Adult Neurogenesis Differentially Reduce Hippocampal Volume,” Biol. Psychiatry, vol. 82, no. 12, pp. 914–923, 2017, doi: 10.1016/j.biopsych.2017.05.013.
[61] J. L. Warner-Schmidt and R. S. Duman, “Hippocampal neurogenesis: Opposing effects of stress and antidepressant treatment,” Hippocampus, vol. 16, no. 3, pp. 239–249, 2006, doi: 10.1002/hipo.20156.
[62] M. Kavakli, M. Li, and T. Rudra, “Towards the development of a virtual counselor to tackle students’ exam stress,” J. Integr. Des. Process Sci., vol. 16, no. 1, pp. 5–26, 2012, doi: 10.3233/jid-2012-0004.
[63] T. Rudra, M. Li, and M. Kavakli, “ESCAP: Towards the design of an AI architecture for a virtual counselor to tackle students’ exam stress,” in Proceedings of the Annual Hawaii International Conference on System Sciences, 2012, pp. 2981–2990. doi: 10.1109/HICSS.2012.249.
[64] M. Shean and D. Mander, “Building emotional safety for students in school environments: Challenges and opportunities,” in Health and Education Interdependence: Thriving from Birth to Adulthood, 2020, pp. 225–248. doi: 10.1007/978-981-15-3959-6_12.
[65] M. K. Miller et al., “Efficacy of a university offered mindfulness training on perceived stress,” J. Couns. Dev., vol. 100, no. 3, pp. 278–283, 2022, doi: 10.1002/jcad.12421.
[66] A. Morsy, “Emotional matters: Innovative software brings emotional intelligence to our digital devices,” IEEE Pulse, vol. 7, no. 6, pp. 38–41, 2016, doi: 10.1109/MPUL.2016.2608724.
[67] E. D. Brown and K. L. Sax, “Arts enrichment and preschool emotions for low-income children at risk,” Early Child. Res. Q., vol. 28, no. 2, pp. 337–346, 2013, doi: 10.1016/j.ecresq.2012.08.002.
[68] G. A. Toto, “The influences of musical learning on psycho-physical development, intelligence and technology,” Turkish Online J. Educ. Technol., vol. 2017, no. Special Issue 2017, pp. 801–807, 2017, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85038827141&partnerID=40&md5=a1967bf6ae4d681f63ee8d42aff87462
[69] B. Blain and T. Sharot, “Intrinsic reward: potential cognitive and neural mechanisms,” Curr. Opin. Behav. Sci., vol. 39, pp. 113–118, 2021, doi: 10.1016/j.cobeha.2021.03.008.
[70] N. Miura, H. C. Tanabe, A. T. Sasaki, T. Harada, and N. Sadato, “Neural evidence for the intrinsic value of action as motivation for behavior,” Neuroscience, vol. 352, pp. 190–203, 2017, doi: 10.1016/j.neuroscience.2017.03.064.
[71] W. A. Carlezon Jr. and M. J. Thomas, “Biological substrates of reward and aversion: A nucleus accumbens activity hypothesis,” Neuropharmacology, vol. 56, no. SUPPL. 1, pp. 122–132, 2009, doi: 10.1016/j.neuropharm.2008.06.075.
[72] E. A. West, T. M. Moschak, and R. M. Carelli, “Distinct functional microcircuits in the nucleus accumbens underlying goal-directed decision-making,” in Goal-Directed Decision Making: Computations and Neural Circuits, 2018, pp. 199–219. doi: 10.1016/B978-0-12-812098-9.00009-7.
[73] B. Fischer, Looking for learning: Auditory, visual and optomotor processing of children with learning problems. 2007. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060240537&partnerID=40&md5=1d722f561e47ac7fe0cbbe4cdac014da
[74] J.-H. Baik, “Stress and the dopaminergic reward system,” Exp. Mol. Med., vol. 52, no. 12, pp. 1879–1890, 2020, doi: 10.1038/s12276-020-00532-4.
[75] E. Izzo, P. P. Sanna, and G. F. Koob, “Impairment of dopaminergic system function after chronic treatment with corticotropin-releasing factor,” Pharmacol. Biochem. Behav., vol. 81, no. 4, pp. 701–708, 2005, doi: 10.1016/j.pbb.2005.04.017.
[76] Y. Munakata and J. Pfaffly, “Hebbian learning and development,” Dev. Sci., vol. 7, no. 2, pp. 141–148, 2004, doi: 10.1111/j.1467-7687.2004.00331.x.
[77] C. Mulert, “Simultaneous EEG and fMRI: Towards the characterization of structure and dynamics of brain networks,” Dialogues Clin. Neurosci., vol. 15, no. 3, pp. 381–386, 2013, doi: 10.31887/dcns.2013.15.3/cmulert.
[78] R. F. Ahmad, A. S. Malik, N. Kamel, F. Reza, and A. H. Abdul Karim, “Optimization and development of concurrent EEG-fMRI data acquisition setup for understanding neural mechanisms of brain,” in Conference Record - IEEE Instrumentation and Measurement Technology Conference, 2015, pp. 476–481. doi: 10.1109/I2MTC.2015.7151314.
[79] L. Yu and J. Xu, “The Development of Multisensory Integration at the Neuronal Level,” in Advances in Experimental Medicine and Biology, vol. 1437, 2024, pp. 153–172. doi: 10.1007/978-981-99-7611-9_10.
[80] X. Xu, I. L. Hanganu-Opatz, and M. Bieler, “Cross-Talk of Low-Level Sensory and High-Level Cognitive Processing: Development, Mechanisms, and Relevance for Cross-Modal Abilities of the Brain,” Front. Neurorobot., vol. 14, 2020, doi: 10.3389/fnbot.2020.00007.
[81] M. K. Shaleh Md Asari, N. M. Suaib, M. H. Abd Razak, M. A. Ahmad, and N. M. K. Shaleh, “Empowering Skill-Based Learning with Augmented Reality and Virtual Reality: A Case Study,” in Digest of Technical Papers - IEEE International Conference on Consumer Electronics, 2024, pp. 225–229. doi: 10.1109/ISCT62336.2024.10791270.
[82] I. Firsova, D. Vasbieva, and Y. Firsov, “Immersive Virtual Reality Technology for Teaching Marketing in Higher Education,” in Lecture Notes in Networks and Systems, 2024, pp. 308–328. doi: 10.1007/978-3-031-76800-2_21.
[83] E. G. G. Verdaasdonk, L. P. S. Stassen, M. P. Schijven, and J. Dankelman, “Construct validity and assessment of the learning curve for the SIMENDO endoscopic simulator,” Surg. Endosc. Other Interv. Tech., vol. 21, no. 8, pp. 1406–1412, 2007, doi: 10.1007/s00464-006-9177-5.
[84] D. E. Mayasari and Merline Eva Lyanthi, “Rasio Legis Hukum Waris Adat Bali Seorang Ahli Waris Yang Pindah Agama,” J. Chem. Inf. Model., vol. 53, no. February, p. 2021, 2021, [Online]. Available: https://doi.org/10.1080/09638288.2019.1595750%0Ahttps://doi.org/10.1080/17518423.2017.1368728%0Ahttp://dx.doi.org/10.1080/17518423.2017.1368728%0Ahttps://doi.org/10.1016/j.ridd.2020.103766%0Ahttps://doi.org/10.1080/02640414.2019.1689076%0Ahttps://doi.org/
[85] K. Yoshida, F. Hirai, and I. Miyaji, “Learning system using simple electroencephalograph feedback effect during memory work,” in Procedia Computer Science, 2014, pp. 1596–1604. doi: 10.1016/j.procs.2014.08.243.
[86] M. Bisla and R. S. Anand, “Wearable EEG technology for the brain-computer interface,” in Computational Intelligence in Healthcare Applications, 2022, pp. 137–155. doi: 10.1016/B978-0-323-99031-8.00005-3.
[87] E. H. Jacobs, “Neurofeedback treatment of two children with learning, attention, mood, social, and developmental deficits,” J. Neurother., vol. 9, no. 4, pp. 55–70, 2006, doi: 10.1300/J184v09n04_06.
[88] S. Franklin-Guy and D. Schnorr, “A review of the use of neurofeedback training as an intervention method in the treatment of AD/HD,” Int. J. Learn. Divers. Identities, vol. 20, no. 4, pp. 51–57, 2014, doi: 10.18848/2327-0128/CGP/v20i04/48588.