Electroencephalograph Analysis of Mental Fatigue in Learning the Physics at Senior High School’s Students

  • Authors

    • Hartomo Soewardi
    • Faradhina Azzahra
    • Catur Atmaji
    2018-11-30
    https://doi.org/10.14419/ijet.v7i4.28.22612
  • The result of national examination in Senior High School students of Indonesia fluctuated for the last 3 years particularly in Yogyakarta. This examination is one of the national indicators for the achievement in the knowledge comprehension among the student on a certain subjects. Physics is a subject tested producing digression on the average score for last 3 years; 2015-2017. Some factors that contributes are learning process method, environment, subject, teacher, and student’s cognitive manner. However, latest factor has a high effect on accomplishing a success. The objective of this study is to investigate the mental fatigue of students in taking a part of teaching-learning process of Physics by analyzing the brain activity at cognitive system in 4 sessions. It is the combination of learning methods (autodidact and non-autodidact) and conditions (late morning and afternoon). An experimental study was conducted at laboratory to record beta, alpha and theta wave of brain’s recorded by electroencephalograph (EEG). Four students of Senior High School were participated in this study to attend a learning process of Physics for 90 minutes in each session. Non-parametric statistical analysis was done to test the hypothesis. The result of this study showed that the autodidact learning method in the late morning for 54.25 minutes had a better performance in learning the Physic subject.

  • References

    1. [1] Ministry of Education and Culture. (2017). Rekap Hasil Ujian Nasional (UN) Tingkat Sekolah. Retrieved from https://puspendik.kemdikbud.go.id/hasil-un/ (In Ina)

      [2] Kinantie, O. A., Hernawaty, T., & Hidayati1, N. O. (2012). Gambaran tingkat stres siswa SMAN 3 Bandung kelas XII menjelang ujian nasional 2012, 1–14. (In Ina)

      [3] Djemari, & Kartowagiran, B. K. (2009). Dampak Ujian Nasional. Universitas Negeri Yogyakarta. (In Ina)

      [4] Wascher, E., Rasch, B., S??nger, J., Hoffmann, S., Schneider, D., Rinkenauer, G., … Gutberlet, I. (2014). Frontal theta activity reflects distinct aspects of mental fatigue. Biological Psychology, 96(1), 57–65. https://doi.org/10.1016/j.biopsycho.2013.11.010

      [5] Charbonnier, S., Roy, R. N., Bonnet, S., & Campagne, A. (2016). EEG index for control operators’ mental fatigue monitoring using interactions between brain regions. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2016.01.013

      [6] Sanei, S., & Chambers, J. (2007). EEG Signal Processing. England: John Wily & Sons Ltd.

      [7] Mun, S., Kim, E., & Park, M. (2014). Effect of mental fatigue caused by mobile 3D viewing on selective attention: An ERP study. International Journal of Psychophysiology. https://doi.org/10.1016/j.ijpsycho.2014.08.1389

      [8] Chen, C., Li, K., Wu, Q., Wang, H., Qian, Z., & Sudlow, G. (2013). EEG-based detection and evaluation of fatigue caused by watching 3DTV. Displays, 34(2), 81–88. https://doi.org/10.1016/j.displa.2013.01.002

      [9] Chen, C., Wang, J., Li, K., Wu, Q., Wang, H., Qian, Z., & Gu, N. (2014). Assessment visual fatigue of watching 3DTV using EEG power spectral parameters. Displays, 35(5), 266–272. https://doi.org/10.1016/j.displa.2014.10.001

      [10] Boksem, M. A. S., Meijman, T. F., & Lorist, M. M. (2005). Effects of mental fatigue on attention: An ERP study. Cognitive Brain Research, 25(1), 107–116. https://doi.org/10.1016/j.cogbrainres.2005.04.011

      [11] Käthner, I., Wriessnegger, S. C., Müller-putz, G. R., Kübler, A., & Halder, S. (2014). Effects of mental workload and fatigue on the P300 , alpha and theta band power during operation of an ERP ( P300 ) brain – computer interface. Biological Psychology, 102, 118–129. https://doi.org/10.1016/j.biopsycho.2014.07.014

      [12] Arnau, S., Möckel, T., & Rinkenauer, G. (2017). The interconnection of mental fatigue and aging: An EEG study. International Journal of Psychophysiology. https://doi.org/10.1016/j.ijpsycho.2017.04.003

      [13] Simons, P. R. J. (1989). Learning to learn. Triburg University. Retrieved from http://igitur-archive.library.uu.nl/ivlos/2005-0622-185541/5888.pdf

      [14] Van Beek, J. A., De Jong, F. P. C. M., Minnaert, A. E. M. G., & Wubbels, T. (2014). Teacher practice in secondary vocational education: Between teacher-regulated activities of student learning and student self-regulation. Teaching and Teacher Education, 40, 1–9. https://doi.org/10.1016/j.tate.2014.01.005

      [15] Dunn, R., Beaudry, J. S., & Klavas, A. (2002). Survey of Research on Learning Styles. California Journal of Science Education, II(2), 75–98.

      [16] Babiloni, F. (2012). Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload ... Neuroscience and Biobehavioral Reviews, (August 2017). https://doi.org/10.1016/j.neubiorev.2012.10.003

      [17] Yin, Z., & Zhang, J. (2017). Cross-session classification of mental workload levels using EEG and an adaptive deep learning model. Biomedical Signal Processing and Control, 33, 30–47. https://doi.org/10.1016/j.bspc.2016.11.013

      [18] Cheng, S.-Y., & Hsu, H.-T. (2011). Mental Fatigue Measurement Using EEG.

      [19] Nishihara, N., Wargocki, P., & Tanabe, S. ichi. (2014). Cerebral blood flow, fatigue, mental effort, and task performance in offices with two different pollution loads. Building and Environment, 71, 153–164. https://doi.org/10.1016/j.buildenv.2013.09.018

      [20] Zhao, C., Zhao, M., Liu, J., & Zheng, C. (2012). Electroencephalogram and electrocardiograph assessment of mental fatigue in a driving simulator. Accident Analysis and Prevention, 45, 83–90. https://doi.org/10.1016/j.aap.2011.11.019

      [21] Soewardi, H., Anugraheni, A. R., & Shabrina, N. (2015). Analysis of Electromyography on Computer Interaction Devices to the Risk of Carpal Tunnel Syndrome. https://doi.org/10.17706/jcp.10.5.3

      [22] Vollmer, C., Pötsch, F., & Randler, C. (2013). Morningness is associated with better gradings and higher attention in class. Learning and Individual Differences, 1–7. https://doi.org/10.1016/j.lindif.2013.09.001

      [23] te Kulve, M., Schlangen, L. J. M., Schellen, L., Frijns, A. J. H., & van Marken Lichtenbelt, W. D. (2017). The impact of morning light intensity and environmental temperature on body temperatures and alertness. Physiology and Behavior, 175(March), 72–81. https://doi.org/10.1016/j.physbeh.2017.03.043

      [24] Romeijn, N., Raymann, R. J. E. M., Møst, E., Te Lindert, B., Van Der Meijden, W. P., Fronczek, R., … Van Someren, E. J. W. (2012). Sleep, vigilance, and thermosensitivity. Pflugers Archiv European Journal of Physiology, 463(1), 169–176. https://doi.org/10.1007/s00424-011-1042-2

      [25] Lodewijks, H. G. L. C. (1982). Self-Regulated versus Teacher Provided Sequencing of Information in Learning from Text. Advances in Psychology, 8, 509–520. https://doi.org/10.1016/S0166-4115(08)62715-6

      [26] Berkenbosch, F., Van Oers, J. W. A. M., Del Rey, A., Tilders, F., & Besedovsky, H. (1987). Corticotropin-releasing factor-producing neurons in the rat activated by interleukin-1. Science, 238(4826), 524-526.

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    Soewardi, H., Azzahra, F., & Atmaji, C. (2018). Electroencephalograph Analysis of Mental Fatigue in Learning the Physics at Senior High School’s Students. International Journal of Engineering & Technology, 7(4.28), 344-349. https://doi.org/10.14419/ijet.v7i4.28.22612