Main Article Content

Abstract

Background. Various teaching strategies impact cognitive functions differently. These methods influence concentration and attention, crucial for information assimilation, processing, and retrieval. This research examines the influence of lecture-based and video-based learning on primary school students' brain activities, using Quantitative Electroencephalogram (QEEG) analysis. Method. The study involved 36 children aged 10-12 years, including 17 boys and 19 girls. Quantitative Electroencephalogram (QEEG) recordings were obtained using the EMOTIV EPOC 14-Channel device. The analysis focused on the frontal, temporal, occipital region, examining delta, theta, alpha, beta, high-beta, beta-1, beta-2, and beta-3 brainwaves. These waveforms were normalized to Z-Scores for comparison. Statistical differences between groups were assessed using t-tests.Result. Post-lecturing and video-based learning, QEEG analyses revealed an enhancement in beta-2 wave activity at F3 and F7 locations. Increase beta wave, suggesting differentiated cognitive engagement patterns between the two learning modalities. Conclusion. Lecturing and video-based learning enhance cognitive engagement, evidenced by elevated alfa and beta wave activity. Lecturing elicits stronger concentration and executive function responses, positioning it as a preferred approach for tasks demanding significant verbal processing and motor planning. Meanwhile showed higher emotional expression, emotional memory, and visual processing activity.


Latar Belakang. Berbagai strategi pengajaran memengaruhi fungsi kognitif secara berbeda. Metode-metode ini memengaruhi konsentrasi dan perhatian, yang sangat penting untuk asimilasi, pemrosesan, dan pengambilan informasi. Penelitian ini mengkaji pengaruh pembelajaran berbasis ceramah dan berbasis video terhadap aktivitas otak siswa sekolah dasar, menggunakan analisis Elektroensefalogram Kuantitatif (QEEG). Metode. Studi ini melibatkan 36 anak berusia 10-12 tahun, termasuk 17 laki-laki dan 19 perempuan. Rekaman Elektroensefalogram Kuantitatif (QEEG) diperoleh menggunakan perangkat EMOTIV EPOC 14-Channel. Analisis difokuskan pada daerah frontal, temporal, dan oksipital, dengan memeriksa gelombang otak delta, theta, alpha, beta, high-beta, beta-1, beta-2, dan beta-3. Gelombang-gelombang ini dinormalisasi ke Z-Score untuk perbandingan. Perbedaan statistik antar kelompok dinilai menggunakan uji-t.Hasil. Setelah perkuliahan dan pembelajaran berbasis video, analisis QEEG mengungkapkan peningkatan aktivitas gelombang beta-2 di lokasi F3 dan F7. Peningkatan gelombang beta menunjukkan pola keterlibatan kognitif yang berbeda antara kedua modalitas pembelajaran tersebut.Kesimpulan. Perkuliahan dan pembelajaran berbasis video meningkatkan keterlibatan kognitif, dibuktikan dengan peningkatan aktivitas gelombang alfa dan beta. Perkuliahan memicu konsentrasi dan respons fungsi eksekutif yang lebih kuat, menjadikannya pendekatan yang lebih disukai untuk tugas-tugas yang membutuhkan pemrosesan verbal dan perencanaan motorik yang signifikan. Sementara itu, menunjukkan ekspresi emosional, memori emosional, dan aktivitas pemrosesan visual yang lebih tinggi.


 

Keywords

QEEG Anak Fungsi kognitif

Article Details

How to Cite
Zelvira, B., Gea Pandhita S, & Erlin Listiyaningsih. (2025). Visualizing cognitive load and mnemonic encoding: a comparative QEEG study on traditional lecturing and digital multimedia instruction. Sanus Medical Journal, 7(2), 168–188. https://doi.org/10.22236/sanus.v7i2.22409

References

  1. Adlam ALR, Patterson K, Bozeat S, Hodges JR. The Cambridge semantic memory test battery: Detection of semantic deficits in semantic dementia and alzheimers disease. Neurocase. 2010;16(3):193–207. Available from: https://doi.org/10.1080/13554790903405693
  2. Alvarez JA, Emory E. Executive function and the frontal lobes: A meta-analytic review. Neuropsychology Review. 2006;16:17–42. Available from: https://doi.org/10.1007/s11065-006-9002-x
  3. Anderson ND, Craik FIM. The mnemonic mechanisms of errorless learning. Neuropsychologia. 2006;44:2806–2813. Available from: https://doi.org/10.1016/j.neuropsychologia.2006.05.026
  4. Arenth P, Russell K, Scanlon J, Kessler L, Ricker J. Encoding and recognition after traumatic brain injury: Neuropsychological and functional magnetic resonance imaging findings. Journal of Clinical And Experimental Neuropsychology. 2012;34(4):333–344. Available from: https://doi.org/10.1080/13803395.2011.633896
  5. Carpenter SK. Cue strength as a moderator of the testing effect: The benefits of elaborative retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition. 2009;35(6):1563–1569. Available from: https://doi.org/10.1037/a0017021
  6. Carpenter SK. Semantic information activated during retrieval contributes to later retention: Support for the mediator effectiveness hypothesis of the testing effect. Journal of Experimental Psychology: Learning, Memory, and Cognition. 2011;37(6):1547–1552. Available from: https://doi.org/10.1037/a0024140
  7. Cohen M, Ylvisaker M, Hamilton J, Kemp L, Claiman B. Errorless learning of functional life skills in an individual with three aetiologies. Neuropsychological Rehabilitation. 2010;20(3):355–376. Available from: https://doi.org/10.1080/09602010903309401
  8. Crawford JR, Garthwaite PH, Sutherland D, Borland N. Some supplementary methods for the analysis of the delis–kaplan executive function system. Psychological Assessment. 2011;23:888–898. Available from: https://doi.org/10.1037/a0023712
  9. Delis D, Freeland J, Kramer J, Kaplan E. Integrating clinical assessment with cognitive neuroscience. Journal of Consulting And Clinical Psychology. 1988;56(1):123–130. Available from: https://doi.org/10.1037//0022-006x.56.1.123
  10. Delis C, Kaplan E, Kramer JH. Delis-Kaplan executive function system. PsycTESTS Dataset; 2001. Available from: https://doi.org/10.1037/t15082-000
  11. De Luca J, Schultheis MT, Madigan NK, Christodoulou C, Averill A. Acquisition versus retrieval deficits in traumatic brain injury. Archives of Physical Medicine and Rehabilitation. 2000;81(10):1327–1333. Available from: https://doi.org/10.1053/apmr.2000.9390
  12. Faul M, Wald MM, Rutland-Brown W, Sullivent EE, Sattin RW. Using a costbenefit analysis to estimate outcomes of a clinical treatment guideline. The Journal of Trauma and Acute Care Surgery. 2007;63(6):1271–1278. Available from: https://doi.org/10.1097/TA.0b013e3181493080
  13. Gifford KA, Phillips JS, Samuels LR, et al. Associations between verbal learning slope and neuroimaging markers. Journal of the International Neuropsychological Society. 2015;21(6):455–467. Available from: https://doi.org/10.1017/s1355617715000430
  14. Gillis MM, Hampstead BM. A two-part preliminary investigation of encoding-related activation changes after moderate to severe TBI. Brain Imaging and Behavior. 2015;9:801–820. Available from: https://doi.org/10.1007/s11682-014-9337-5
  15. Grimaldi PJ, Karpicke JD. When and why do retrieval attempts enhance subsequent encoding? Journal of Applied Research in Memory and Cognition. 2012;40(4):505–513. Available from: https://doi.org/10.3758/s13421-011-0174-0
  16. Haslam C, Hodder KI, Yates PJ. Errorless learning and spaced retrieval. Journal of Clinical and Experimental Neuropsychology. 2011;33:432–447. Available from: https://doi.org/10.1080/13803395.2010.533155
  17. Hildebrandt H. Cognitive Rehabilitation of Memory. Academic Press; 2019. Available from: https://doi.org/10.1016/C2018-0-00397-7
  18. Hodges JR, Patterson K. Semantic memory disorders. Trends in Cognitive Sciences. 1997;1(2):68–72. Available from: https://doi.org/10.1016/s1364-6613(97)01022-x
  19. Kornell N, Hays MJ, Bjork RA. Unsuccessful retrieval attempts enhance subsequent learning. Journal of Experimental Psychology: Learning, Memory and Cognition. 2009;35(4):989–998. Available from: https://doi.org/10.1037/a0015729
  20. Little DM, Kraus MF, et al. Thalamic integrity underlies executive dysfunction in traumatic brain injury. Neurology. 2010;74(7):558–564. Available from: https://doi.org/10.1212/WNL.0b013e3181cff5d5
  21. Lloyd J, Riley G, Powell T. Errorless learning of novel routes through a virtual town. Neuropsychological Rehabilitation. 2009;19(1):98–109. Available from: https://doi.org/10.1080/09602010802117392
  22. Lubinsky T, Rich JB, Anderson ND. Errorless learning and elaborative self-generation. Journal of the International Neuropsychological Society. 2009;15:704–716. Available from: https://doi.org/10.1017/S1355617709990270
  23. Mallas EJ, De Simoni S, et al. Abnormal dorsal attention network activation in memory impairment after TBI. Brain. 2021;144:114–127. Available from: https://doi.org/10.1093/brain/awaa380
  24. McKissock S, Ward J. Do errors matter? Errorless and errorful learning in anomic picture naming. Neuropsychological Rehabilitation. 2007;17(3):355–373. Available from: https://doi.org/10.1080/09602010600892113
  25. Mera Y, Rodríguez G, Marin-Garcia E. Unravelling the benefits of experiencing errors during learning. Psychonomic Bulletin and Review. 2022;29:753–765. Available from: https://doi.org/10.3758/s13423-021-02022-8
  26. Metcalfe J, Xu J. Learning from one’s own errors and those of others. Psychonomic Bulletin and Review. 2018;25:402–408. Available from: https://doi.org/10.3758/s13423-017-1287-7
  27. Metzler-Baddeley C, Snowden JS. Errorless versus errorful learning in Alzheimer’s disease. Journal of Clinical and Experimental Neuropsychology. 2005;27(8):1070–1079. Available from: https://doi.org/10.1080/13803390490919164
  28. Middleton EL, Schwartz MF. Errorless learning in cognitive rehabilitation: A critical review. Neuropsychological Rehabilitation. 2012;22(2):138–168. Available from: https://doi.org/10.1080/09602011.2011.639619
  29. Mikels JA, Maglio SJ, et al. Should I go with my gut? Emotion. 2011;11(4):743–753. Available from: https://doi.org/10.1037/a0023986
  30. Nasreddine Z, Phillips N, et al. The Montreal cognitive assessment, MoCA. Journal of The American Geriatrics Society. 2005;53(4):695–699. Available from: https://doi.org/10.1111/j.1532-5415.2005.53221.x
  31. Nettelbeck T, Rabbitt P, et al. Uncoupling learning from initial recall. British Journal of Psychology. 1996;87(4):593–607. Available from: https://doi.org/10.1111/j.2044-8295.1996.tb02610.x
  32. Novack TA, Bush BA, et al. Outcome after traumatic brain injury. Archives of Physical Medicine and Rehabilitation. 2001;82(3):300–305. Available from: https://doi.org/10.1053/apmr.2001.18222
  33. Panwar N, Purohit D, et al. Evaluation of neurocognitive functions in TBI patients using MoCA. Asian Journal of Psychiatry. 2019;41:60–65. Available from: https://doi.org/10.1016/j.ajp.2018.08.007
  34. Pitel AL, Beaunieux H, et al. Two case studies in the application of errorless learning techniques. Brain Injury. 2006;20:1099–1110. Available from: https://doi.org/10.1080/02699050600909961
  35. Polinder S, Cnossen MC, et al. A multidimensional approach to post-concussion symptoms. Frontiers in Neurology. 2018;9:1113. Available from: https://doi.org/10.3389/fneur.2018.01113
  36. Shah SA, Goldin Y, et al. Executive attention deficits after TBI reflect impaired recruitment of resources. NeuroImage: Clinical. 2017;14:233–241. Available from: https://doi.org/10.1016/j.nicl.2017.01.010
  37. Shao Z, Janse E, et al. What do verbal fluency tasks measure? Frontiers in Psychology. 2014;5. Available from: https://doi.org/10.3389/fpsyg.2014.00772
  38. Skidmore ER. Training to optimize learning after traumatic brain injury. Current Physical Medicine and Rehabilitation Reports. 2015;3(2):99–105. Available from: https://doi.org/10.1007/s40141-015-0081-6
  39. Slamecka NJ, Graf P. The generation effect: Delineation of a phenomenon. Journal of Experimental Psychology: Human Learning and Memory. 1978;4(6):592–604. Available from: https://doi.org/10.1037/0278-7393.4.6.592
  40. Sohlberg MM, McLaughlin KA, et al. Evaluation of attention process training in persons with TBI. Journal of Clinical and Experimental Neuropsychology. 2000;22(5):656–676. Available from: https://doi.org/10.1076/1380-3395(200010
  41. Soraci SA Jr, Franks JJ, et al. Incongruous item generation effects. Journal of Experimental Psychology: Learning, Memory and Cognition. 1994;20(1):67–78. Available from: https://doi.org/10.1037/h0080017
  42. Vakil E, Greenstein Y, et al. The effects of TBI on episodic memory: A meta-analysis. Neuropsychology Review. 2019;29(3):270–287. Available from: https://doi.org/10.1007/s11065-019-09413-8
  43. Vannest J, Eaton KP, et al. Cortical correlates of self-generation in verbal paired associate learning. Brain Research. 2012;1437:104–114. Available from: https://doi.org/10.1016/j.brainres.2011.12.020
  44. Visser MAL, Lambon-Ralph MA. Differential contributions of bilateral ventral anterior temporal lobe. Journal of Cognitive Neuroscience. 2011;23(10):3121–3131. Available from: https://doi.org/10.1162/jocn_a_00007
  45. Wechsler Memory Scale-Fourth Edition. PsycTESTS dataset; 2009. Available from: https://doi.org/10.1037/t15175-000
  46. Wilson BA, Baddeley A, et al. Errorless learning in the rehabilitation of memory impaired people. Neuropsychological Rehabilitation. 2010;4(3):307–326. Available from: https://doi.org/10.1080/09602019408401463
  47. Wright MJ, Schmitter-Edgecombe M. The impact of verbal memory encoding and consolidation deficits during recovery from TBI. Journal of Head Trauma Rehabilitation. 2011;26(3):182–191. Available from: https://doi.org/10.1097/HTR.0b013e318218dcf9
  48. Yonelinas AP. The nature of recollection and familiarity. Journal of Memory and Language. 2002;46(3):441–517. Available from: https://doi.org/10.1006/jmla.2002.2864
  49. Zawadzka K, Hanczakowski M. Two routes to memory benefits of guessing. Journal of Experimental Psychology: Learning. Memory, and Cognition. 2019;45(10):1748–1760. Available from: https://doi.org/10.1037/xlm0000676
  50. Breitenstein C, Grewe T, et al. Intensive speech and language therapy in patients with chronic aphasia after stroke. The Lancet. 2017;389(10078):1528–1538. Available from: https://doi.org/10.1016/S0140-6736(17)30067-3
  51. Bugli C, Lambert P. Comparison between principal component analysis and independent component analysis. Biomedical Journal. 2006;49:312–327. Available from: https://doi.org/10.1002/bimj.200510285
  52. Goucha T, Emiliano Z, Friederici AD. A revival of Homo Loquens as a builder of labeled structures. Neuroscience & Biobehavioral Reviews. 2017;81:213–224. Available from: https://doi.org/10.1016/j.neubiorev.2017.01.036
  53. Grundy J, Anderson J, Bialystok E. Bilinguals have more complex EEG brain signals in occipital regions. NeuroImage. 2017;159:280–288. Available from: https://doi.org/10.1016/j.neuroimage.2017.07.063
  54. Gurumoorthy S, et al. Epilepsy analysis using open source EDF tools. International Journal of Communication Systems. 2020;33(13):e4095. Available from: https://doi.org/10.1002/dac.4095
  55. Haufe S, et al. Electrophysiology-based detection of emergency braking intention in real-world driving. Journal of Neural Engineering. 2014;11(5):056011. Available from: https://doi.org/10.1088/1741-2560/11/5/056011
  56. Hebb AO, Ojemann GA. The thalamus and language revisited. Brain and Language. 2013;126(1):99–108. Available from: https://doi.org/10.1016/j.bandl.2012.06.010
  57. Jamil N, Belkacem AN, et al. Noninvasive EEG equipment for brain-computer interfaces: A systematic review. Sensors. 2021;21(14):4754. Available from: https://doi.org/10.3390/s21144754
  58. Kang J, Ojha A, Lee M. Development of intelligent learning tool for improving foreign language skills. HAI '15. 2015:53–56. Available from: https://doi.org/10.1145/2814940.2814951
  59. Kawala-Sterniuk A, et al. Comparison of smoothing filters in analysis of EEG data. Sensors. 2020;20(3):807. Available from: https://doi.org/10.3390/s20030807
  60. Rashid M, et al. Current status, challenges, and possible solutions of EEG-based brain-computer interface. Frontiers in Neurorobotics. 2020;14:25. Available from: https://doi.org/10.3389/fnbot.2020.00025
  61. Rosenfeld JV, Wong YT. Neurobionics and the brain-computer interface. The Medical Journal of Australia. 2017;206(8):363–368. Available from: https://doi.org/10.5694/mja16.01011
  62. Schultz T, et al. Biosignal-based spoken communication: A survey. IEEE/ACM Transactions on Audio, Speech, and Language Processing. 2017;25(12):2257–2271. Available from: https://doi.org/10.1109/TASLP.2017.2752365
  63. Werker JF, Hensch TK. Critical periods in speech perception: New directions. Annual Review of Psychology. 2015;66(1):173–196. Available from: https://doi.org/10.1146/annurev-psych-010814-015104
  64. Xiang H, et al. The structural connectivity underpinning language aptitude, working memory, and IQ. Language Learning. 2012;62:110–130. Available from: https://doi.org/10.1111/j.1467-9922.2012.00708.x