مقایسه ی میزان فعالیت مغزی در زمان ارائه ی تصاویر دو بعدی و سه بعدی در دانش آموزان با هوش فضایی بالا و پایین

نوع مقاله: مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد روانشناسی، دانشگاه آزاد واحد گرمسار، ایران.

2 دانشجو دکتری روانشناسی، دانشگاه آزاد اسلامی واحد بوشهر، ایران

3 استادیار گروه سنجش و اندازه گیری، مرکز تحقیقات علوم رفتاری، انیستیتوی سبک زندگی، دانشگاه علوم پزشکی بقیه الله، تهران، ایران.

چکیده

هدف پژوهش حاضر، مقایسه ی فعالیت مغزی دانش آموزان دبیرستانی، در زمان آموزش نحوه ی عملکرد قلب، از طریق ویدئوهای کامپیوتری است. در یکی از ویدئوها تصاویر آموزشی دو بعدی و در ویدئوی دیگر تصاویر سه بعدی (15 تصویر) قابل رویت بود. این پژوهش به لحاظ دستکاری متغیر مستقل، نیمه آزمایشی محسوب می شود. در این پژوهش متغیر مستقل فعال بعد تصاویر ارائه شده و متغیر مستقل هویتی، هوش فضایی (بالا و پایین) دانش آموزان بود. جامعه ی مورد مطالعه کلیه ی دانش آموزان دبیرستانی رشته ی تجربی، شهرستان بردسکن اند که در سال تحصیلی 97-96 ثبت نام کرده اند. از این جامعه 50 نفر با هوش فضایی بالا و 50 نفر با هوش فضایی پایین (در هرگروه 25 نفر زن و 25 نفر مرد) به روش نمونه گیری خوشه ای انتخاب شدند. امواج مغزی دانش آموزان از طریق دستگاه EEG از نقاط مختلف مغز به دست آمد. داده های نهایی بعد از حذف نویز و آرتیفکت ها، با تکنیک تحلیل واریانس دو راهه تحلیل شدند. نتایج نشان داد که تفاوت معناداری در میزان فعالیت مغزی دانش آموزان با هوش فضایی بالا و پایین، وجود ندارد(p value>0.05). این موضوع در مورد سطوح مختلف ابعاد تصاویر (دو بعد و سه بعد) و همچنین تعامل هوش فضایی و ابعاد تصاویر صادق است. یافته های جانبی نشان می دهند که میزان فعالیت مغزی دانش آموزان وابسته به جنسیت است(p value<0.008)، از طرفی جنسیت با نوع تصاویر ارائه شده نیز تعامل معنادار دارد (p value<0.01).

کلیدواژه‌ها

موضوعات


Baddeley, A. D., & Hitch, G. (1974). Working memory. In G. A. Bower (Ed.), Recent Advances in Learning and Motivation (8th ed., pp. 47–90). New York: Academic Press.

Barone, D. A. C., Maron, G., & Ramos, E. de A. (2012). Measuring the differences between Spatial Intelligence in different individuals using Lyapunov Exponents. In 7th International Conference on Mass Data Analysis of Images and signals. Retrieved from http://www.mda-signals.de/BestPaper/ MDA2012_35. pdf

Başar, E. (1999). Brain Function and Oscillations: Integrative brain function. Neurophysiology and cognitive processes. Springer.

Doppelmayr, M., Klimesch, W., Stadler, W., Pöllhuber, D., & Heine, C. (2002). EEG alphapower and intelligence. Intelligence, 30(3), 289–302. Retrieved from http://www.sciencedirect.com/science/article /pii/S0160289601001015

Gardner, H. (1983). Frames of mind. The theory of multiple intelligences. New York: BasicBooks.

Gardner, H. (1999). Intelligence Reframed: Multiple Intelligences for the Twenty-first Century (p. 292). New York: Basic Books. Retrieved from http://books.google.com/books?id=nOHsjJZB0J8C&printsec =frontcover&dq=In tellige nce+Refra med.+Multiple+intelligences+for+the+21s t+century&hl=en&sa =X&ei=QUjaUY3WNYHJygHgiYGIDw&ved=0CC8Q6AEwAA#v=onepage&q=“spatialintelligence”&f=false

Garg, A., Norman, G. R., Spero, L., & Maheshwari, P. (1999). Do virtual computer model hinder anatomy learning? Academic Medicine, 74(10), 87–89. Retrieved from http://journals.lww.com/ academicmedicine/Abstract/1999/10000/Do_virtual_computer_models_hinder_anatomy.49.aspx104

Gerě, I., & Jaušcvec, N. (2001). Differences in EEG Power and Coherence Measures Related to the Type of Presentation: Text versus Multimedia. Journal of Educational Computing Research, 25(2), 177–195. Retrieved from   http://baywood.metap ress.com/media/p3d6f5hcbp6jyh910gur/contributions/y/d/w/y/ ydwyu3fj4ly4lynd. pdf

Gevins, A., & Schaffer, R. E. (1980). A critical review of electroencephalographic EEG correlates of higher cortical function. CRC Critical Reviews in Bioengineering, 4, 113–164.

Gregoriou, G. G., Gotts, S. J., Zhou, H., & Desimone, R. (2009). High-Frequency, LongRange Coupling Between Prefrontal and Visual Cortex During Attention. Science, 324(5930), 1207–1210. Retrieved from http://psych.stanford.edu/~ jlm/pdfs/GregouriouGottsZhouDesimone_Coupling.pdf

Haier, R. J., Siegel, B., Tang, C., Abel, L., & Buchsbaum, M. S. (1992). Intelligence and changes in regional cerebral glucose metabolic rate following learning. Intelligence, 16(3–4), 415–426. Retrieved from http://www.sciencedirect.com/science/article/pii/016028969290018M 105

Höffler, T. N. (2010). Spatial Ability: Its Influence on Learning with Visualizations—a Meta-Analytic Review. Educational psychology review, 22, 245–269. Retrieved from http://www.springerlink.com /content/m75728122768j6x4/fulltext.pdf

Huk, T. (2006). Who benefits from learning with 3D models? the case of spatial ability.Journal of computer assisted learning, 22, 392–404. Retrieved from http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2729.2006.00 180.x/pdf

Joseph, J. H., & Dwyer, F. M. (1984). The effects of prior knowledge, presentation mode, and visual realism on student achievement. The Journal of Experimental Education, 52(2), 110–121. Retrieved from http://www.jstor.org/stable/20151533 106

 Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Research Reviews, 29, 169–195.  Retrieved from http://www.physics3110 .org/images/Foley_Article.pdf

Kozhevnikov, M., Motes, M. A., & Hegarty, M. (2007). Spatial visualization in physics problem solving. Cognitive Science, 31(4), 549–79. Retrieved from http://o nlinelibrary.wiley.com/doi/ 10.1080/15326900701399897/full

Krasny, K. A., Sadoski, M., & Paivio, A. (2007). Unwarranted Return: A Response to McVee, Dunsmore, and Gavelek’s (2005) Schema Theory Revisited’'. Review of 107 Education Research, 77(2), 239–244. Retrieved from http://rer.sagepub.com/cont ent/77/2/239.full.pdf

Lei, S., & Roetting, M. (2011). Influence of Task Combination on EEG Spectrum Modulation for Driver Workload Estimation. Human Factors, 53(2), 168–179. Retrieved from http://intl-hfs.sagepub.com/ content/53/2/168.full#ref-36

Liu, T., Shi, J., Zhao, D., & Yang, J. (2008). The relationship between EEG band power, cognitive processing and intelligence and in school-age children. Psychology Science Quarterly, 50(2), 259–268. Retrieved from http://www.psychologieak tuell.com/fileadmin/download/PschologyScience/2-2008/11_

Liu.pdf

Lopes da Silva, F. H. ., Vos, J. E. ., Mooibreck, J. ., & Van Rotterdam, A. . (1980). Relative contributions of intracortical and thalamocortical processes in the generation of alpha rhythms, revealed by partial coherence analysis. Electroencephalography and Clinical Neurophysiology, 50, 449–456. Retrieved from http://www.sciencedirect.com/science/article/pii/0013469480900115#

Markham, J. A., & Greenough, W. T. (2004). Experience-driven brain plasticity: beyond the synapse. Neuron Glia Biology, 1(4), 351–363. Retrieved from http://www.ncbi.nlm.nih.go v/pmc/articles/PMC1550735/

Mayer, R. E., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93(1), 187–198. doi:10.1037//0022-0663.93.1.187

Mayer, R. E., & Moreno, R. (2002). Animation as an Aid to Multimedia Learning. Educational Psychology Review, 14(1), 87–100. Retrieved from http://sciencevi ew.berkeley.edu/research/agents/ 02.Mayer. Moreno.EPR.pdf

Miller, G. A. (1956). The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information. The Psychological Review, 63, 81–97. Retrieved from  http://www.musanim .com/miller1956/

Neubauer, A. C., & Freudenthaler, H. H. (1995). Intelligence and spatiotemporalpatterns of event-related desynchronization (ERD). Intelligence, 20(3), 249–266. Retrieved from http://www.sciencedirect .com/science/article /pii/0160289695900101

Orion, N., Ben-Chaim, D., & Kali, Y. (1997). Relationship between earth-science education and spatial visualization. Journal of Geoscience Education, 45, 129–132. Retrieved from http://stwww.weizman n.ac.il/menu/publications/ea rth/a6_whole .pdf

Paivio, A. (1986a). Dual coding theory. Psychology, (1991), 8–9.

Paivio, A. (1986b). Mental representations: A dual coding approach. Oxford, England: Oxford University Press. 110

Paivio, A. (1991). Dual coding theory: Retrospect and current status. Canadian Journal of Psychology, 45, 255–287.

Parasuraman, R., & Rizzo, M. (2006). Neuroergonomics: The Brain at Work, Volume 195177614. (R. Parasuraman & M. Rizzo, Eds.). Oxford University Press.

Park, G., Lubinski, D., & Benbow, C. P. (2010). Recognizing Spatial Intelligence. Scientific American. Retrieved from http://www.scientificamerican.com /article .cfm?id=recognizing-spatial-intel

Schmid, R. G., Tirsch, W. S., & Scherb, H. (2002). Correlation between spectral EEG parameters and intelligence test variables in school-age children. Clinical Neurophysiology, 113(10), 1647–1656. Retrieved from  http://www.clin phjournal.com/article/S1388-2457(02)00212-2/abstract

Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84(1), 1–66. Retrieved from http://psycnet.apa.org/journals/rev/84/1/1.pdf

Smith, M. E., Gevins, A., Brown, H., Karnik, A., & Du, R. (2001). Monitoring task load with multivariate EEG measures during complex forms of human-computer interaction. Human Factors, 43, 366–380. Retrieved from http://hfs.sag epub.com/content/43/3/366.full.pdf

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257–285. Retrieved from http://dcom.arch.gatech.edu/old /Coa6763/Readings/sweller-88a.pdf

Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology review, 10(3), 251–296. Retrieved from  https://files.nyu.edu/jpd2 47/public/2251/readings/sw eller_cog_arch.pdf

Taubert, M., Draganski, B., Anwander, A., Müller, K., Horstmann, A., Villringer, A., & Ragert, P. (2010). Dynamic Properties of Human Brain Structure: Learning-Related Changes in Cortical Areas and Associated Fiber Connections. The Journal of Neuroscience, 30(35), 11670–11677. Retrieved from http://www.jneuro sci.org/cont ent/3 0/35/11670.full.pdf#page=1&view=FitH

Trindade, J., Fiolhais, C., & Almeida, L. (2002). Science learning in virtual environments: a descriptive study. British Journal of Educational Technology, 33(4), 471–488. Retrieved from http://onlinelibrary.wiley.com/doi/10.1111/1467- 8535.00283/abstract

Vandenberg, S. G., & Kuse, A. R. (1978). Mental rotations, a group test of threedimensional spatial abilities: A meta-analysis and consideration of critical variables. Perceptual and Motor Skills, 47(2), 599–604. Retrieved from http://www.amsciepub.com/doi/abs/10.2466/pms.1978.47.2.599