研究生: |
黃聖翔 Huang. Sheng-Siang |
---|---|
論文名稱: |
以事件相關電位比較台灣高中生函數問題及乘法問題之差異 Comparisons of Taiwanese high school students’ cognitive behaviors and ERP brain activities between function problems and multiplication problems |
指導教授: |
許慧玉
Hsu, Hui-Yu |
口試委員: |
鄭英豪
Cheng, Ying-Hao 陳建誠 Cheng, Jian-Cheng |
學位類別: |
碩士 Master |
系所名稱: |
竹師教育學院 - 數理教育研究所 Graduate Institute of Mathematics and Science Education |
論文出版年: | 2022 |
畢業學年度: | 110 |
語文別: | 中文 |
論文頁數: | 98 |
中文關鍵詞: | 事件相關腦電位 、數學函數測驗 、數學乘法測驗 、高中生 、題目真偽 |
外文關鍵詞: | Event-related potential(ERP) |
相關次數: | 點閱:2 下載:0 |
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本研究以事件相關電位(Event-related potential,ERP)技術探究臺灣高中生函數問題及乘法問題之認知行為差異以及腦波差異,取樣163名新竹地區十至十二年級高中生為研究對象,分別施測函數問題以及乘法計算問題,並將題目分為真偽(題目本身答案為正確或錯誤),再進行變異數分析,分別分析腦波帽中64個電極、逐一統計分析,以探討在不同難度的測驗間或題目本身的真偽間是否會造成腦波表現的差別,且探討行為表現與腦波表現差異,認知行為部份探討答對率以及答對所需的反應時間;腦波部份則探討振幅差異,以及造成振幅差異之題目是否要成延遲性之影響。
研究結果發現:(1)在行為表現測驗統計乘法測驗的答對率平均為90.665%,反應時間乘法測驗的反應時間平均數為1110.124毫秒,函數測驗的反應時間平均數為1744.23毫秒,兩測驗於答對率及反應時間均達顯著差異。(2)乘法真題答對率平均為92.209%,乘法偽題答對率平均為89.121%,乘法真題反應時間平均數為1060.575毫秒,乘法偽題反應時間平均數為1161.701毫秒,函數真題答對率為63.865%,函數偽題答對率為73.415%,函數真題平均反應時間為1971..323毫秒,函數偽題反應時間的平均數為1556.618毫秒,兩測驗題目真偽不論是反應時間或答對率也都達到顯著差異。(3)在P100中兩個測驗達到顯著差異的電極有48個電極,沒有在乘法測驗中因選項錯誤或正確造成顯著差異的電極,在函數測驗中因選項錯誤或正確造成顯著差異的電極有2個。在P200中兩個測驗達到顯著差異的電極有58個電極,在乘法測驗中因選項錯誤或正確造成顯著差異的電極有1個,在函數測驗中因選項錯誤或正確造成顯著差異的電極有3個。在N270中兩個測驗達到顯著差異的電極有50個電極,沒有在乘法測驗中因選項錯誤或正確造成顯著差異的電極,在函數測驗中因選項錯誤或正確造成顯著差異的電極有1個。在P300中兩個測驗達到顯著差異的電極有50個電極,在乘法測驗中因選項錯誤或正確造成顯著差異的電極有5個,在函數測驗中因選項錯誤或正確造成顯著差異的電極有12個。在N400中兩個測驗達到顯著差異的電極有53個電極,在乘法測驗中因選項錯誤或正確造成顯著差異的電極有1個,在函數測驗中因選項錯誤或正確造成顯著差異的電極有4個。
In this study, we used the Event-related potential (ERP) technique to investigate the cognitive behavioral differences and brainwave differences of complex function problems and simple multiplication problems among high school students in Taiwan. 163 high school students in grades 10-12 in Hsinchu were sampled, and the function problems and multiplication problems were administered separately. The questions were classified as true or false (correct or incorrect answers), and the variance analysis was conducted to analyze the 64 electrodes in the brainwave cap, one by one, to investigate whether the difference in brainwave performance was caused between different levels of difficulty or between true and false questions, and to investigate the difference in behavioral performance and brainwave performance, and to investigate the correct response rate and the response time required for correct answers in the cognitive behavior section and the amplitude in the brainwave section.
張玟溢(2020)。臺灣、美國、新加坡國中函數主題教材之比較研究。國立嘉義大學數理教育研究所碩士論文,嘉義市。 取自https://hdl.handle.net/11296/ufkmbj
Ansari, D., & Lyons, I. M. (2016). Cognitive neuroscience and mathematics learning: how far have we come? Where do we need to go? ZDM, 48(3), 379-383.
Badre, D., & Wagner, A. D. (2007). Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia, 45(13), 2883-2901.
Byrnes, J. P., & Fox, N. A. (1998). The educational relevance of research in cognitive neuroscience. Educational Psychology Review, 10(3), 297-342.
Czigler, I., Balázs, L., & Winkler, I. (2002). Memory-based detection of task-irrelevant visual changes. Psychophysiology, 39(6), 869-873
Danker, J. F., & Anderson, J. R. (2007). The roles of prefrontal and posterior parietal cortex in algebra problem solving: A case of using cognitive modeling to inform neuroimaging data. Neuroimage, 35(3), 1365-1377.
De Smedt, B., Ansari, D., Grabner, R. H., Hannula, M. M., Schneider, M., & Verschaffel, L. (2010). Cognitive neuroscience meets mathematics education. Educational Research Review, 5(1), 97-105.
Deary, I. J., & Caryl, P. G. (1997). Neuroscience and human intelligence differences. Trends in Neurosciences, 20(8), 365-371.
Dehaene, S., Molko, N., Cohen, L., & Wilson, A. J. (2004). Arithmetic and the brain. Current opinion in neurobiology, 14(2), 218-224.
Dehaene, S., Piazza, M., Pinel, P., & Cohen, L. (2003). Three parietal circuits for number processing. Cognitive neuropsychology, 20(3-6), 487-506.
Donchin, E. (1981). Surprise!… surprise? Psychophysiology, 18(5), 493-513
Domahs, F., Domahs, U., Schlesewsky, M., Ratinckx, E., Verguts, T., Willmes, K., & Nuerk, H. C. (2007). Neighborhood consistency in mental arithmetic: Behavioral and ERP evidence. Behavioral and Brain Functions, 3(1), 1-13.
Frey, M. C., & Detterman, D. K. (2004). Scholastic assessment or g? The relationship between the scholastic assessment test and general cognitive ability. Psychological science, 15(6), 373-378.
Gevins, A., & Smith, M. E. (2000). Neurophysiological measures of working memory and individual differences in cognitive ability and cognitive style. Cerebral cortex, 10(9), 829-839.
Grenier, A. E., Dickson, D. S., Sparks, C. S., & Wicha, N. Y. (2020). Meaning to multiply: Electrophysiological evidence that children and adults treat multiplication facts differently. Developmental Cognitive Neuroscience, 46, 100873.
Griffiths, O., Le Pelley, M. E., Jack, B. N., Luque, D., & Whitford, T. J. (2016). Cross‐modal symbolic processing can elicit either an N2 or a protracted N2/N400 response. Psychophysiology, 53(7), 1044-1053.
Hillyard, S. A., & Anllo-Vento, L. (1998). Event-related brain potentials in the study of visual selective attention. Proceedings of the National Academy of Sciences, 95(3), 781-787.
Jaušovec, N., & Jaušovec, K. (2004). Differences in induced brain activity during the performance of learning and working-memory tasks related to intelligence. Brain and Cognition, 54(1), 65-74.
Jeffreys, D. (1989). A face-responsive potential recorded from the human scalp.Experimental brain research, 78(1), 193-202.
Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence. Behavioral and brain sciences, 30(2), 135.
Krutetskii, V. A., WIRSZUP, I., & Kilpatrick, J. (1976). The psychology of mathematical abilities in schoolchildren: University of Chicago Press.
Kutas, M., & Federmeier, K. D. (2011). Thirty years and counting: finding meaning in the N400 component of the event-related brain potential (ERP). Annual review of psychology, 62, 621-647.
Leikin, M., Paz-Baruch, N., & Leikin, R. (2013). Memory abilities in generally gifted and excelling-in-mathematics adolescents. Intelligence, 41(5), 566-578.
Leikin, M., Waisman, I., & Leikin, R. (2013). How brain research can contribute to the evaluation of mathematical giftedness. Psychological Test and Assessment Modeling, 55(4), 415.
Leikin, R. (2009). Bridging research and theory in mathematics education with research and theory in creativity and giftedness. In Creativity in mathematics and the education of gifted students (pp. 383-411): Brill Sense.
Leikin, R. (2014). Giftedness and high ability in mathematics. Encyclopedia of mathematics education, 247-251.
Leikin, R., Waisman, I., & Leikin, M. (2016). Does solving insight-based problems differ from solving learning-based problems? Some evidence from an ERP study. ZDM, 48(3), 305-319.
Lev, M., & Leikin, R. (2013). The connection between mathematical creativity and high ability in mathematics. Paper presented at the Proceedings of the Eight Congress of the European Society for Research in Mathematics Education (CERME8).
Luck, S. J. (2014). An introduction to the event-related potential technique: MIT press.
Luck, S. J., & Hillyard, S. A. (1994). Spatial filtering during visual search: evidence from human electrophysiology. Journal of Experimental psychology: Human perception and performance, 20(5), 1000.
Neubauer, A. C., Fink, A., & Schrausser, D. G. (2002). Intelligence and neural efficiency: The influence of task content and sex on the brain–IQ relationship. Intelligence, 30(6), 515-536.
Niedeggen, M., & Rösler, F. (1999). N400 effects reflect activation spread during retrieval of arithmetic facts. Psychological Science, 10(3), 271-276.
O'Boyle, M. W. (2008). Mathematically gifted children: Developmental brain characteristics and their prognosis for well-being. Roeper Review, 30(3), 181-186.
Ponte, J. P. D. (1992). The history of the concept of function and some educational implications. The Mathematics Educator, 3-8.
Prieto-Corona, B., Rodríguez-Camacho, M., Silva-Pereyra, J., Marosi, E., Fernández, T., & Guerrero, V. (2010). Event-related potentials findings differ between children and adults during arithmetic-fact retrieval. Neuroscience letters, 468(3), 220-224.
Raven, J., Court, J., & Raven, J. C. (1998). Manual for Raven's progressive matrices and vocabulary scales.
Renzulli, J. S. (1978). What makes giftedness? Reexamining a definition. Phi Delta Kappan, 60(3), 180.
Renzulli, J. S. (2005). Applying gifted education pedagogy to total talent development for all students. Theory into practice, 44(2), 80-89.
Ruchkin, D. S., Johnson Jr, R., Mahaffey, D., & Sutton, S. (1988). Toward a functional categorization of slow waves. Psychophysiology, 25(3), 339-353
Santens, S., Roggeman, C., Fias, W., & Verguts, T. (2010). Number processing pathways in human parietal cortex. Cerebral cortex, 20(1), 77-88.
Smith, J. P., van den Heuvel-Panhuizen, M., & Teppo, A. R. (2011). Learning, teaching, and using measurement: introduction to the issue. In: Springer.
Spapé, M., Verdonschot, R., & Steenbergen, H. (2019). The E-Primer: An introduction to creating psychological experiments in E-Prime. Second edition updated for E-Prime 3.
Steiner, H. H., & Carr, M. (2003). Cognitive development in gifted children: Toward a more precise understanding of emerging differences in intelligence. Educational Psychology Review, 15(3), 215-246.
Terao, A., Koedinger, K. R., Sohn, M.-H., Qin, Y., Anderson, J. R., & Carter, C. S. (2004). An fMRI study of the interplay of symbolic and visuo-spatial systems in mathematical reasoning. Paper presented at the Proceedings of the Annual Meeting of the Cognitive Science Society.
Vernon, P. A. (1993). Biological approaches to the study of human intelligence: Praeger.
Vogel, E. K., Luck, S. J., & Shapiro, K. L. (1998). Electrophysiological evidence for a postperceptual locus of suppression during the attentional blink. Journal of Experimental psychology: Human perception and performance, 24(6), 1656
Waisman, I., Leikin, M., & Leikin, R. (2016). Brain activity associated with logical inferences in geometry: focusing on students with different levels of ability. ZDM, 48(3), 321-335. doi:10.1007/s11858-016-0760-5
Waisman, I., Leikin, M., Shaul, S., & Leikin, R. (2014). Brain activity associated with translation between graphical and symbolic representations of functions in generally gifted and excelling in mathematics adolescents. International Journal of Science and Mathematics Education, 12(3), 669-696.
Zohar, A. (1990). Mathematical reasoning ability: Its structure, and some aspects of its genetic transmission: Hebrew University of Jerusalem.
Zhou, X., Chen, C., Zhang, H., Chen, C., Zhou, R., & Dong, Q. (2007). The operand-order effect in single-digit multiplication: An ERP study of Chinese adults. Neuroscience letters, 414(1), 41-44.