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(1)37. 國立政治大學「教育與心理研究」 2015 年 9 月,38 卷 3 期,頁 37-69 DOI. 10.3966/102498852015093803002. 以多元智能量表探究音樂與數學中的時空 推理能力 吳璧純*. 摘. 要. 本研究關注音樂與數學能力關係。以Howard Gardner多元智能理論之量表為主 要工具,並以新竹國小三年級與五年級學生83位為樣本,探討多元智能之間的關 係、音樂智能與數學智能、音樂智能與時空推理能力,以及樂理成績與數學及時空 推理能力的關係。另外,以音樂學習經驗相關變項,例如,是否為音樂班、是否會 樂器、學習樂器時間長短、是否參加過合唱團、是否學過認譜等,利用線性迴歸預 測樂理成績,也預測時空推理能力。研究結果指出:一、八種智能之間有顯著中度 正相關。二、音樂智能與數學智能之間有中度相關,但其相關可能源於時空推理能 力。三、樂理與數學智能以及時空推理有低度顯著相關,且其與數學智能之間的相 關可能源於時空推理能力。四、「音樂班學生」最能預測樂理成績,解釋變異量 達 .75。五、「會樂器」最能預測時空推理能力,其解釋變異量卻只有 .18。最後 針對樂理知識與時空推理能力關係之探究、量表、音樂教育取向之探討提出未來研 究之建議。 關鍵詞: 多元智能、音樂教育、音樂與數學關係、時空推理能力、莫札特效應 *. 吳璧純:國立臺北大學師資培育中心教授 電子郵件:[email protected] 收件日期:2014.07.30;修改日期:2015.01.13;接受日期:2015.03.19.

(2) 38. Journal of Education & Psychology September, 2015, Vol. 38 No. 3, pp. 37-69. To Explore the Relationship of Temporalspatial Reasoning Between Music and Mathematics by an Inventory based on the Multiple Intelligence Theory Pi-Chun Wu*. Abstract. This study focuses on the relationship of people's music and math ability. To explore the relationships among multiple intelligences, between music intelligence and mathematical intelligence, between musical intelligence and temporal-spatial reasoning, and among the scores of music theory, mathematical intelligence, and temporal-spatial reasoning, the present study employs an inventory based on Howard Gardner's theory of multiple intelligences. There are 83 third graders and fifth-graders from the Hsinchu Elementary School, participating in the study. Moreover, variables regarding music learning, such as students, whether from music classes, whether being able to play instruments, whether participating in choir, whether being able to reading music, and time duration of learning instruments, are used to predict music theory and temporalspatial reasoning by the linear regression analysis. The results show: (1) There is a significant moderate positive correlation among the eight intelligences. (2) Musical intelligence has a moderate correlation with mathematical intelligence, but may be due to. *. Pi-Chun Wu: Professor, Center for Teacher Education, National Taipei University E-mail: [email protected]. Manuscript received: 2014.07.30; Revised: 2015.01.13; Accepted: 2015.03.19.

(3) 39. temporal-spatial reasoning ability. (3) Among music theory, mathematical intelligence and temporal-spatial reasoning, there are significantly low correlations, and the relationship between the scores of music theory and mathematical intelligence may be due to temporal-spatial reasoning abilities. (4) Belonging to the music class at school can best predict achievement in music theory. The explanatory variation is .75. (5) Playing instruments can best predict temporal-spatial reasoning. However, the explanatory variation is low as .18. The suggestions regarding the exploration of the relationship between music theory and temporal-spatial reasoning abilities, the researches concerning the inventory of multiple intelligence, and the studies about the effect of different musical education approaches are proposed.. Keywords: multiple intelligence, musical education, the relationship between music and mathematics, temporal-spatial reasoning, mozart effect.

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(24) 60 教育與心理研究 38 卷 3 期. 本研究以多元智能量表所得到的. 討。. 學生自陳多元智能傾向及樂理成績,探. 有 關 量 表 方 面 , Gardner 也 曾 提. 究學生音樂智能與數學智能的關係。研. 及,要為每一個智慧能力進行實質檢. 究結果指出,國小三年級與五年級的學. 測,其工具的編製會是一件艱難的工. 生,在多元智能理論架構下的八個智能. 作,但為求音樂能力、數學能力及時空. 之間有中度顯著相關,且音樂與數學及. 推理之間,較具因果關聯的探究,建議. 時空推理能力之間也都有中度相關;然. 未來的研究可以朝編製MI智能測驗的. 而透過淨相關處理,得到音樂與數學智. 方向努力。. 能的關係似乎來自時空推理能力,同樣. 另外,由於MI量表所測得的是個. 的現象也出現在樂理成績與數學智能上. 別差異的分數,不同文化、年級與特性. 的關係。因此,本研究基本上支持音樂. 的研究對象,都可能產生不同的研究結. 與數學關係探究上的神經生理與認知心. 果,因此本研究以新竹國小83位三年級. 理學研究結果⎯⎯音樂與數學能力有. 與五年級學生所做的研究結果,能否推. 關,而其關聯性主要在於時空推理能力. 論到全臺灣的國小學生,這個問題也值. 上。. 得進一步探究。建議未來的研究可以嘗 另外,本研究結果也指出,學生. 的樂理成績與音樂智能、數學智能及時. 試以不同年齡層與不同音樂經驗的學生 為研究對象,探究相同的問題。. 空推理都有中度顯著正相關,音樂班學. 最後,音樂能力與時空推理能力. 生樂理成績顯著高於非音樂班學生。以. 有關聯,並不代表著應該直接教授音樂. 迴歸分析進行各音樂學習變項對樂理成. 來提升時空推理能力,或是直接教導時. 績的預測,也只有「是否為音樂班學. 空推理能力來提升音樂能力。未來的研. 生」最能預測樂理成績。在時空推理的. 究也可以針對直接教授樂理、直接教授. 預測上,則只有是否會樂器這個變項有. 時空推理能力,以及從遊戲、聽音開始. 解釋力。此結果似乎無法說明樂理成績. 到樂理學習的三種音樂教學取向進行比. 與時空推理的穩定關係,應該還有許多. 較研究,探討不同音樂教學取向對於學. 中介因素影響兩個主變項之間的關係,. 生音樂能力培養的成效。. 特別是教育的方式、取向和師資,可能 深深影響著樂理知識與時空推理能力的 形成,本研究並沒有蒐集學生如何接受 音樂教育的相關資料,因此無法進一步 推論,建議後續研究能做此面向的探. 參考文獻 翁瑞霖(2006)。數學與音樂的對話⎯⎯ 探討音樂中的數學應用。科學教育月 刊,288,2-21。.

(25) 以多元智能量表探究音樂與數學中的時空推理能力 61. 【 Ong, J. L. (2006). The dialogue between mathematics and music--A study of the application of mathematics to music. Science Education Monthly, 288, 2-21.】. 郭木山(2001)。多元智慧在音樂教學之 行 動 研 究 。 台 東 師 院 學 報 , 12 (上),179-210。 【Kuo, M. S. (2001). To improve the instruction of music: Acollaborative action research based on multi-intelligences. Journal of National Taitung Teachers College, 12(1), 179-210.】. 陳惠齡(2012)。幼兒音樂律動與教學。臺 北市:華騰。 【Chen, H. L. (2012). Early childhood music rhythm and teaching. Taipei, Taiwan: FarTerng.】. 張滄敏(2001)。多元智慧之主題探索教 學行動研究(未出版之碩士論文)。 國立臺北教育大學,臺北市。 【Zhang, C. M. (2001). An action research of a thematic exploration through a multiple intelligence learning center approach (Unpublished master’s thesis). National Taipei University, Taipei, Taiwan.】. 蔡聰明(1994)。音樂與數學:從弦內之 音 到 弦 外 之 音 。 數 學 傳 播 , 18 (1),1-20。 【Tsai, T. M. (1994). Music and mathematics: From the sound of the chord within overtones. Mathmedia, 18(1), 1-20.】. 盧英俊、吳海珍、錢靚、謝飛(2011)。 莫札特奏鳴曲K.448對腦電功率譜與重 心 頻 率 的 影 響 。 生 物 物 理 學 報 , 27 (2),154-166。 【Lu, Y. G., Wu, H. Z., Qian, J., & Xie, F. (2011). Research on the influence of Mozart sonata K.448 on EEG power spectrum and gravity frequency. Acta Biophysica Sinica, 27(2), 154-166.】. Gardner, H.(2013)。多元智能(Multiple Intelligences: New Horizons )( 李 乙 明、李淑貞,譯)。臺北市:五南。. (原著出版於1993年) 【 Gardner, H. (2013). Multiple intelligences: New horizons (Y. M. Li & S. Z. Li, Trans.). Taipei, Taiwan: Wu-Nan. (Original work published 1993)】. Ahmadian, M., & Hosseini, S. (2012). A study of the relationship between Iranian EFL learners’ multiple intelligences and their performance on writing. Mediterranean Journal of Social Science, 3(1), 111-126. Aldalalah, O. A., & Fong, S. F. (2010). Music intelligence and music theory learning: A cognitive load theory viewpoint. International Journal of Psychological Studies, 2(2), 150-158. Altenmüller, E. O. (2001). How many music centers are in the brain? Annals of the New York Academy of Sciences, 930, 273-280. Benson, D. J. (2007). Music: A mathematical offering. Cambridge, England: Cambridge University Press. Brust, J. C. M. (2001). Music and the neurologist: A historical perspective. Annals of the New York Academy of Sciences, 930, 143-152. Burton, S. L. (2009). Music and the math connection: An interview with Dr. Frances Rauscher. Perspectives, 4(1), 48. Butzlaff, R. (2000). Can music be used to teach reading? Journal of Aesthetic Education, 34(3/4), 167-178. Chabris, C. F. (1999). Prelude or requiem for the ‘Mozart effect’? Nature, 400, 826827. Chan, W. D. (2007). Musical aptitude and multiple intelligences among Chinese gifted students in Hong Kong: Do selfperceptions predict abilities? Personality.

(26) 62 教育與心理研究 38 卷 3 期. and Individual Differences, 43(6), 16041615. Cohen, J. E. (1961). Some relationships between music and mathematics. Music Educators Journal, 48(1), 104-109. Edelson, R. J., & Johnson, G. (2003/2004). Music makes math meaningful. Childhood Education, 80(2), 65-70. Elliott, C. A. (1982). The relationships among instrumental sight-reading ability and seven selected predictor variables. Journal of Research in Music Education, 30(1), 5-14. Elliott, C. A. (1985). Behind the budget crisis, a crisis of philosophy. Music Educators Journal, 70(2), 36-37. Elliot, D. J. (2005). Musical understanding, musical works, and emotional expression: Implications for education. Educational Philosophy and Theory, 37(1), 93-103. Ellis, K., & Fouts, J. T. (2001). Interdisciplinary curriculum: The research base. Music Educators Journal, 87(5), 22-26, 68. Ewer, G., & Mus, B. (2001). Why you need music theory? Retrieved from http://www.EasyMusicTheory.com Forgeard, M., Schlaug, G., Norton, A., Rosam, C., Iengar, U., & Winner, E. (2008). The relation between music and phonological processing in normalreading children and children with dyslexia. Music Perception, 25(4), 383390. Gardner, H. (1999). Intelligence reframed: Multiple intelligence for the 21st century. New York, NY: Basic Books. Gardner, H. (2011). Frames of mind: The. theory of multiple intelligence (3rd ed.). New York, NY: Basic Books. Garland, T. H., & Kahn, C. V. (1995). Math and music: Harmonious connections. Palo Alto, CA: Pearson Learning. Gouzouasis, P., Guhn, M., & Kishor, N. (2007). The predictive relationship between achievement and participation in music and achievement in core grade 12 academic subjects. Music Education Research, 9(1), 81-92. Graziano, A. B., Peterson, M., & Shaw, G. L. (1999). Enhanced learning of proportional math through music training and spatial-temporal training. Neurological Research, 21(2), 139-152. Gromko, J. E. (2004). Predictors of music sight-reading ability in high school wind players. Journal of Research in Music Education, 52(1), 6-15. Gudmundsdottir, H. R. (2010). Advances in music-reading research. Music Education Research, 12(4), 331-338. Hayward, C. M., & Gromko, J. E. (2009). Relationships among music sightreading and technical proficiency, spatial visualization and aural discrimination. Journal of Research in Music Education, 57(1), 26-36. Harrison, C. S. (1990a). Predicting music theory grades: The relative efficiency of academic ability, music experience, and musical aptitude. Journal of Research in Music Education, 38(2), 124-137. Harrison, C. S. (1990b). Relationships between grades in the components of freshman music theory and selected background variables. Journal of Research in Music Education, 38(3),.

(27) 以多元智能量表探究音樂與數學中的時空推理能力 63. 175-186. Hetland, L. (2000). Learning to make music enhances spatial reasoning. Journal of Aesthetic Education, 34(3-4), 179-238. Ho, Y., Cheung, M., & Chan, A. S. (2003). Music training improves verbal but not visual memory: Cross-sectional and longitudinal explorations in children. Neuropsychology, 17(3), 439-450. Jenkins, J. S. (2001). The Mozart effect. Journal of the Royal Society of Medicine, 94(4), 170-172. Johnson, D. A. (2000). The development of music aptitude and effects on scholastic achievement of 8 to 12 year olds (Unpublished doctoral dissertation). University of Louisville, KY. Kluball, J. L. (2000). The relationship of instrumental music instruction and academic achievement for the senior class of 2000 at Lee County High School, Leesburg, Georgia. Dissertation Abstracts International, 61(11), 4320A. Kreutz, G., & Lotze, M. (2007). Neuroscience of music and emotion. In W. Gruhn & Rauscher, F. (Eds.), Neuroscience in music pedagogy (Chapter 6, pp. 143167). New York, NY: Nova Science. Kvet, E. (1985). Excusing elementary school students from regular classroom activities for the study of instrumental music: The effect on sixth-grade reading, language, and mathematics achievement. Journal of Research in Music Education, 32(1), 45-54. Koura, A. A., & Al-Hebaish, S. M. (2014). The relationship between multiple intelligences, self-efficacy and academic achievement of Saudi gifted and regular. intermediate students. Educational Research International, 3(1), 48-70. Lamar, H. B., Jr. (1989). An examination of the congruency of music aptitude scores and mathematics and reading achievement scores of elementary children. Dissertation Abstracts International, 51(03), 0778A. Leng, X., Shaw, G., & Wright, E. (1990). Coding of musical structure and the trion model of cortex. Music Perception, 8(1), 49-62. Levitin, D. J., & Tirovolas, A. K. (2009). Current advances in the cognitive neuroscience of music. Annals of the New York Academy of Sciences, 1156, 211-231. Luce, J. R. (1965). Sight-reading and earplaying abilities as related to instrumental music students. Journal of Research in Music Education, 13(2), 101-109. Luiz, C. S. (2007). The learning of music as a means to improve mathematical skills. International Symposium on Performance Science. Retrieved from http://www. performancescience.org/ISPS2007/Proce edings/26santos-Luiz.pdf Marzban, M., Shahbazi, A., Tondar, M., Soleiman, M., Bakhshayesh, M., Moshkforoush, A., … Joghataei, M. T. (2011). Effect of Mozart music on hippocampal content of BDNF in postnatal rats. Neuroscience, 2(3), 21-26. McKelvie, P., & Low, J. (2002). Listening to Mozart does not improve children’s spatial ability: Final curtains for the Mozart effect. British Journal of Developmental Psychology, 20(2), 241-.

(28) 64 教育與心理研究 38 卷 3 期. 258. McMahon, S. D., Rose, D. S., & Parks, M. (2004). Multiple intelligences and reading achievement: An examination of the Teele Inventory of multiple intelligences. The Journal of Experimental Education, 73(1), 41-52. Newman, J., Rosenbach, J. H., Burns, K. L., Latimer, B. C., Matocha, H. R., & Vogt, E. R. (1995). An experimental test of the Mozart effect: Does listening to his music improve spatial ability? Perceptual and Motor Skills, 81, 13791387. Peretz, I., & Zatorre, R. J. (Eds.). (2003). The cognitive neuroscience of music. New York, NY: Oxford University Press. Rauscher, F. H., & Hinton, S. (2006). The Mozart effect: Music listening is not music instruction. Educational Psychologist, 41(4), 233-238. Rauscher, F. H., LeMieux, M., & Hinton, S. C. (2005). Selective effects of music instruction on cognitive performance of at-risk children. Paper presented at the biannual meeting of the European Conference on Developmental Psychology, Tenerife, Canary Islands. Rauscher, F. H., Robinson, K. D., & Jens, J. J. (1998). Improved maze learning through early music exposure in rats. Neurological Research, 20(5), 427-432. Rauscher, F. H., Shaw, G. L, & Ky, K. N. (1993). Music and spatial task performance. Nature, 365(6447), 611. Rauscher, F. H., Shaw, G. L., Levine, L. J., Wright, E. L., Dennis, W. R., & Newcomb, R. L. (1997). Music training causes long-term enhancement of. preschool children’s spatial-temporal reasoning. Neurological Research, 19(1), 1-8. Robitaille, J., & O’Neal, S. 1981 “Why instrumental music in the elementary schools?” Phi Delta Kappan, 63, 21. Schellenberg, E. G., & Hallam, S. (2005). Music listening and cognitive abilities in 10 and 11 year olds: The Blur effect. Annals of the New York Academy of Sciences, 1060(1), 1-8. Schmithorst, V. J., & Holland, S. K. (2004). The effect of musical training on the neural correlates of math processing: A functional magnetic resonance imaging study in humans. Neuroscience Letters, 354(3), 193-196. Shah, S. (2010). An exploration of the relationship between mathematics and music. Math30000, 3rd Year Project, Manchester Institute for Mathematical Sciences, School of Mathematics, The University of Manchester. Sharifi, H. P. (2008). The introductory study of Gardner’s multiple intelligences theory, in the field of lesson subjects and the students’ compatibility. Quarterly Journal of Educational Innovations, 24, 11-20. Sluming, V., Brooks, J., Howard, M., Downes, J. J., & Roberts, N. (2007). Broca’s area supports enhanced visuospatial cognition in orchestral musicians. Journal of Neuroscience, 27(14), 3799-3806. Southgate, D. E., & Roscigno, V. J. (2009). The impact of music on childhood and adolescent achievement. Social Science Quarterly, 90(1), 5-20. Steele, K. M., Ball, T. N., & Crook, M..

(29) 以多元智能量表探究音樂與數學中的時空推理能力 65. (1999). The mystery of the Mozart effect: Failure to replicate. Psychological Science, 10(4), 366-369. Taylor, J. M., & Rowe, B. (2012). The "Mozart Effect" and the mathematical connection. Journal of College Reading and Learning, 42(2), 51-66. Trainor, L. J., & Schmidt, L. A. (2003). Processing emotions induced by music. In I. Peretz & R. J. Zatorre (Eds.) The cognitive neuroscience of music (Chapter 20, pp. 310-324). New York, NY: Oxford University Press. Upitis, R. (2013). Using a whole-music approach creatively. In P. Burnard & R. Murphy (Eds.), Teaching music creatively (pp. 153-163). London, UK: Routledge. Vaughn, K. (2000). Music and mathematics: Modest support for the oft-claimed relationship. Journal of Aesthetic Education, 34(3/4), 149-166.. Vaughn, K., & Winner, E. (2000). SAT scores of students who study the arts: What we can and cannot conclude about association. Journal of Aesthetic Education, 34(3/4), 77-89. Waterhouse, L. (2006). Multiple intelligences, the Mozart effect, and emotional intelligence: A critical review. Educational Psychologist, 41, 207-225. Winner, E., & Hetland, L. (2000). The arts in education: Evaluating the evidence for a causal link. Journal of Aesthetic Education, 34(3/4), 3-10. Wright, D. (2009). Mathematics and music. Providence, RI: American Mathematical Society. Zeki, S., Romaya, J. P., Benincasa, D. M., & Atiyah, M. (2014). The experience of mathematical beauty and its neural correlates. Frontier in Human Neuroscience, 8(68), 1-12..

(30) 66 教育與心理研究 38 卷 3 期. 附錄:多元智能檢核表(原量表題目敘述採用14號字體,方便小學生閱讀) 姓名:________________. 年級:______. 座號:______. 請依照你自己的情況,在空格中勾選符合的程度。 I. 題 號. 題目敘述. 完全 符合. 非常 符合. 有些 符合. 不太 完全 符合 不符 合. 完全 符合. 非常 符合. 有些 符合. 不太 符合. 1 我喜歡聽別人口說事情(例如:故事、廣播、故事錄音帶等)。 2 我對於要如何做事,會問很多問題。 3* 我可以清楚說出眼睛看到的或腦中想到的影像。 4 我擅長一種或多種體育運動(如跑步、籃球、躲避球、羽毛球 等)。 5 聽到音樂走調或出錯時我能立刻知道。 6 我喜歡與同伴談心。 7 我能獨立、意志堅強,不隨便放棄。 8 我擅長分辨動物、植物或岩石的種類。. II. 題 號. 題目敘述. 1 我善於編出新奇的故事或笑話。 2 我很會心算。 3 我閱讀地圖和圖表比閱讀文字來得容易。 4 我長時間在一處坐著,會有扭動、敲打東西或煩躁不安的現象。 5 我能很快記得歌曲的旋律。 6 我喜歡領導或指揮別人做事。 7 我清楚了解自己的優缺點。 8 我在上課時喜歡談論一些有關動植物的知識。. 完全 不符 合.

(31) 以多元智能量表探究音樂與數學中的時空推理能力 67. III. 題 號. 題目敘述. 完全 符合. 非常 符合. 有些 符合. 不太 符合. 完全 不符 合. 完全 符合. 非常 符合. 有些 符合. 不太 符合. 完全 不符 合. 完全 符合. 非常 符合. 有些 符合. 不太 符合. 完全 不符 合. 1 我喜歡說順口溜、雙關語、繞口令。 2 我喜歡上數學課。 3 我喜歡想像。 4 我善於模仿他人的動作或言談舉止。 5 我唱歌很好聽。 6 我喜歡提供意見給有問題的朋友。 7 我自己一個人也可以玩耍或學習。 8 我喜歡看、聽、聞以及觸摸所看到的物體。. IV. 題 號. 題目敘述. 1 我喜歡玩像語詞接龍這樣的文字遊戲。 2 我對算數遊戲或電腦算數遊戲感興趣。 3 我喜歡參加畫展等藝術活動。 4 我喜歡把物品拆解、然後再組裝回去。 5 我會彈奏樂器或曾參加合唱團。 6 當我對事情無法做決定時,習慣馬上去問別人的意見。 7 我的生活和學習方式與眾不同。 8 我喜歡養寵物或種植一些花草樹木。. V. 題 號. 題目敘述. 1 我說故事或聊天能吸引別人的專注。 2 我喜歡象棋或其他策略性遊戲。 3 我畫圖畫得比其他人好。 4 我喜歡觸摸所見到的事物。 5 我在講話或走動時很有節奏感。 6 我喜歡小組活動或參加社團。 7 我會常常反省自己的行為。 8 我常會注意到其他人所未注意到的事物。.

(32) 68 教育與心理研究 38 卷 3 期. VI. 題 號. 題目敘述. 完全 符合. 非常 符合. 有些 符合. 不太 符合. 完全 不符 合. 完全 符合. 非常 符合. 有些 符合. 不太 符合. 完全 不符 合. 完全 符合. 非常 符合. 有些 符合. 不太 符合. 完全 不符 合. 1 我喜歡寫作文和日記。 2 我喜歡做猜謎或推理方面的解題遊戲。 3 我喜歡看電影、幻燈片或其他視覺表演。 4 我喜歡跑、跳、跳舞或類似的活動。 5 我會無意識地自己哼哼唱唱。 6 我喜歡教導別人。 7 我會自己訂做事的目標。 8 我時常仰望天空做觀察,而且告訴別人各種雲的種類和它們所帶 來的天氣型態。. VII. 題 號. 題目敘述. 1 我喜歡看書。 2 我喜歡思考問題。 3* 我喜歡製作有趣的立體模型。 4 我喜歡演戲。 5 我對外界的噪音很敏感。 6 我至少有兩、三個好朋友。 7 我能準確表達自己的感覺。 8 我喜歡參加賞鳥、園藝、自然步道等戶外活動。. VIII. 題 號. 題目敘述. 1 我會善用成語、形容詞和比喻等修辭方法。 2 我喜歡用符號計算或記錄事情。 3 我喜歡閱讀圖畫很多的書。 4 我在思考與工作時,常會有手舞足蹈的動作。 5 我喜歡聽音樂。 6 我會主動關心別人。 7 我能從生活和失敗中學習。 8 我對介紹自然界的書、影帶或節目特別有興趣。.

(33) 以多元智能量表探究音樂與數學中的時空推理能力 69. IX. 題 號. 題目敘述. 完全 符合. 非常 符合. 有些 符合. 不太 完全 符合 不符 合. 完全 符合. 非常 符合. 有些 符合. 不太 完全 符合 不符 合. 1 我的字總是寫得又好看又正確。 2 我對事情的原因和結果總是會弄得很清楚。 3* 我能用圖像表達自己的想法。 4 我喜歡黏土或手指畫等活動。 5 我會自己唱課本學來的歌曲。 6 別人喜歡找我做伴。 7 我的自尊心很強。 8 我喜歡收集一些自然界的景物(例如標本、貝殼),並做有系統 的分類。. X. 題 號. 題目敘述. 1 我喜歡和別人交談。 2 我喜歡將事物分類或分等。 3* 我喜歡拼圖、走迷宮或類似的視覺活動。 4 我有手工方面的技能(如木工、縫紉、機械等) 。 5 我會一邊做事,一邊在桌子上打節拍。 6 我喜歡與其他人一起玩。 7 我喜歡獨立工作。 8 我很容易注意並分辨住家或學校附近的植物。.

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