簡易檢索 / 詳目顯示

研究生: 陳映涵
Chen, Ying-Han
論文名稱: 小學中、高年級學生一般詞彙知識與數學詞彙知識對數學成就的預測力
The Predictive Power of General Vocabulary and Mathematics Vocabulary for Mathematics Achievement among Middle- and High-Grade Students of Elementary School
指導教授: 吳昭容
Wu, Chao-Jung
口試委員: 林世華
Lin, Shi-Hua
曾建銘
Tseng, Chien-Ming
吳昭容
Wu, Chao-Jung
口試日期: 2021/06/11
學位類別: 碩士
Master
系所名稱: 教育心理與輔導學系
Department of Educational Psychology and Counseling
論文出版年: 2021
畢業學年度: 109
語文別: 中文
論文頁數: 44
中文關鍵詞: 一般詞彙知識數學詞彙知識數學成就
英文關鍵詞: general vocabulary knowledge, mathematics vocabulary knowledge, mathematics achievement
研究方法: 實驗設計法
DOI URL: http://doi.org/10.6345/NTNU202100563
論文種類: 學術論文
相關次數: 點閱:108下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 一般詞彙知識與數學詞彙知識在數學成就中所扮演的角色日益受到關注。本研究探討在控制非語文智力和語文智力之下,一般詞彙知識與數學詞彙知識對數學成就之預測。研究對象為342位四年級學生與395位六年級學生,共737位學生。在研究工具上,測量智力採用國小中高年級學校能力測驗,測量一般詞彙知識採用詞彙成長測驗,測量數學詞彙知識採用國民中小學數學詞彙知識測驗,測量數學成就的採用自編的數學成就測驗。本研究在107年6月進行數學詞彙知識與一般詞彙知識測驗之施測,並於108年5月進行智力測驗、與數學成就測驗之施測。本研究採Mplus 8.3統計軟體進行分析,透過建立結構方程模式進行路徑分析,亦採SPSS 23.0統計軟體進行相關分析。研究結果顯示:第一,在四年級與六年級中,非語文智力和語文智力對數學成就皆具有預測力。四年級非語文智力的預測力為 .50,語文智力的預測力為 .22;六年級非語文智力的預測力為 .32,語文智力的預測力為 .42。顯示年級較低時,非語文智力的預測力較大;而年級較高時,語文智力的預測力較大。第二,在控制非語文智力和語文智力之下,四年級與六年級在一般詞彙知識對數學成就有獨特的預測力。四年級一般詞彙知識的預測力為 .14;六年級一般詞彙知識的預測力為 .25。第三,在控制非語文智力、語文智力與一般詞彙知識的預測之下,四年級與六年級在數學詞彙知識對數學成就仍有獨特的預測力。四年級數學詞彙知識的預測力為 .11;六年級數學詞彙知識的預測力為 .20。第四,四年級與六年級的數學詞彙知識在一般詞彙知識對數學成就的關係皆具有部分中介效果。四年級的部分中介效果值為 .04;六年級的部分中介效果值為 .09。此結果代表非語文智力、語文智力、一般詞彙知識、數學詞彙知識對數學成就分別都具有獨特的預測力,且隨著年級的增長而變化。一般詞彙知識會有部分透過數學詞彙知識間接預測數學成就,且高年級學生之預測力更高。最後,本研究建議未來相關研究可以針對施測時間有更好的設計,並擴展研究對象與變項多樣性的搜集,期望對一般詞彙知識與數學詞彙知識對數學成就之關係有更深入地了解。

    The roles of general vocabulary knowledge and mathematics vocabulary knowledge are gradually gaining recognition in mathematics achievement. This study aims to determine the predictive power of the knowledge of general and mathematics vocabulary for mathematics achievement after controlling for non-verbal and verbal intelligence. A total of 737 students was recruited to participate in this study, including 342 fourth-graders and 395 sixth-graders. OLSAT-8 was administered to measure the subjects’ intelligence quotient, while general vocabulary was measured using the vocabulary growth test. In addition, the national elementary and middle school mathematics vocabulary knowledge test was used to measure the participants’ mathematics vocabulary, and a self-edited mathematics achievement test was adopted to measure the subjects’ mathematics achievement. Measurements of mathematics vocabulary and general vocabulary were conducted in June 2018, while intelligence tests and self-edited mathematics achievement tests were administered in May 2019. Mplus 8.3 was used for statistical analysis, structural equation modelling was performed for path analysis, and SPSS 23.0 was employed for correlation analysis. The results demonstrate that (1) non-verbal intelligence and verbal intelligence are both predictive of mathematics achievement in the two observed groups. The predictive powers o f non-verbal intelligence and verbal intelligence, respectively, were .50 and .22 in the fourth-graders and .32 and .42 in the sixth-graders. This result implies that the predictive power of non-verbal intelligence is greater in lower grades, while that of verbal intelligence is higher in higher grades. (2) After controlling for non-verbal and verbal intelligence, general vocabulary showed a particular predictive power for the mathematics achievement of fourth-graders and sixth-graders of .14 and .25, respectively. (3) Controlling for non-verbal intelligence, verbal intelligence, and general vocabulary, mathematics vocabulary showed a predictive power for mathematics achievement of .11 for fourth-graders and .20 for the sixth-graders. (4) Mediators exist in the relationship between mathematics vocabulary knowledge and general vocabulary knowledge with mathematics achievement, with mediation effects of .04 for fourth-graders and .09 for sixth-graders. This result indicates that non-verbal intelligence, verbal intelligence, general vocabulary knowledge, and mathematics vocabulary knowledge show specific predictabilities for mathematics achievement that vary by grade. Furthermore, some general vocabulary knowledge may indirectly influence mathematics achievement via mathematics vocabulary knowledge, with higher grades experiencing greater predictability. Finally, in the hope of acquiring a deeper insight into how general vocabulary knowledge and mathematics vocabulary knowledge would affect mathematics achievement, this study suggests lines of future research to optimize the timing of measurements on the aforementioned variables, expand the investigation to more subjects, and broaden the variables collected.

    謝詞 i 中文摘要 ii 英文摘要 iii 目次 v 表次 vi 圖次 vii 壹、緒論 1 一、數學成就、一般詞彙知識與數學詞彙知識的意涵 2 二、一般詞彙知識、數學詞彙知識與數學成就之關係 9 三、其他相關的預測因素 13 四、研究架構與問題 16 貳、研究方法 18 一、研究對象 18 二、研究工具 18 三、研究程序 20 四、資料分析 20 參、研究結果 21 一、描述統計 21 二、路徑分析 23 肆、結論與建議 33 一、研究結論 33 二、數學教育實務相關建議 35 三、研究限制與建議 36 參考文獻 38 中文部分 38 英文部分 39

    吳昭容、曾建銘、陳柏熹(2020):國民中小學數學詞彙知識測驗。心理出版社。
    吳昭容、曾建銘、鄭鈐華、陳柏熹、吳宜玲(2018):領域特定詞彙知識的測量:三至八年級學生數學詞彙知識。教育研究與發展期刊,14(4),140。https://doi.org/10.3966/181665042018121404001
    林宜臻(2021):TASA小四小六數學學習成就標準設定之省思―評量架構宜與PLD政策性定義一致。取自國家教育研究院電子報網站:https://epaper.naer.edu.tw/ed.php?grp_no=2&edm_no=25&content_no=637#,2021年4月22日。
    洪儷瑜、陳心怡、陳柏熹、陳秀芬(2014):詞彙成長測驗。中國行為科學社。
    國家教育研究院(2018):長期主題型調查—臺灣學生學習成就評量資料庫(TASA)。引自網站:https://tasal.naer.edu.tw/tasa
    張偉豪、鄭時宜(2012):與結構方程模式共舞—曙光初現。前程文化。
    教育部(2003):國民中小學九年一貫課程綱要數學學習領域。引自網站:https://cirn.moe.edu.tw/Upload/file/742/67260.pdf
    教育部(2018):十二年國民基本教育課程綱要數學領域。引自網站: https://cirn.moe.edu.tw/Upload/file/27405/61868.pdf
    陳美芳、陳心怡(2006):國小中高年級學校能力測驗。中國行為科學社。
    曾雅瑛、黃秀霜(2002):國民小學中文詞彙測驗之編製。測驗年刊,49(2),199216。
    黃聖霖(2017):國小六年級學生對數學教科書文字題詞彙識別之研究(未發表)。國立屏東大學科普傳播學系碩士論文。
    Albanese, O., De Stasio, S., Di Chiacchio, C., Fiorilli, C., & Pons, F. (2010). Emotion comprehension: The impact of nonverbal intelligence. The Journal of Genetic Psychology, 171(2), 101–115. http://dx.doi.org/10.1080/00221320903548084
    Alloway, T. P., & Passolunghi, M. C. (2011). The relationship between working memory, IQ, and mathematical skills in children. Learning and Individual Differences, 21(1), 133137. https://doi.org/10.1016/j.lindif.2010.09.013
    Anderson, R. C., & Freebody, P. (1981). Vocabulary knowledge. Comprehension and Teaching: Research Reviews, 77–117.
    Berch, D. B., & Mazzocco, M. M. M. (2007). Why is math so hard for some children? The nature and origins of mathematical learning difficulties and disabilities. Paul H. Brookes.
    Blazhenkova, O., & Kozhevnikov, M. (2010). Visual-object ability: A new dimension of non-verbal intelligence. Cognition, 117(3), 276–301. https://doi.org/10.1016/j.cognition.2010.08.021
    Brenner, A. B. (1981). Elementary school students’ abilities to read and solve arithmetic word problems: A study of prerequisite skills [Unpublished doctoral dissertation]. University of California, Los Angeles.
    Edwards, A. S. (1936). A mathematics vocabulary test and some results of an examination of university freshmen. Journal of Educational Psychology, 27(9), 694–697. https://doi.org/10.1037/h0062378
    Forsyth, S. R., & Powell, S. R. (2017). Differences in the mathematics-vocabulary knowledge of fifth-grade students with and without learning difficulties. Learning Disabilities Research and Practice, 32, 231–245. https://doi.org/10.1111/ldrp.12144
    Fuchs, L. S., Fuchs, D., Compton, D. L., Hamlett, C. L., & Wang, A. Y. (2015). Is word-problem solving a form of text comprehension? Scientific Studies of Reading, 19(3), 204–223. https://doi.org/10.1080/10888438.2015.1005745
    Fuchs, L. S., Gilbert, J. K., Fuchs, D., Seethaler, P. M., & Martin, B. N. (2018). Text comprehension and oral language as predictors of word-problem solving: Insights into word-problem solving as a form of text comprehension. Scientific Studies of Reading, 22(2), 152–166. https://doi.org/10.1080/10888438.2017.1398259
    Gairns, R., & Redman, S. (1986). Working with words: A guide to teaching and learning vocabulary. Cambridge University Press.
    Geary, D. C. (2011). Cognitive predictors of achievement growth in mathematics: A 5-year longitudinal study. Developmental Psychology, 47, 1539–1552. https://doi.org/10.1037/a0025510
    Gerrig, R. J., Zimbardo, P. G., Zimbardo, P. G., Psychologue, E. U., & Zimbardo, P. G. (2010). Psychology and life (Vol. 20). Pearson.
    Gimbert, F., Camos, V., Gentaz, E., & Mazens, K. (2019). What predicts mathematics achievement? Developmental change in 5-and 7-year-old children. Journal of Experimental Child Psychology, 178, 104120. https://doi.org/10.1016/j.jecp.2018.09.013
    Gottfredson, L. S. (1997). Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography. Wall Street Journal, 24(1), 13–23. https://doi.org/10.1016/S0160-2896(97)90011-8
    Green, C. T., Bunge, S. A., Chiongbian, V. B., Barrow, M., & Ferrer, E. (2017). Fluid reasoning predicts future mathematical performance among children and adolescents. Journal of Experimental Child Psychology, 157, 125143. https://doi.org/10.1016/j.jecp.2016.12.005
    Kim, I.-S. (2009). The relevance of multiple intelligences to CALL instruction. The Reading Matrix, 9(1), 1–16. https://doi.org/10.1080/0952398980350206
    Kyttälä, M., & Lehto, J. E. (2008). Some factors underlying mathematical performance: The role of visuospatial working memory and non-verbal intelligence. European Journal of Psychology of Education, 23(1), 77–94. https://doi.org/10.1007/BF03173141
    Lervåg, A., Dolean, D., Tincas, I., & Melby-Lervåg, M. (2019). Socioeconomic background, nonverbal IQ and school absence affects the development of vocabulary and reading comprehension in children living in severe poverty. Developmental science, 22(5), 1–15. https://doi.org/10.1111/desc.12858
    Lin, X. (2020). Investigating the unique predictors of word-problem solving using meta-analytic structural equation modeling. Educational Psychology Review. Advance online publication. https://doi.org/10.1007/s10648-020-09554-w
    Lin, X., Peng, P., & Zeng, J. (2021). Understanding the Relation between Mathematics Vocabulary and Mathematics Performance: A Meta-analysis. The Elementary School Journal, 121(3), 504540. https://doi.org/10.1016/j.lindif.2018.11.006
    Mayer, J. D., Roberts, R. D., & Barsade, S. G. (2008). Human abilities: Emotional intelligence. Annual Review of Psychology, 59, 507–536. https://doi.org/10.1146/annurev.psych.59.103006.093646
    Mayer, R. E., Bove, W., Bryman, A., Mars, R., & Tapangco, L. (1996). When less is more: Meaningful learning from visual and verbal summaries of science textbook lessons. Journal of Educational Psychology, 88(1), 64–73. https://doi.org/10.1037/0022-0663.88.1.64
    Monroe, E. E., & Orme, M. P. (2002). Developing mathematical vocabulary. Preventing School Failure: Alternative Education for Children and Youth, 46(3), 139–142. https://doi.org/10.1080/10459880209603359
    Monroe, E. E., & Panchyshyn, R. (1995). Vocabulary considerations for teaching mathematics. Childhood Education, 72(2), 80–83. https://doi.org/10.1080/00094056.1996.10521849
    Moschkovich, J. N. (2015). Scaffolding student participation in mathematical practices. Mathematics Education, 47(7), 1067–1078. https://doi.org/10.1007/s11858-015-0730-3
    Nahavandi, Z., Tabatabaee-Yazdi, M., & Samir, A. (2020). Verbal and Non-Verbal Fluid Intelligence as Predictors of Vocabulary Knowledge. Journal of English Language Research, 1(1), 12–21. https://doi.org/10.1016/j.intell.2005.03.008
    National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. National Council of Teachers of Mathematics.
    Oh, M. H., & Mancilla-Martinez, J. (2021). Comparing vocabulary knowledge conceptualizations among Spanish–English dual language learners in a new destination state. Language, Speech, and Hearing Services in Schools, 52(1), 369–382. https://doi.org/10.1044/2020_LSHSS-20-00031
    Peng, P., & Lin, X. (2019). The relation between mathematics vocabulary and mathematics performance among fourth graders. Learning and Individual Differences, 69, 11–21. https://doi.org/10.1016/j.lindif.2018.11.006
    Peng, P., Lin, X., Ünal, Z. E., Lee, K., Namkung, J., Chow, J., & Sales, A. (2020). Examining the mutual relations between language and mathematics: A meta-analysis. Psychological Bulletin, 146(7), 595–634. https://doi.org/10.1037/bul0000231
    Peng, P., Namkung, J., Barnes, M., & Sun, C. Y. (2016). A meta-analysis of mathematics and working memory: Moderating effects of working memory domain, type of mathematics skill, and sample characteristics. Journal of Educational Psychology, 108, 455–473. https://doi.org/10.1037/edu0000079
    Peng, P., Sun, C. Y., Li, B. L., & Tao, S. (2012). Phonological storage and executive function deficits in children with mathematics difficulties. Journal of Experimental Child Psychology, 112, 452–466. https://doi.org/10.1016/j.jecp.2012.04.004
    Phillips, C. (1960). The relationship between arithmetic achievement and vocabulary knowledge of elementary mathematics. The Arithmetic Teacher, 7(5), 240–242. https://doi.org/10.5951/AT.7.5.0240
    Pina, V., Fuentes, L. J., Castillo, A., & Diamantopoulou, S. (2014). Disentangling the effects of working memory, language, parental education, and non-verbal intelligence on children’s mathematical abilities. Frontiers in Psychology, 5, 415. https://doi.org/10.3389/fpsyg.2014.00415
    Powell, S. R., & Nelson, G. (2017). An investigation of the mathematics-vocabulary knowledge of first-grade students. The Elementary School Journal, 117(4), 664–686. https://doi.org/10.37099/mtu.dc.etdr/1043
    Powell, S. R., Driver, M. K., Roberts, G., & Fall, A. M. (2017). An analysis of the mathematics vocabulary knowledge of third-and fifth-grade students: Connections to general vocabulary and mathematics computation. Learning and Individual Differences, 57, 22–32. https://doi.org/10.1016/j.lindif.2017.05.011
    Powell, S. R., Fuchs, L. S., & Fuchs, D. (2013). Reaching the mountaintop: Addressing the common core standards in mathematics for students with mathematics difficulties. Learning Disabilities Research and Practice, 28(1), 38–48. https://doi.org/10.1111/ldrp.12001
    Ramsden, S., Richardson, F. M., Josse, G., Thomas, M. S., Ellis, C., Shakeshaft, C., Mohamed L. Seghier, M. L.,& Price, C. J. (2011). Verbal and non-verbal intelligence changes in the teenage brain. Nature, 479(7371), 113–116. https://doi.org/10.1038/nature10514
    Rose, L. T., & Rouhani, P. (2012). Influence of Verbal Working Memory Depends on Vocabulary: Oral Reading Fluency in Adolescents With Dyslexia. Mind, Brain, and Education, 6(1), 1–9. https://doi.org/10.1111/j.1751-228X.2011.01135.x
    Rubenstein, R. N., & Thompson, D. R. (2002). Understanding and supporting children’s mathematical vocabulary development. Teaching Children Mathematics, 9(2), 107–113. https://doi.org/10.5951/TCM.9.2.0107
    Sasanguie, D., Göbel, S. M., Moll, K., Smets, K., & Reynvoet, B. (2013). Approximate number sense, symbolic number processing, or number–space mappings: What underlies mathematics achievement?. Journal of Experimental Child Psychology, 114(3), 418–431. https://doi.org/10.1016/j.jecp.2012.10.012
    Sayeski, K. L., & Paulsen, K. J. (2010). Mathematics reform curricula and special education: Identifying intersections and implications for practice. Intervention in School and Clinic, 46(2), 13–21. https://doi.org/10.1177/1053451210369515
    Schleppegrell, M. J. (2007). The linguistic challenges of mathematics teaching and learning: A research review. Reading and Writing Quarterly, 23(2), 139–159. https://doi.org/10.1080/10573560601158461
    Simpson, A., & Cole, M. W. (2015). More than words: A literature review of language of mathematics research. Educational Review, 67(3), 369–384. https://doi.org/10.1080/00131911.2014.971714
    Sonnenschein, S., Thompson, J. A., Metzger, S. R., & Baker, L. (2013). Relations between Preschool Teachers’ Language and Gains in Low Income English Language Learners’ and English Speakers’ Vocabulary, Early Literacy and Math Skills. NHSA Dialog, 16(4), 64–87. https://doi.org/10.1080/03004430.2016.1219854
    Spearman, C. (1904). ‘‘General intelligence” objectively determined and measured. American Journal of Psychology, 15, 201–293. https://doi.org/10.1037/11491-006
    Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. Cambridge University Press.
    Swanson, H. L., & Sachse-Lee, C. (2001). Mathematical problem solving and working memory in children with learning disabilities: Both executive and phonological processes are important. Journal of Experimental Child Psychology, 79(3), 294–321. https://doi.org/10.1006/jecp.2000.2587
    Thurstone, L. L., & Thurstone, T. G. (1938). Primary mental abilities (Vol. 119). University of Chicago Press.
    Vacca, J., Vacca, R. T., Gove, M. K., Burkey, L. C., Lenhart, L. A., & McKeon, C. A. (2009). Reading and learning to read (7th ed.). Pearson.
    Vukovic, R. K. (2006). The development of numeracy: A longitudinal study of children from first through fourth grade [Unpublished doctoral dissertation]. University of British Columbia.
    Waring, R.(1999). Tasks for assessing second language receptive and productive vocabulary [Unpublished doctoral dissertation]. University of Wales.
    Wasik, B. A., & Hindman, A. H. (2020). Increasing preschoolers’ vocabulary development through a streamlined teacher professional development intervention. Early Childhood Research Quarterly, 50, 101–113. https://doi.org/10.1016/j.ecresq.2018.11.001

    無法下載圖示 電子全文延後公開
    2026/06/21
    QR CODE