國小學生對統計圖理解層次之研究

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：93

、訪客IP：3.138.110.119

姓名

陳偉琳(Wei-lin Chen) 查詢紙本館藏

畢業系所

學習與教學研究所

論文名稱

國小學生對統計圖理解層次之研究
(The Study of Elementary School Students' Understandingon the Levels of Graph Comprehension)

相關論文

★ 以同儕互評與討論提升小六學童之寫作表現 ~以行動學習輔具教室為例	★ 從眼動資料探討字形與聲旁在篇章閱讀的效果
★ 從眼動資料探討連接詞與閱讀歷程之關係	★ EFL大學生閱讀英文的眼動資料分析
★ 以眼動型態探討背景知識對詞彙辨識的影響	★ 閱讀教學與國民小學學童閱讀動機及行為的關係—以2005年PIRLS資料為例
★ 合作寫作對於國小學童科學概念學習之影響	★ 記憶廣度與語境效應對閱讀歧義句的影響：來自眼動的證據
★ 由句法探討手語聽障生書面語閱讀的現象	★ 英文閱讀能力與先備知識對閱讀物理篇章推論的影響
★ 正負數量表徵的心理數線發展	★ 識字教學法與口語詞彙能力對新移民女性中文識字學習之影響
★ 國小學童對幽默漫畫閱讀歷程之研究	★ 成人與小六學童在中文多義詞語意激發和選擇的比較
★ 線上閱讀測驗之發展與學生能力表現之探究	★ 關係子題及線圖對國小數學低成就學生理解比較型文字題之影響

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

本研究旨在探討國小六年級學生在理解統計圖所需的報讀、比較大小、計算、推論和摘要等五項能力的表現情形，特別是數學課程未進行教學的推論和摘要能力，並檢視高、低數學能力的學生在此兩項能力題目的理解表現是否有差異；統計圖理解層次分別為報讀資料、比較資料和解讀資料層次，本研究根據各理解層次的定義共細分出五項所需的能力，分別為屬於報讀資料層次的報讀能力、比較資料層次中的比較大小和計算兩項能力，以及解讀資料層次所需的推論和摘要兩項能力。為了解六年級學生在五項能力上的理解表現，本研究自行設計能夠反映五項能力內涵的統計圖理解層次測驗，並增加檢視學生是否能夠辨識統計圖的基本構成要素例如橫/縱軸的識圖題，即每個統計圖題組皆包含前述六種類型的題目，每人需回答七個題組，所採用的統計圖類型為學生在學校課程可學習到的長條圖、折線圖和圓形圖，統計圖主題包含社會課本單元中有採用統計圖的主題和日常生活中常見以統計圖呈現數據資料的議題。此外，採用學生的在校段考數學成績作為數學能力的依據指標。
本研究發現，六年級學生在推論和摘要的表現是五項能力之中表現較弱的項目，其中，數學能力會影響學生在此兩項能力題目的表現，且學生在推論和摘要的表現有顯著差異。此外，影響摘要表現的因素包含學生的數學能力、統計圖主題內容及統計圖的複雜程度；根據本研究結果建議，在教學上，教師可提供目前學校課程未進行教學的推論和摘要能力之課程，藉由加強學生在此兩項能力的不足，可幫助學生具備從統計圖資料中獲取意義的能力。

摘要(英)

This study examined sixth grade students’ performance on the five abilities of graph comprehension, which include reading, comparison, calculation, reasoning and summarization. This study especially concerns with the ability of reasoning and summarization on mathematics curriculums that were not taught in class. In addition,
this study also interested in whether mathematical ability will influence the performance on graph comprehension. Five abilities above-mentioned are subdivisions from three levels of graph comprehension (reading, comparing, and
interpreting data). The ability of reading is from the level of reading data. Comparison and calculation are from the level of comparing data, whereas reasoning and
summarization came from the level of interpreting data. Assessment test used in this study is structured based on three types of statistical graphics (i.e., bar chart, line chart and pie chart) and contained five types of questions, which are formulated in accordance to the definitions of five abilities. Every student has to answer seven questions. The basis of students’ mathematical ability is determined on students’monthly mathematical exams.
Following results are found: Students’ performance on reasoning and summarization are significantly lower than the other three abilities. In addition, mathematical ability influenes the performance of these two abilities. From these results, one suggests that mathematics teachers should teach students more about reasoning and summarization. Because these two abilities help the students to derive meanings out of statistical graphics.

關鍵字(中)

★ 國小學生
★ 統計圖
★ 統計圖理解層次
★ 數學能力

關鍵字(英)

★ elementary school students
★ statistical graphic
★ mathematical ability

論文目次

第一章緒論..............................................................................................................1
第一節研究背景與動機......................................................................................1
第二節研究目的與問題......................................................................................5
第三節名詞釋義..................................................................................................6
第四節研究限制..................................................................................................7
第二章文獻探討.....................................................................................................8
第一節理解統計圖及相關研究..........................................................................8
第二節統計圖的理解層次................................................................................12
第三節影響理解統計圖的因素........................................................................18
第四節國內數學課程中的統計圖教學............................................................21
第五節小結........................................................................................................26
第三章研究方法...................................................................................................27
第一節統計圖理解層次測驗............................................................................27
第四章結果分析...................................................................................................36
第一節高、低數學能力對推論與摘要表現之影響........................................37
第二節學生在推論和摘要的表現....................................................................39
第五章綜合討論...................................................................................................45
參考文獻...................................................................................................................49
附錄一統計圖理解層次測驗............................................................................53
附錄二評分標準................................................................................................68

參考文獻

邱皓政（民 99）。量化研究與統計分析（第五版）。台北：五南。
陳幸玫、陳忠信（民100）。北市、新北市國小六年級學童對社會教科書統計圖
的理解能力。教育資料與研究雙月刊，98，125-154。
教育部（2008）。97 年國民中小學九年一貫課程綱要－數學學習領域。2011 年
11 月14 日，取自http://www.edu.tw/EJE/content.aspx?site_content_sn=15326
Berg, C., & Smith, P. (1994). Assessing students’ abilities to construct and interpret
Line Graphs: Disparities between Multiple-Choice and Free-Response
Instruments. Science Education, 78(6), 527-554.
Bertin, J. (1983). Semiology of graphics (2nd ed., W. J. Berg, Trans.). Madison:
University of Wisconsin Press.
Bright, G.W., & Friel, S.N. (1998). Graphical representations: Helping students
interpret data. In S. P. Lajoie (Ed.), Reflections on statistics: Learning, teaching,
and assessment in grades K-12 (pp. 275-295). Mahwah, NJ: Erlbaum.
Carpenter, P. A., & Shah, P. (1998). A model of the perceptual and conceptual
processes in graph comprehension. Journal of Experimental Psychology, 4,
75–100.
Carswell, C. M. (1992). Choosing specifiers: An evaluation of the basic tasks model
of graphical perception. Human Factors, 34, 535-554.
Cleveland, W. S., & McGill, R. (1984). Graphical perception: Theory,
experimentation, and application to the development of graphical methods.
Journal of the American Statistical Association, 77, 541–547.
Cleveland,W. S., & McGill, R. (1985). Graphical perception and graphical methods
for analyzing scientific data. Science, 229, 828–833.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Second
Edition. Hillsdale, NJ: Lawrence Erlbaum Associates.
Curcio, F. R. (1987). Comprehension of mathematical relationships expressed in
graphs. Journal for Research in Mathematics Education, 18, 382-393.
Curcio, F. R. (1989). Developing graph comprehension. Reston, VA: National
Council of Teachers of Mathematics.
Curcio, F. R., & Artz, A. F. (1997). Assessing students’ statistical problem-solving
behaviors in a small-group setting. In I. Gal & J. B. Garfield (Eds.), The
assessment challenge in statistics education (pp. 123–138). Amsterdam: IOS
Press.
Dossey, J. A., Mullis, I. V. S., & Jones, C. O. (1993). Can students do mathematical
Problem solving? Washington, DC: U.S. Department of Education.
Friel, S. N., Curcio, F. R., & Bright, G.W. (2001). Making sense of graphs: Critical
factors in influencing comprehension and instructional implications. Journal for
Research in Mathematics Education, 32, 124-158.
Gal, I. (1993). Reaching out: Some issues and dilemmas in expanding statistics
education. In L. Pereira-Mendoza(Ed.), Introducing data-analysis in the schools:
Who should teach it and how? (pp. 189-203). Voorburg, The Netherlands:
International Statistics Institute.
Gal, I. (1998). Assessing statistical knowledge as it relates to students’’ interpretation
of data. In S. P. Lajoie (Ed.), Reflections on statistics: Learning, teaching, and
assessment in grades K-12 (pp. 275-295). Mahwah, NJ: Erlbaum.
Gattis, M., & Holyoak, K. J. (1996). Mapping conceptual to spatial relations in visual
reasoning. Journal of Experimental Psychology: Learning, Memory, and
Cognition, 22(1), 231-239.
Gillian, D. J., & Lewis, R. (1994). A componential model of human interaction with
graphs: 1. Linear regression modeling. Human Factors, 36, 419–440.
Graesser, A. C., Swamer, S. S., Baggett, W. B., & Sell, M. A. (1996). New models of
deep comprehension. In B. K. Britton & A. C. Graesser (Eds.), Models of
understanding text (pp. 1-32). Mahwah, NJ: Erlbaum.
Jolliffe, F. R. (1991). Assessment of the understanding of statistical concepts. In D.
Vere-Jones (Ed.), Proceedings of the third international conference on teaching
statistics (Vol. 1, pp. 461-466). Voorburg, The Netherlands: International
Statistical Institute.
Kosslyn, S. M. (1989). Understanding charts and graphs. Applied Cognitive
Psychology, 3, 185–225.
Kosslyn, S. M. (1994). Elements of graph design. New York: W. H. Freeman
Larkin, J. H. & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten
thousand words. Cognitive Science, 11(1), 65-100.
Leinhardt, G., Zaslavsky, O., & Stein, M. K. (1990). Functions, graphs, and
graphing: Tasks, learning, and teaching. Review of Educational Research, 60,
1-64.
Legge, G. E., Gu, Y., & Luebker, A. (1989). Efficiency of graphical perception.
Perception and Psychophysics, 46, 365-374.
Lohse, G. L. (1993). A cognitive model of understanding graphical perception.
Human-Computer Interaction, 8, 353–388.
Maichle,U. (1994). Cognitive processes in understanding line graphs. In W.
Schnotz & R. W. Kulhavy (Eds.), Comprehension of graphics (pp. 207-226).
New York: Elsevier Science.
McKnight, C. C. (1990). Critical evaluation of quantitative arguments. In G. Kulm
(Ed.), Assessing higher order thinking in mathematics (pp. 169-185). Washington,
DC: American Association for the Advancement of Science.
Meyer, J., Shinar, D., & Leiser, D. (1997). Multiple factors that determine
performance with tables and graphs. Human Factors, 39, 268-286.
Michalis, I. (2005). Graph comprehension of primary school students. In B. Hudson
& J.Fragner (Eds.), Researching the teaching and learning of mathematics II (pp.
271-293). Linz, The Austria: Trauner.
Mosenthal, P. B., & Kirsch, I. S. (1990a). Understanding graphs and charts, Part I.
Journal of Reading, 33, 371-373.
Mosenthal, P. B., & Kirsch, I. S. (1990b). Understanding graphs and charts, Part II.
Journal of Reading, 33, 454-457.
Pereira-Mendoza, L., & Mellor, J. (1991). Students’ concepts of bar graphs – Some
preliminary findings. In D. Vere-Jones (Ed.), Proceedings of the third
international conference on teaching statistics (Vol. 1, pp. 150–157). Voorburg,
The Netherlands: International Statistical Institute.
Pinker, S. (1990). A theory of graph comprehension. In R. Frele (Ed.), Artificial
intelligence and the future of testing (pp. 73–126). Hillsdale, NJ: Erlbaum.
Preece, J. (1990). Some HCI issues concerned with displaying quantitative
information graphically. In Gorny, P., & Tauber, M. J. (Eds.), Visualization in
Human–Computer Interaction. Springer, New York.
Russell, S. J. (1991). Counting noses and scary things: Children construct their ideas
about data. In D. Vere-Jones (Ed.), In Proceedings of the third international
conference on teaching statistics (Vol. 1, pp. 158–164). Voorburg, Netherlands:
International Statistical Institute.
Shah, P. (2002). Graph comprehension: The role of format, content, and individual
differences. In M. Anderson, M., B. Meyer, & P. Olivier. (Eds.), Diagrammatic
Representation and Reasoning. New York: Springer.
Shah, P., Mayer, R. E., & Hegarty, M. (1999). Graphs as aids to knowledge
construction: signaling techniques for guiding the process of graph
comprehension. Journal of Educational Psychology, 91(4), 690-702.
Shah, P., & Hoeffner, J. (2002). Review of graph comprehension research:
Implications for instruction. Educational Psychology Review,14(1), 47-69.
Shaughnessy, J. M., Garfield, J. & Greer, B. (1996). Data Handling. In A. J. Bishop,
K. Clements, C. Keitel, J. Kilpatrick, & C. Laborde (Eds.), International
Handbook of Mathematics Education (Part 1, pp. 205–237). Dordrecht, The
Netherlands: Kluwer Academic Pblishers.
Stenning, K., & Oberlander, J. (1995). A cognitive theory of graphical and linguistic
reasoning: logic and implementation. Cognitive Science, 19, 97–140.
Szyjka, S., Mumba, F., & Wise, K. C. (2011). Cognitive and Attitudinal Predictors
Related to Line Graphing Achievement among Elementary Pre-service Teachers.
Journal of Science Teacher Education, 22(7), 563-578.
Tversky, B. (2001). Spatial schemas in depictions. In M. Gattis (Ed.) Spatial schemas
and abstract thought (pp. 79-111). Cambridge: MIT Press.
Van Dijk, T. A., & Kintsch, W. (1983). Strategies of discourse comprehension. New
York: Academic Press
Wainer, H. (1992). Understanding graphs and tables. Educational Researcher, 21(1),
14-23.
Zawojewski, J. S., & Heckman, D. J. (1997). What do students know about data
analysis, statistics, and probability? In P. A. Kenney & E. A. Silver (Eds.),
Results from the Sixth Mathematics Assessment of the National Assessment of
Educational Progress (pp. 195-223). Reston, VA: National Council of Teachers
of Mathematics.

指導教授

柯華葳(Hwa-wei Ko)

審核日期

2012-7-26

推文