研究生: |
趙君培 Chun-Pei Chao |
---|---|
論文名稱: |
國三學生對分佈特徵與分佈概念了解情形之研究 |
指導教授: |
譚克平
Tam, Hak-Ping |
學位類別: |
碩士 Master |
系所名稱: |
科學教育研究所 Graduate Institute of Science Education |
論文出版年: | 2009 |
畢業學年度: | 97 |
語文別: | 中文 |
論文頁數: | 131 |
中文關鍵詞: | 分佈 、九年一貫課程綱要 、統計 |
英文關鍵詞: | Distribution, Grade 1-9 Curriculum, Statistics |
論文種類: | 學術論文 |
相關次數: | 點閱:180 下載:5 |
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在資訊發達的現代社會,統計是必須具備的知能,分佈是統計中的重要概念,具分佈概念可掌握整體資料。本研究的目的為探討國三學生統計分佈特徵與分佈概念了解情形,並以此探討「九年一貫數學學習領域課程綱要」中統計分佈的編排。
本研究採調查研究法,研究對象為台北地區國三學生276名,以自編之經過效化的「統計分佈概念試題」為研究工具,得到下列發現:
1. 學生在「中心量數的概念」較「求取中心量數」表現差。
2. 學生在「變異量數的概念」較「求取變異量數」表現差。
3. 學生缺乏「形狀」概念。
4. 學生不擅描述資料分佈,多數學生僅使用一個分佈特徵描述一個資料分佈。
5. 若未給學生所有的資料點,多數學生無法畫出適當的統計圖形呈現分佈。
從本研究得知:在目前課程綱要下,國三學生較擅長計算量數,但分佈概念不足,探討「九年一貫課程綱要」後,提出兩點建議:
1. 課程內容宜加入統計分佈概念,包括分佈特徵。
2. 課程內容應重視分佈特徵的概念,尤其是「形狀」概念。
Modern society is abundant with quantitative information. To be an effective member of the society, every citizen should have basic statistics knowledge and skill. Distribution is a core concept in statistics, those who understand it well will know a lot about the data they have at hand. The main purpose of this study was to explore ninth graders’ understanding of the concept of distribution and its characteristics. Based on their performances, this study would then analyze and reflect on the arrangement of the content on distribution in the Guidelines of Mathematics Learning Area in Grade 1-9 Curriculum.
A self-designed questionnaire on the concept of distribution was validated on a group of 276 ninth graders’ in the Taipei Area. Further analysis revealed the following results:
1. Students’ performance in items related to the concept of central tendency was inferior to their ability in finding the central tendency indices.
2. Students’ performance in items related to the concept of variation was inferior to their ability in computing the variation indices.
3. Students were weak in their understanding of the shape of a distribution.
4. Students were not good at describing the distribution of a data set. Furthermore, most of them would only used one of the characteristics of a distribution to describe the distribution.
5. If students were not given all of the data values, most of them could not represent the distribution using appropriate statistical graphs.
As mentioned above, students were proficient in computing the indices of center and variation, but they were weak in their understanding of the concept in distribution. Based on these findings, this author analyzed and reflected on the arrangement of the content on distribution in the Grade 1-9 Curriculum and offered the following suggestions:
1. The content on the concept of distribution together with its characteristics should be increased and be more organized in the curriculum.
2. The various characteristics of a distribution should be emphasized in the curriculum, especially with respect to the shape of a distribution.
教育部(2003)。國民中小學九年一貫課程綱要數學領域。台北市:教育部。
譚克平(2007)。國中教導盒狀圖的建議及介紹如何用EXCEL製作盒狀圖。科學教育月刊,305,20-34。
蘇國樑(1994)。國小兒童統計概念之分析(I)統計資料分佈概念之分析。行政院國家科學委員會專題研究成果報告(報告編號:NSC83-0111-S180-002-N),未出版。
羅傑‧波凱斯。(1995)。統計學辭典。台北:貓頭鷹。
Moore, D. S.(2002)。統計學的世界。(鄭惟厚譯)。台北市:天下遠見。(原著出版年:2001)
Australian Education Council (1991), A national statement on mathematics for Australian schools, Melbourne: Curriculum Corporation.
Bakker, A. (2004). Design research in statistics education: on symbolizing and
computer tools. Utrecht, the Netherlands: CD Beta Press.
Bakker, A., & Gravemeijer, K. P. E. (2004). Learning to reason about distribution In D. Ben-Zvi & J. B. Garfield (Eds.), The challenge of developing statistical literacy, reasoning and thinking (pp. 147-168). Dordrecht, The Netherlands: Kluwer Academic Publishers.
Bakker, A., & Hoffmann, M. H. G. (2005). Diagrammatic reasoning as the basis for developing concepts: a semiotic analysis of students' learning about statistical distribution. Educational Studies in Mathematics, 60(3), 333-358.
Ben-Zvi, D. (2002, July). Seventh grade students' sense making of data and data representations. Paper presented at the Proceedings of the Sixth International Conference on Teaching Statistics, Cape Town, South Africa.
Ben-Zvi, D., & Arcavi, A. (2001). Junior high school students' construction of global views of data and data representations. Educational Studies in Mathematics, 45, 35-65.
Cain, R. B. (1972). Elementary statistical concepts. Philadelphia: Saunders.
Ciancetta, M. A. (2007). Statistics students reasoning when comparing distributions of data. Unpublished doctoral dissertation, State University of Portland, Portland.
Bright, G., & Friel, S. (1998). Graphical representations: helping students interpret data. In S. P. Lajoie (Ed.), Reflections on statistics: leaning, teaching, and assessment in grades K-12. Mahwah, New Jersey: Lawrence Erlbaum.
Capraro, M. M., Kulm, G., & Capraro, R. M. (2005). Middle grades: Misconceptions in statistical thinking. School Science and Mathematics Journal, 105(4), 165-171.
Cobb, P. (2002). Modeling, symbolizing, and tool use in statistical data analysis. In K. Gravemeijer, R. Lehrer, B. v. Oers & L. Verschaffel (Eds.), Symbolizing, Modeling and Tool Use in Mathematics Education (pp. 171-195). Netherland: Kluwer Academic.
Cooper, L. L., & Shore, F. S. (2008). Students' misconceptions in interpreting center and variability of data represented via histograms and stem-and-leaf plots. Journal of Statistics Education, 16(2), Retrieved Jan 31, 2009, from the World Wide Web: http://www.amstat.org/publications/jse/v16n2/cooper.pdf
Delmas, R., Garfield, J., & Ooms, A. (2005, July). Using assessment items to study students' difficulty reading and interpreting graphical representations of distributions. Paper presented at the Proceedings of the Fourth International Research Forum on Statistical Reasoning, Literacy, and Reasoning, Auckland, New Zealand.
Freund, J. E., & Williams, F. J. (1966). Dictionary/outline of Basic Statistics. New York: McGraw-Hill.
Gal, I. (1998). Assessing statistical knowledge as it relates to students' interpretation of data. In S. P. Lajoie (Ed.), Reflections on statistics: leaning, teaching, and assessment in grades K-12. Mahwah, New Jersey: Lawrence Erlbaum.
Gallimore, M. (1990, August). Graphicacy in the primary curriculum. Paper presented at the Proceedings of Third International Conference on Teaching Statistics.
Garfield, J. B., & Ben-Zvi, D. (2004). Research on statistical literacy, reasoning, and thinking Issues, challenges, and implications. In D. Ben-Zvi & J. B. Garfield (Eds.), The challenge of developing statistical literacy, reasoning and thinking (pp. 397-409). Dordrecht, The Netherlands: Kluwer Academic Publishers.
Garfield, J. B., & Ben-Zvi, D. (2008). Learning to reason about distribution. In J. B. Garfield & D. Ben-Zvi (Eds.), Developing students' statistical reasoning (pp. 165-186). Dordrecht, The Netherlands: Kluwer Academic Publishers.
Gove, P. B. (1972). Webster's third new international dictionary of the English language, unabridged (3 ed.). Springfield, Mass: G. & C. Merriam Company.
Groth, R. E., & Bergner, J. A. (2006). Preservice elementary teachers' conceptual and procedural knowledge of mean, median, and mode. Mathematical Thinking and Learning, 8(1), 37-63.
Konold, C., Higgins, T., & Russell, S. J. (2000, October). Developing statistical perspectives In the elementary grades. Paper presented at the Proceeding of the 22nd Annual Meeting of the North American Chapter of International Group for the Psychology of Mathematics Education, Tucson, Arizona.
Konold, C., & Pollatsek, A. (2002). Data analysis as the search for signals in noisy processes. Journal for Research in Mathematics Education, 33(4), 259-289.
Konold, C., Robinson, A., & Khalil, K. (2002, July). Students' use of modal clumps to summarize data. Paper presented at the Proceedings of the Sixth International Conference on Teaching Statistics, Cape Town, South Africa.
Leavy, A. (2006). Using data comparison to support a focus on distribution: examining preservice teachers' understanding of distribution when engaged in statistical inquiry. Statistics Education Research Journal, 5(2), 89-114.
Lehrer, R. (2007, July). Introducing students to data representation and statistics. In J. Watson & K. Beswick (Eds.), Proceedings of the 30th annual conference of the Mathematics Education Research Group of Australasia. Tasmania: MERGA.
MacDonald, T. H. (2007). Basic concepts in statistics and epidemiology. Abingdon: Radcliffe.
McClain, K., Cobb, P., & Gravemeijer, K. (2000). Supporting students' ways of reasoning about data. In M. J. Burke & F. R. Curcio (Eds.), Learning Mathematics for a New Century (pp. 174-187).
McClain, K., McGatha, M., & Hodge, L. L. (2000). Improving data analysis through discourse. Mathematics Teaching in the Middle School, 5(8), 548-553.
McGatha, M., Cobb, P., & McClain, K. (2002). An analysis of students' initial statistical understandings: developing a conjectured learning trajectory. Journal of Mathematical Behavior, 21, 339-355.
Makar, K., & Confrey, J. (2005). "Variation-Talk": Articulating meaning in statistics. Statistics Education Research Journal, 4(1), 27-54.
Meletiou, M., & Lee, C. (2002, July). Student understanding of histograms: a stumbling stone to the development of intuitions about variation. Paper presented at the Proceedings of the Sixth International Conference on Teaching Statistics, Cape Town, South Africa.
Meletiou-Mavrotheri, M., & Stylianou, D. A. (2003, July). Graphical representation of data: the effect of the use of dynamical statistics technological tool. Paper presented at the Proceedings of the Sixth International Conference on Computer Based Learning in Science, Nicosia, Cyprus.
Ministry of Education (1992). Mathematics in the New Zealand Curriculum. Wellington: Learning Media.
National Council of Teachers of Mathematics (1989). Curriculum and evaluation standards for school mathematics. Reston, VA: Author.
National Council of Teachers of Mathematics (2000). Principles and standards for school mathematics. Reston, VA: Author.
Nelson, D. (Ed.). (2004). The Penguin dictionary of statistics. New York: Penguin.
Pfannkuch, M. (2006). Comparing box plot distributions: a teacher's reasoning. Statistics Education Research Journal, 5(2), 27-45.
Pfannkuch, M., Budgett, S., Parsonage, R., & Horring, J. (2004, July). comparison of data plots: building a pedagogical framework. Paper presented at the 10th International Congress on Mathematical Education, Copenhagen, Denmark.
Pfannkuch, M., & Reading, C. (2006). Reasoning about distribution: a complex process. Statistics Education Research Journal, 5(2), 4-9.
Rasmussen, S. (1992). An introduction to statistics with data analysis. Pacific Grove: Brooks/Cole Pub. Co.
Reading, C., & Reid, J. (2006). An emerging hierarchy of reasoning about distribution: from a variation perspective. Statistics Education Research Journal, 5(2), 46-68.
Shaughnessy, M. (2008). What Do We Know about Students' Thinking and Reasoning about Variability in Data. Retrieved Sep 16, 2008, from the World Wide Web: http://www.nctm.org/uploadedFiles/Research_News_and_Advocacy/Research/Clips_and_Briefs/Research_brief_11_-_Variability.pdf
Shaughnessy, J. M., & Pfannkuch, M. (2002). How faithful is old faithful? statistical thinking: a story of variation and prediction. Mathematics Teacher, 95(4), 252-259.
Upton, G., & Cook, I. (Eds.). (2006). A dictionary of statistics (2 ed.). New York: Oxford University Press.
Watson, J. M., Kelly, B. A., Callingham, R. A., & Shaughnessy, J. M. (2003). The measurement of school students' understanding of statistical variation. International Journal of Mathematical Education in Science and Technology, 34(1), 1-29.
Watkins, A. E., Scheaffer, R. L., & Cobb, G. W. (2004). Statistics in action: understanding a world of data. Emeryville: Key Curriculum Press.
Wild, C. (2006). The concept of distribution. Statistics Education Research Journal, 5(2), 10-26.
Zawojewski, J. S., & Shaughnessy, J. M. (2000). Mean and median: Are they really so easy? . Mathematics Teaching in the Middle School, 5(7), 436-440.