A Case Study on Pre-Service Teacher Students’ Interaction with Graphical Artefacts
Downloads
Abstract
This study reports from a pre-service teacher’s online learning and assessment activity on determining variability of two graphical artefacts. Using a critical-analytical perspective to data, the present study indicate that the prospective teachers surveyed showed awareness of relevant subject specific operators and methods however, these seem not be well coordinated and were submerged in forms of expressions characterized by intuitive methods and everyday language. Significantly the prospective teachers seemed to substitute statistical and mathematical methods with explanatory metaphors which while providing room for deeper subject specific engagement were however, only used superficially. Their reliance on everyday forms of expression and visual perception is perceive as a factor that might have hampered their effective choice and application of relevant subject specific tools and forms of expression. This observation puts to task the role of informal methods in statistics education.Downloads
References
Alacaci, C., Lewis, S., O'Brien, G. E. & Jiang, Z. (2011). Pre-service elementary teachers’ understandings of graphs. EURASIA Journal of Mathematics, Science and Technology Education, 7, 3-14.
Google Scholar CrossrefBakker, A. (2004a). Design research in statistics education: On symbolizing and computer tools. Utrecht, the Netherlands: CD Beta Press.
Google Scholar CrossrefBakker, A. (2004b). Reasoning about shape as a pattern in variability. Statistics Education Research Journal, 3, 64- 83.
Google Scholar Crossrefhttp://www.stat.auckland.ac.nz/~iase/publications.php?show=serj
Google Scholar CrossrefBakker, A. & Gravemeijer K.P.E. (2004) Learning to reason about distribution. In D. Ben-Zvi & J. Garfield (Eds.), The challenges of developing statistical literacy, reasoning, and thinking (pp. 147-168). Dordrecht, the Netherlands: Kluwer Academic Publishers.
Google Scholar CrossrefBiehler, R (1997). Students’ difficulties in practicing computer supported data analysis – some hypothetical generalizations from results of two exploratory studies. In J. Garfield & G. Burrill (Ed.), Research on the role of technology in teaching and learning statistics (pp. 169-190). Voorburg, The Netherlands: International Statistical Institute.
Google Scholar CrossrefBen-Zvi, D. & Arcavi, A. (2001). Junior high school students’ construction of global views of data and data representations. Educational Studies in Mathematics, 45, 36-65.
Google Scholar CrossrefBen-Zvi, D., & Friedlander, A. (1997). Statistical thinking in a technological environment. In J. Garfield & G. Burrill (Eds.), Research on the Role of Technology in Teaching and Learning Statistics, (pp. 45-55). Voorburg, The Netherlands: International Statistical Institute.
Google Scholar CrossrefBorasi, R., & Rose, B. J. (1989). Journal writing and mathematics instruction. Educational Studies in Mathematics, 20(4), 347-365.
Google Scholar CrossrefClarke, D. J., Waywood, A., & Stephens, M. (1993). Probing the structure of mathematical writing. Educational Studies in Mathematics, 25, 235-250.
Google Scholar CrossrefCooper, L. L., & Shore, S. F. (2008). Students’ Misconceptions in Interpreting Center and Variability of Data Represented via Histograms and Stem-and-leaf Plots. Journal of Statistics Education . Retrieved September, 14, 2012 from
Google Scholar Crossrefwww.amstat.org/publications/jse/v16n2/cooper.html
Google Scholar CrossrefCooper, L. L., & Shore, S. F. (2010). The effects of data and graph type on concepts and visualizations of variability. Journal of Statistics Education. Retrieved September, 14, 2012 from
Google Scholar Crossrefwww.amstat.org/publications/jse/v18n2/cooper.html
Google Scholar CrossrefDaniels, H. (2008) Vygotsky and Research, London: Routledge.
Google Scholar CrossrefdelMas, R., & Liu, Y. (2005). Exploring students’ conceptions of the standard deviation. Statistics Education Research Journal, Retrieved September, 14, 2012 from
Google Scholar Crossrefhttp://www.stat.auckland.ac.nz/~iase/publications.php?show=serj
Google Scholar CrossrefdelMas, R., Garfield, J., & Ooms, A. (2005). Using assessment items to study students’ difficulty reading and interpreting graphical representations of distributions. In: Makar, K. (Ed.) Proceedings of the Fourth International Research Forum on Statistical Reasoning, Thinking, and Literacy (SRTL-4), University of Auckland, New Zealand, 2–7 July. Brisbane: University of Queensland
Google Scholar Crossrefhttps://app.gen.umn.edu/artist/articles/SRTL4_ARTIST.pdf
Google Scholar CrossrefDysthe, O. (red). (2003). Dialogue, samspel och lärande. Studentlitteratur, Lund
Google Scholar CrossrefDuval, R ( 2008). Eight problems for a semiotic approach in mathematics education. In: Luis Radford, Gert Schubring & Falk Seeger (Eds.), Semiotics in mathematics education, (pp. 39-61). Rotterdam: Sense.
Google Scholar CrossrefEmig, J. (1977). Writing as a mode of learning. College Composition and Communication, 28, 122-128.
Google Scholar CrossrefFranklin, C. Kader, G ….. (2006). Guidelines for assessment and instruction in statistics education (GAISE) report: A Pre-K–12 curriculum framework
Google Scholar CrossrefGal, I. (2002). Adults' Statistical Literacy: Meanings, Components, Responsibilities: International Statistical Review, 70 , 1-25
Google Scholar CrossrefGarfield, J. (1995), "How students learn statistics," International Statistical Review, 63, 25-34.
Google Scholar CrossrefGarfield, J. (2002). The Challenge of Developing Statistical Reasoning. Journal of Statistics Education. Retrieved September, 14, 2012 from
Google Scholar Crossrefwww.amstat.org/publications/jse/v10n3/garfield.html
Google Scholar CrossrefGarfield, J. & Ben-Zvi, D. (2007a). The discipline of statistics education. Retrieved January 25, 2012, from www.ugr.es/~icmi/iase_study/BackgroundpaperGarfield.pdf
Google Scholar CrossrefGarfield, J. & Ben-Zvi, D. (2007b) How students learn statistics revisited:a current review of research on teaching and learning statistics International Statistical Review (2007), 75 (3), 372-396
Google Scholar CrossrefGarfield, J. & Ben-Zvi, D. (2004).Statistical literacy, reasoning, and thinking: goals, definations and challenges. In D. Ben-Zvi & J. Garfield (Eds.), The challenges of developing statistical literacy, reasoning, and thinking (pp. 353-373). Dordrecht, the Netherlands: Kluwer Academic Publishers
Google Scholar CrossrefGonzález, T., Espinel, C., & Ainley, J. (2011). Teachers’ graphical competence. In C. Batanero, G. Burrill & C. Reading (Eds.). Teaching Statistics in School Mathematics. Challenges for Teaching and Teacher Education. A Joint ICMI and IASE Study. New York: Springer.
Google Scholar CrossrefGordon, T. (1986). Is the standard deviation tied to the mean? Teaching Statistics, 8(2), 40-2.
Google Scholar CrossrefGroth, R. (2005). An investigation of statistics in two different contexts: detecting a signal in a noisy process and determining a typical value. Journal of mathematical behavior 24(2), 109-124
Google Scholar CrossrefGupta, S.C. (1992) Fundamentals of statistics. Bombay, India: Himalaya Publishing House.
Google Scholar CrossrefHärdle, W., Klinke, S. & Ziegenhagen, U. (2007). On the utility of e-learning in statistics (SFB 649 discussion paper, No. 2007, 050) Retrieved from the website of Lebniz information centre for economics http://www.econstor.eu/bitstream/10419/25222/1/558612121.PDF
Google Scholar CrossrefKader, G. & Perry, M. (2007). Variability for categorical variables Journal of Statistics Education, 15 (2) http://www.amstat.org/publications/jse/v15n2/kader.html
Google Scholar CrossrefKonold, C., Higgins, T., Russell, S. J., & Khalil, K. (2004). Data seen through different lenses. Amherst, MA: University of Massachusetts. Retrieved June, 14, 2012 from
Google Scholar Crossrefwww.umass.edu/srri/serg/papers/index.html.
Google Scholar CrossrefKonold, C. & Pollatsek, A. (2004). Conceptualizing an average as a stable feature of a noisy process. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning and thinking (pp.169-199) Dordrecht: Kluwer Academic Publishers.
Google Scholar CrossrefLoosen, F., Lioen, M. & Lacante, M. (1985). The standard deviation: some drawbacks to an intuitive approach. Teaching Statistics, 7(1), 2-5.
Google Scholar CrossrefLowrie, T., Diezmann, C. M. & Logan, T. (2011). Understanding graphicacy: Students’ making sense of graphics in mathematics assessment tasks. International Journal for Mathematics Teaching and Learning. Retrieved September, 14, 2012 from
Google Scholar Crossrefhttp://www.cimt.plymouth.ac.uk/journal/default.htm
Google Scholar CrossrefMakar, K., & Confrey, J. (2004). Secondary teachers’ reasoning about comparing two groups. In D. Ben-Zvi & J. Garfield (Eds.), The challenges of developing statistical literacy, reasoning, and thinking (pp.353-373). Dordrecht, the Netherlands: Kluwer Academic Publishers.
Google Scholar CrossrefMonteiro, C., & Ainley, J. (2007). Investigating the interpretation of media graphs among student teachers. International Electronic Journal of Mathematics Education 2 (3), 188-207.
Google Scholar CrossrefAUTHORS. (in press).
Google Scholar CrossrefPerry, M. & Kader, G. (2005). Variation as Unalikeability. Teaching Statistics, 27 (2), 58-60.
Google Scholar CrossrefPfannkuch, M. (2006). Comparing box plot distributions: a teacher’s reasoning SERJ
Google Scholar CrossrefPfannkuch, M. (2007) year 11 students informal inferential reasoning: a case study about the interpretation of box plots. International Electronic Journal of Mathematics Education 2(3), 149-167.
Google Scholar CrossrefProdromou, T. & Pratt, D. (2006). The role of causality in the co-ordination of two perspectives on distribution within a virtual simulation. Statistics Education Research Journal, 5(2), 69-88, http://www.stat.auckland.ac.nz/serj
Google Scholar CrossrefRadford, L. (2013). Three key concepts of the theory of objectification: knowledge, knowing and learning. REDIMAT -Journal of Research in Mathematics Education,1, 7-44
Google Scholar CrossrefReading, C & Shaughnessy, J. M. (2004). Reasoning about variation. In D. Ben-Zvi and J. Garfield (Eds.), The Challenge of Developing Statistical Literacy, Reasoning and Thinking, (pp. 201-226.) Dordrecht, The Netherlands: Kluwer Academic Publishers
Google Scholar CrossrefShaughnessy, J. M. (2007). Research on statistics learning and reasoning in Lester, second handbook of
Google Scholar CrossrefStern, E., Aprea, C., & Ebner, H. G. (2003). Improving cross-content transfer in text processing by means of active graphical representation. Learning and Instruction, 13(2), 191-203.
Google Scholar CrossrefWatson, J. M. & Moritz, J. (2001): development of reasoning associated with pictorial graphs: representing, interpreting and predicting. Educational studies in mathematics ,48, 47-81
Google Scholar CrossrefWild, C. (2006). The concept of distribution, Statistics Education Research Journal, 5(2), 10-26.
Google Scholar CrossrefZieffler, A., Garfield, J., delMas, R., Le, L., Isaak, R., Bjonsdottir, A, & Park, J. (2011) Publishing in SERJ an analysis of papers from 2002-2009. Statistics Education Research Journal Retrieved September, 14, 2012 from
Google Scholar Crossrefhttp://www.stat.auckland.ac.nz/serj
Google Scholar CrossrefDownloads
Published
Almetric
Dimensions
Issue
Section
License
Authors retain copyright and grant the journal the right of first publication but allow anyone to share: (unload, , reprint, distribute and/or copy) and adapt (remix, transform reuse, modify,) for any proposition, even commercial, always quoting the original source.
