Literature Index

Displaying 1 - 10 of 3040
  • Author(s):
    Khalil, K.I., & Konold, C.
    Year:
    2002
    Abstract:
    In this experiment, we investigate the correspondence between how graph-readers visually inspect a graph to answer a comparison question about two groups and the justifications they offer. We recorded how people visually inspected graphs using a device that restricted how much data they could see at any given time. Students offered a variety of justifications for why two groups differed (e.g., slices, cut-points, modal clumps), and these appear to correspond to how they visually parsed the data.
  • Author(s):
    Wiggins, G.
    Year:
    2001
    Abstract:
    The result of students' endless exposure to typical tests is a profound lack of understanding about what mathematics is:"Perhaps the greatest difficulty in the whole area of mathematics concerns students' misapprehension of what isactually at stake when they are posed a problem. . . . [S]tudents are nearly always searching for [how] to follow the algorithm. . . . Seeing mathematics as a way of understanding the world . . . is a rare occurrence."9 Surely this has more to do with enculturation via the demands of school, than with some innate limitation.10
  • Author(s):
    Trickett, S., Trafton, J. G., Saner, L., & Schunn, C.
    Editors:
    Lovett, M. C., & Shah, P.
    Year:
    2007
  • Author(s):
    Saldanha, L.
    Editors:
    Thompson, P.
    Year:
    2004
    Abstract:
    This study explores the reasoning that emerged among eight high school juniors and seniors as they participated in a classroom teaching experiment addressing stochastic conceptions of sampling and statistical inference. Toward this end, instructional activities engaged students in embedding sampling and inference within the foundational notion of sampling distributions - patterns of dispersion that one conceives as emerging in a collection of a sample statistic's values that accumulate from re-sampling.<br>The study details students' engagement and emergent understandings in the context of<br>instructional activities designed to support them. Analyses highlight these components: the design of instructional activities, classroom conversations and interactions that emerged from students' engagement in activities, students' ideas and understandings that emerged in the process, and the design team's interpretations of students' understandings. Moreover, analyses highlight the synergistic interplay between these components that drove the unfolding of the teaching experiment over the course of 17 lessons in cycles of design, engagement, and interpretation. These cycles gave rise to an emergent instructional trajectory that unfolded in four interrelated phases of instructional engagements:<br>Phase 1: Orientation to statistical prediction and distributional reasoning;<br>Phase 2: Move to conceptualize probabilistic situations and statistical unusualness;<br>Phase 3: Move to conceptualize variability and distribution;<br>Phase 4: Move to quantify variability and extend distribution.<br>Analyses reveal that students experienced significant difficulties in conceiving the distribution of sample statistics and point to possible reasons for them. Their difficulties centered on composing and coordinating imagined objects with actions into a hierarchical structure in re-sampling scenarios that involve: a population of items, selecting items from the population to accumulate a sample, recording the value of a sample statistic of interest, repeating this process to accumulate a collection of data values, structuring such collections and conceiving patterns within and across them in ways that support making statistical inferences.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/dissertations/04.Saldanha.Dissertation.pdf
  • Author(s):
    Martin, M. A.
    Year:
    2003
    Abstract:
    Students often come to their first statistics class with the preconception that statistics is confusing and dull. This problem is compounded when even introductory techniques are steeped in jargon. One approach that can overcome some of these problems is to align the statistical techniques under study with elements from students' everyday experiences. The use of simple physical analogies is a powerful way to motivate even complicated statistical ideas. In this article, I describe several analogies, some well known and some new, that I have found useful. The analogies are designed to demystify statistical ideas by placing them in a physical context and by appealing to students' common experiences. As a result, some frequent misconceptions and mistakes about statistical techniques can be addressed.
    Location:
    http://www.amstat.org/publications/jse/v11n2/martin.html
  • Author(s):
    Makar, K. &amp; Confrey, J.
    Year:
    2005
    Abstract:
    Little is known about the way that teachers articulate notions of variation in their own words. The study reported here was conducted with 17 prospective secondary math and science teachers enrolled in a preservice teacher education course which engaged them in statistical inquiry of testing data. This qualitative study examines how these preservice teachers articulated notions of variation as they compared two distributions. Although the teachers made use of standard statistical language, they also expressed rich views of variation through nonstandard terminology. This paper details the statistical language used by the prospective teachers, categorizing both standard and nonstandard expressions. Their nonstandard language revealed strong relationships between expressions of variation and expressions of distribution. Implications and the benefits of nonstandard language in statistics are outlined.
    Location:
    http://www.stat.auckland.ac.nz/~iase/serj/SERJ4(1).pdf
  • Author(s):
    McNab, S. L., Moss, J., Woodruff, E., &amp; Nason, R.
    Editors:
    Burrill, G. F.
    Year:
    2006
    Abstract:
    This article describes a teaching study with fifth- and sixth-grade students in which they explored some of issues involved in critically examining data such as questioning the underlying assumptions. Students generated their own mathematical models as a way of understanding a real-life situation.
  • Author(s):
    Demetrulias, D. M.
    Year:
    1988
    Abstract:
    Argues that the teaching of statistics can be freed from the tedium of routine and repetitive calculations with the use of several creative approaches. Concludes that these approaches enable students to invent and seek applications as a result of their own initiative and understanding. (MS)
  • Author(s):
    Schrage, G.
    Year:
    1983
    Abstract:
    I am not an expert in the theory of decision making, rather I am concerned with mathematics education and teacher training. Within the frame of this task one of my special interests is teaching statistics. Statistics - to use a definition of W. A. Wallis and H. W. Roberts - is a body of methods for making decisions in the face of uncertainty., and that is the subject of our conference.
  • Author(s):
    Bibby, J.
    Editors:
    Davidson, R., &amp; Swift, J.
    Year:
    1986
    Abstract:
    Episodes recounted in this paper illustrate the evolution of statistics as a discipline and as a profession. The two are indissolubly linked, and it is useful to remember this as we contemplate present-day development.

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