Literature Index

Displaying 3251 - 3260 of 3326
  • Author(s):
    Michael Martin
    Year:
    2008
    Abstract:
    Analogical thinking is a powerful cognitive tool that leverages knowledge and<br>understanding of familiar ideas and relationships to form knowledge and understanding in a new<br>setting. For students approaching their first statistics class, fear of the unknown can be a major<br>factor in slowing and even stopping learning. Yet many statistical ideas have their roots in<br>thinking with which students are already familiar. Knowing this fact, and how to exploit it<br>through the use of analogy gives us a decisive advantage in the battle for hearts and minds of<br>students who do not yet know how much they need statistics in their lives. I will describe analogy<br>as a tool for teaching statistics, my experiences with its use, and many examples of analogies I<br>have invented, borrowed, stolen, lost then rediscovered, and otherwise acquired.
  • Author(s):
    George Cobb
    Year:
    2013
    Abstract:
    The 1993 inaugural issue of the Journal of Statistics Education (JSE) published an article about a small conference for Principal Investigators (PIs) and co-PIs of twelve projects in statistics education funded by the National Science Foundation (NSF). This twenty-year retrospective (1) offers some personal memories related to the founding of JSE, (2) offers some thoughts about the legacies of the twelve funded projects, (3) sets out a sense of how the conference themes have fared over the last twenty years, and (4) indicates what this might suggest about the future of our profession. In conclusion, I argue (briefly) that at this moment in its history, statistics education faces the biggest opportunity and challenge of its last 40 years.
  • Author(s):
    Watson, J. M.
    Year:
    1992
    Abstract:
    States and local schools face the implementation of the Chance and Data part of a curriculum with no Australian research base from which to make recommendations for the preparation of teachers or for the suggestion of methods and topics realistic to the developmental level of the students. It is the purpose of this paper to suggest such a base.
  • Author(s):
    Shaw, P.
    Editors:
    Vere-Jones, D., Carlyle, S., &amp; Dawkins, B. P.
    Year:
    1991
    Abstract:
    This paper describes a course aimed at mature age students who are lacking in basic mathematical skills and who are anxious about mathematics but who are required to do a service course in statistics. The course aims to improve basic skills and attitudes to mathematics and, in addition, to move students from a rule-based approach to mathematics and statistics to a more flexible one. Flexibility in mathematical thinking is required if students at a later stage are to be able to consider and assess the relative merits of different ways of analysing batches of data. Basic skills and attitudes both before and after the course have been measured using an author-prepared test for the former and an attitude to mathematics [Fennema] test for the latter. Mathematical thinking has been measured by using material based on the SOLO (Structure of the Learned Outcome) taxonomy. There has been some evidence of a change in basic skills and attitudes to mathematics over the duration of the course, but to date there has not been an accompanying change in the level of mathematical thinking.
  • Author(s):
    Julian L. SIMON
    Year:
    1994
    Abstract:
    Simulation is simpler intellectually than the formulaic<br>method because it does not require that one calculate the<br>number of points in the entire sample space and the number<br>of points in some subset. Instead, one directly samples<br>the ratio. This article presents probabilistic problems<br>that confound even skilled statisticians when attacking the<br>problems deductively, yet are easy to handle correctly, and<br>become clear intuitively, with physical simulation. This<br>analogy demonstrates the usefulness of simulation in the<br>form of resampling methods.
  • Author(s):
    Unger C.
    Year:
    1994
    Abstract:
    By applying the Teaching for Understanding Project's framework to classroom situations, both teachers and researchers gained new insights.
  • Author(s):
    Olsen, C.
    Year:
    1998
    Abstract:
    This paper provides the scoring rubric used to score the open-ended questions on the advanced placement statistics examination.
  • Author(s):
    Snee, R. D.
    Year:
    1993
    Abstract:
    There is a growing feeling in the statistical community that significant changes must be made in statistical education. Statistical education has traditionally focused on developing knowledge and skills and assumed that students would create value for the subject in the process. This approach hasn't worked. It is argued that we can help students better learn statistical thinking and methods and create value for its use by focusing both the content and delivery of statistical education on how people use statistical thinking and methods to learn, solve problems, and improve processes. Learning from your experiences, by using statistical thinking in real-life situations, is an effective way to create value for a subject and build knowledge and skills at both the graduate and undergraduate levels. The learnings from psychology and behavioral science are also shown to be helpful in improving the delivery of statistics education.
  • Author(s):
    Shoemaker, A. L.
    Year:
    1996
    Abstract:
    This article takes data from a paper in the Journal of the American Medical Association that examined whether the true mean body temperature is 98.6 degrees Fahrenheit. Because the dataset suggests that the true mean is approximately 98.2, it helps students to grasp concepts about true means, confidence intervals, and t-statistics. Students can use a t-test to test for sex differences in body temperature and regression to investigate the relationship between temperature and heart rate.
  • Author(s):
    Mokros, J. R., &amp; Russell, S.J.
    Year:
    1989
    Abstract:
    We are beginning to identify problems that children and adults have in constructing the notion of average. In addition, we are examining the mathematical and organizational concepts that are needed to successfully solve averaging problems. Even though we are in the midst of this research, we know enough at this point to question the methods usually used to teach averaging in the 4th grade. Children no doubt can be taught to do the appropriate calculation, but our research shows that understanding of central tendency is far more complex. Given a good deal of experience in working with data sets, children do show a deeper, although by no means a complete, understanding of average. Experiences in which children are given more opportunities to connect their informal strategies with their formal mathematical knowledge seem to facilitate this deeper understanding.
    Location:

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