Literature Index

Displaying 3301 - 3310 of 3326
  • Author(s):
    Friel, S. N.
    Editors:
    Ferrucci, B. J., Shaughnessy, M.
    Year:
    2002
    Abstract:
    Statistics are more pervasive than ever. We encounter statistical information in newspapers, magazines, advertisements, and on the radio and television. Political, social, economic, scientific, and personal decisions are made on the basis of data. To operate effectively in our world, we must be able to make senes of statistical information. There are new ways to think about the discipline of statistics and about the ways students develop their understanding of statistics.<br>Statistics learning involves a process of doing meaningful statistics (Ben-Zvi, 2000). This process includes four key components: posing questions, collecting data, analyzing distributions, and interpreting results. This process is dynamic, with interactions among the four components being the norm.
  • Author(s):
    Gal, I., &amp; Garfield, J. B.
    Editors:
    Gal, I., &amp; Garfield, J.
    Year:
    1994
    Abstract:
    The enclosed summaries were provided by working group facilitators and placed in the public domain in an unedited form to inform dialouge about and contribute to the improvement of assessment practices in statistics education. A formal conference report is in the planning stage.
  • Author(s):
    Biehler, R.
    Editors:
    Rossman, A., &amp; Chance, B.
    Year:
    2006
    Abstract:
    Pairs of students use the computer software Fathom for working on problems from Exploratory Data Analysis. The exploratory study was interested in identifying how the software as a tool supports or hinders students' thinking. Working styles of students related to distributional thinking in the context of group comparison tasks were studied.
  • Author(s):
    Rossman, A.
    Editors:
    Garfield, J. B. &amp; Burrill, G.
    Year:
    1997
    Abstract:
    Technology has been used as an active learning tool in Workshop Statistics, a project that involved the development and implementation of curricular materials which guide students to learn fundamental statistical ideas through self-discovery. Using the workshop approach, the lecture-format was completely abandoned. Classes are held in microcomputer-equipped classrooms in which students spend class-time working<br>collaboratively on activities carefully designed to enable them to discover statistical concepts, explore statistical principles, and apply statistical techniques.<br><br>The workshop approach uses technology in three ways. First, technology is used to perform the calculations and present the visual displays necessary to analyze real datasets, which are often large and cumbersome. Freeing students from these computational chores also empowers the instructor to focus attention on the understanding of concepts and interpretation of results. Second, technology is used to conduct simulations, which allow students to visualize and explore the long-term behavior of sample statistics under repeated random sampling. Whereas these two uses of technology are fairly standard, the most distinctive use of technology within the workshop approach is to enable students to explore statistical phenomena. Students make predictions about a statistical property and then use the computer to investigate their predictions, revising their predictions and iterating the process as necessary.
  • Author(s):
    Amanda S. Williams
    Year:
    2013
    Abstract:
    Statistics anxiety is a problem for most graduate students. This study investigates the relationship between intolerance of uncertainty, worry, and statistics anxiety. Intolerance of uncertainty was significantly related to worry, and worry was significantly related to three types of statistics anxiety. Six types of statistics anxiety were significantly lower by the end of the semester.
  • Author(s):
    Pereira-Mendoza, L.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    One important part of statistical education is the training of teachers. It would seem to the author that while most teacher education programmes for primary teachers include mathematics education courses, they do not specifically address statistical education. In addition, teachers who enter these programmes would have taken mathematics in school and possibly at post-secondary institutions, but their exposure to statistics would have been limited. Since statistical thinking is different from other forms of thinking, the situation seems to have implications for teacher training. Reasoning under uncertainty is a different way of looking at the world. An accountant may be very good at what he or she does, but the author, for one, would not like an accountant to perform surgery. This paper will raise some questions associated with statistical knowledge as it applies to primary teachers.
  • Author(s):
    Peterson, R. S.
    Year:
    1988
    Abstract:
    This report discusses various techniques to teaching statistics: Writing, Concepts, Essay Exams, Precis and Note cards.
  • Author(s):
    John P. Holcomb
    Year:
    2006
    Abstract:
    This webinar will present a quick overview of assessment methods related to student writing assignments and data analysis projects. Beginning with short writing assignments, we will progress through a range of different approaches to projects at the introductory course level. On-line resources containing existing project ideas will be shown along with ideas for creating one's own projects. We will also discuss several approaches to evaluating the range of assignments.
  • Author(s):
    Joy Jordan
    Year:
    2008
    Abstract:
    Writing can be an effective instrument for students learning new concepts, and there is a plethora of writing-to-learn research. This Webinar will summarize important findings from the writing literature, as well as provide specific writing-assignment examples for the introductory statistics classroom.
  • Author(s):
    Beins, B. C.
    Year:
    1993
    Abstract:
    Students in four statistics classes received different amounts of guidance and instruction in interpretive skills. Students who wrote press releases free of statistical jargon acquired better computational and interpretive skills than did students in a traditional class. Emphasis on interpretation was not associated with greater conceptual knowledge. Writing assignments appear to focus students' attention on the context and rationale for the statistics. This technique can also be used in other courses.

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The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education

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