Literature Index

Displaying 91 - 100 of 3326
  • Author(s):
    Chervany, N. L., Collier, R. O. Jr., Fienberg, S. E., Johnson, P. E., & Neter, J.
    Year:
    1977
    Abstract:
    This paper proposes a framework for the development of instruments to measure content learning and problem-solving skills for the introductory statistics course. This framework is based upon a model of the problem-solving process central to statistical reasoning. The framework defines and interrelates six measurement tasks: (1) subjective reports; (2) reports concerning truth, falsity, or equivalence; (3) supply the appropriate missing information in a message; (4) answer a question based upon a specific message; (5) reproduce a message; and (6) carry out a procedure.
  • Author(s):
    Katie Makar and Andee Rubin
    Year:
    2009
    Abstract:
    Informal inferential reasoning has shown some promise in developing students' deeper understanding of statistical processes. This paper presents a framework to think about three key principles of informal inference - generalizations 'beyond the data,' probabilistic language, and data as evidence. The authors use primary school classroom episodes and excerpts of interviews with the teachers to illustrate the framework and reiterate the importance of embedding statistical learning within the context of statistical inquiry. Implications for the teaching of more powerful statistical concepts at the primary school level are discussed.
  • Author(s):
    ANDREW ZIEFFLER, JOAN GARFIELD, ROBERT DELMAS & CHRIS READING
    Year:
    2008
    Abstract:
    Informal inferential reasoning is a relatively recent concept in the research literature.<br>Several research studies have defined this type of cognitive process in slightly<br>different ways. In this paper, a working definition of informal inferential reasoning<br>based on an analysis of the key aspects of statistical inference, and on research from<br>educational psychology, science education, and mathematics education is presented.<br>Based on the literature reviewed and the working definition, suggestions are made for<br>the types of tasks that can be used to study the nature and development of informal<br>inferential reasoning. Suggestions for future research are offered along with<br>implications for teaching.
  • Author(s):
    Bhanu, K. S. &amp; Deshpande, M. N.
    Editors:
    Goodall, G.
    Year:
    2004
    Abstract:
    In this note, a coin tossing experiment which leads to three discrete distributions is discussed.
  • Author(s):
    Hudson, M. H.
    Year:
    1992
    Abstract:
    Learning and applying the statistical thinking theories and techniques of the Deming management philosophy of Quality Improvement in introductory statistics courses can produce quality general education graduates for the 21st century. Advantages for the graduate who experiences a statistics course with emphasis using the Statistical Process Control (SPC) methodology include: a) replacing fear of mathematics with statistical critical thinking, team problem solving, and writing and communication skills that enable learning for a life time, b) statistical interpretations and analysis of data using reasoning skills that are imperative survival skills necessary for the competitive job market, c) statistical foundations with the Quality Improvement (QI) philosophy which can contribute to improving disciplines and attitudes. The implementation of this new paradigm for statistics courses will require new attitudes for both students and teachers, new methodology of management and teaching, and new context for the course.
  • Author(s):
    Moore, D. S.
    Year:
    1993
    Abstract:
    This interview was conducted for JSE at the Harvard Department of Statistics on December 18, 1992. The topics discussed include the history and future of statistics education, the use of video and computers in teaching statistics, the role of data analysis in statistics textbooks, innovation in the classroom, and graduate education.
  • Author(s):
    Cumming, G.
    Year:
    1977
    Abstract:
    The statistics course given as part of Psychology I in 1976 is described.
  • Author(s):
    Reid, J., &amp; Reading, C.
    Editors:
    Rossman, A., &amp; Chance, B.
    Year:
    2006
    Abstract:
    In this study a hierarchy of consideration of variation was developed from students' responses to a questionnaire given at the beginning of a tertiary introductory statistics course. The hierarchy was then used to code responses to the same questionnaire post-study. Comparison of student performances showed that the development of consideration of variation differs with the context of the question. The proposed hierarchy could provide a basis for a more general hierarchy of consideration of variation that is applicable across a variety of tasks. It also supports educators in identifying the level of a student's consideration of variation, providing direction for teaching and learning activities that will help that consideration develop.
  • Author(s):
    Hiebert, J., Gallimore, R., Stigler, J. W.
    Year:
    2002
    Abstract:
    To improve classroom teaching in a steady, lasting way, the teaching profession needs a knowledge base that grows and improves. In spite of the continuing efforts of researchers, archived research knowledge has had little effect on the improvement of practice in the average classroom. We explore the possibility of building a useful knowledge base for teaching by beginning with practitioners' knowledge. We outline key features of this knowledge and identify the requirements for this knowledge to be transformed into a professional knowledge base for teaching. By reviewing educational history, we offer an incomplete explanation for why the United States has no countrywide system that meets these requirements. We conclude by wondering if U.S. researchers and teachers can make different choices in the future to enable a system for building and sustaining a professional knowledge base for teaching.
  • Author(s):
    Keeler, C. M.
    Abstract:
    This report deals with the use of portfolios in assessing student performance in statistics. It gives a background on the use of portfolios, information on portfolio development, and issues surrounding portfolio assessment. It also provides a sketch of what a portfolio in statistics might look like.

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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