Literature Index

Displaying 1531 - 1540 of 3326

  • Meta-analysis: Pictures that explain how experimental findings can be integrated.

    Author(s):
    Cumming, G.
    Editors:
    Rossman, A., & Chance, B.
    Year:
    2006
    Abstract:
    Meta-analysis (MA) is the quantitative integration of empirical studies that address the same or similar issues. It provides overall estimates of effect size, and can thus guide practical application of research findings. It can also identify moderating variables, and thus contribute to theory-building and research planning. It overcomes many of the disadvantages of null hypothesis significance testing. MA is a highly valuable way to review and summarise a research literature, and is now widely used in medicine and the social sciences. It is scarcely mentioned, however, in introductory statistics textbooks. I argue that MA should appear in the introductory statistics course, and I explain how software that provides diagrams based on confidence intervals can make many of the key concepts of MA readily accessible to beginning students.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/17/C105.pdf

  • Metaphors for instruction: Why we talk about learning environments

    Author(s):
    Wilson, B. G.
    Year:
    1995
    Abstract:
    Defines constructivist learning environments and explains why the idea is worthy of study. Discussion includes the different assumptions underlying common metaphors for instruction, the idea of learning environments, the outcomes of learning environments, and the components or functions that make up learning environments.

  • Method

    Author(s):
    Schoenfeld, A. H.
    Editors:
    Lester, F.
    Year:
    2005
    Abstract:
    A comprehensive review of research methods in mathematics education.

  • Methods for studying coincidences

    Author(s):
    Diaconis, P., & Mosteller, F.
    Year:
    1989
    Abstract:
    This article illustrates basic statistical techniques for studying coincidences.
    Location:
    RISE

  • Methods of learning in statistical education: A randomized trail of public health graduate students.

    Author(s):
    Enders, F. B., & Diener-West, M.
    Editors:
    Gal, I., & Short, T.
    Year:
    2006
    Abstract:
    A randomized trial of 265 consenting students was conducted within an introductory biostatistics course: 69 received eight small group cooperative learning sessions; 97 accessed internet learning sessions; 96 received no intervention. Effect on examination score (95% CI) was assessed by intent-to-treat analysis and by incorporating reported participation. No difference was found by intent-to-treat analysis. After incorporating reported participation, adjusted average improvement was 1.7 points (-1.8, 5.2) per cooperative session and 2.1 points (-1.4, 5.5) per internet session after one examination. After four examinations, adjusted average improvement for four study sessions was 5.3 points (0.4, 10.3) per examination for cooperative learning and 8.1 points (3.0, 13.2) for internet learning. Consistent participation in active learning may improve understanding beyond the traditional classroom.
    Location:
    http://www.stat.auckland.ac.nz/~iase/serj/SERJ_5(1)_Enders_West.pdf

  • Methods of learning in statistical education: Design and analysis of a randomized trial.

    Author(s):
    Boyd, F.
    Editors:
    Diener-West, M.
    Year:
    2002
    Abstract:
    The primary objectives were to evaluate and compare the addition of two active learning methods (cooperative and internet) on students' performance: assess their impact on performance after adjusting for differences in students' learning style; and examine the influence of learning style on trial participation. No performance differences by group were observed by intent-to-treat analysis. Participation in active learning appears to improve students performance in an introductory biostatistics course and provides opportunities for enhancing understanding beyond that attained in traditional didactic classrooms.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/dissertations/02.Boyd.Dissertation.doc

  • Microcomputer and teaching statistics

    Author(s):
    Wasik, J. L.
    Year:
    1985
    Abstract:
    This paper presents a three level scheme for categorizing the use of computers/microcomputers in the teaching of statistics.

  • Microdot: The Microcomputer as a Learning Aid in Sixth-Form Mathematics

    Author(s):
    Higgo, J. R.
    Year:
    1984
    Abstract:
    Demonstrates how microcomputers can be used in teaching differential calculus, iteration, integral calculus, graphs, and statistics. Several ideas for putting this information into practice are outlined. Sample computer programs are included for the discussions on differential calculus, integral calculus, and iteration. (JN)

  • Middle grades: misconceptions in statistical thinking

    Author(s):
    Capraro, M. M., Kulm, G., and Capraro, R. M.
    Year:
    2005
    Abstract:
    A sample of 134 sixth-grade students who were using the Connected Mathematics curriculum were administered an open-ended item entitled, Vet Club (Balanced Assessment, 2000). This paper explores the role of misconceptions and naive conceptions in the acquisition of statistical thinking for middle grades students. Students exhibited misconceptions and naive conceptions regarding representing data graphically, interpreting the meaning of typicality, and plotting 0 above the x-axis.

  • Middle School and High School Students' Probabilistic Reasoning on Coin Tasks

    Author(s):
    Laurie H. Rubel
    Year:
    2007
    Abstract:
    This article describes a subset of results from a larger study (Rubel, 2002) that explored middle school and high school students' probabilistic reasoning abilities across a variety of probabilistic contexts and constructs. Students in grades 5, 7, 9, and 11 at an urban, private school for boys (n = 173) completed a Probability Inventory, comprising adapted tasks from the research literature, which required students to provide answers as well as justifications of their responses. Supplemental clinical interviews were conducted with 33 students to provide further detail about their reasoning. This article focuses specifically on the probabilistic constructs of compound events and independence in the context of coin tossing.
    Location:
    http://my.nctm.org/eresources/article_summary.asp?URI=JRME2007-11-531a&from=B

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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