Literature Index

Displaying 2621 - 2630 of 3326
  • Author(s):
    Erickson, T.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    In an ideal world, science students would act as scientists do: investigating their own questions, designing experiments, and so forth. This paper reports on curriculum development and field testing that takes a step in this open-ended direction. To do this, we have focused on integrating more data analysis into science activities; this also gives students a chance to use more mathematics, in an understandable context. This mathematics includes work with functions and variation. A closer look at plausible activities shows us that principles of measurement connect these elements; furthermore, a broad view of measurement reconnects us to our original goal: to expose students more directly to the nature of science.
  • Author(s):
    Meletiou-Mavrotheris, M., Papristodemou, E., & Stylianou, D.
    Editors:
    Rossman, A., & Chance, B.
    Year:
    2006
    Abstract:
    The research discussed in the paper comes from a multifaceted program for the teaching and learning of early statistical reasoning in Cyprus. The overall aim of the program is to enhance the quality of statistics education offered in Cypriot elementary schools by facilitating professional development of teachers using exemplary technological and educational tools and resources. As part of the program, professional development seminars for the teaching of statistics with the use of Tinkerplots@ - a dynamic data-visualization package designed specifically for young learners - were designed and offered to elementary school teachers. The article discusses insights gained from the seminars regarding the ways in which computer visualization tools can enhance teachers' content and pedagogical knowledge of statistics.
  • Author(s):
    Lesser, L. M.
    Year:
    1998
    Abstract:
    A university's introductory statistics course was redesigned to incorporate technology (including a website) and to implement a standards-based approach that would parallel the recent standards-based education mandate for the state's K-12 schools. The author collected some attitude (pre and post) and performance (post only) data from the "treatment" section and two "comparison (i.e., more traditional)" sections. There was a pattern of positive attitude towards the redesigned aspects of the course, including group work, lab and project emphasis, criterion-referenced assessment and examples from real-life. On the three problems given to the three sections at the end of the course, the only significant ANOVA (F(2,101) = 4.2, p = .0168) involved the treatment section scoring higher than the other sections. This occurred on a problem involving critical thinking (with a graphic from USA Today), an emphasis supported by the particular standards of the redesigned course.
  • Author(s):
    Rossman, A. J.
    Year:
    1994
    Abstract:
    This dataset contains information on life expectancies in various countries of the world and the densities of people per television set and of people per physician in those countries. The example has proven very useful for helping students to discover the fundamental principle that correlation does not imply causation. The data also give students an opportunity to explore data transformations and to consider whether a causal connection is necessary for one variable to be a useful predictor of another.
  • Author(s):
    Maxine Pfannkuch, Matt Regan, Chris Wild, and Nicholas J. Horton
    Year:
    2010
    Abstract:
    Language and the telling of data stories have fundamental roles in advancing the GAISE <br><br>agenda of shifting the emphasis in statistics education from the operation of sets of <br><br>procedures towards conceptual understanding and communication. In this paper we discuss <br><br>some of the major issues surrounding story telling in statistics, challenge current practices, <br><br>open debates about what constitutes good verbalization of structure in graphical and<br><br>numerical summaries, and attempt to clarify what underlying concepts should be brought to <br><br>students  attention, and how. Narrowing in on the particular problem of comparing groups, <br><br>we propose that instead of simply reading and interpreting coded information from graphs, <br><br>students should engage in understanding and verbalizing the rich conceptual repertoire <br><br>underpinning comparisons using plots. These essential data-dialogues include paying <br><br>attention to language, invoking descriptive and inferential thoughts, and determining <br><br>informally whether claims can be made about the underlying populations from the sample <br><br>data. A detailed teacher guide on comparative reasoning is presented and discussed.
  • Author(s):
    Stefano Barone and Eva Lo Franco
    Year:
    2010
    Abstract:
    The need for universities to achieve excellence in the services they provide has been the subject of research for several decades. The idea of involving students and recognizing the importance of their opinions has led to the creation of various models and tools. This paper focuses on teaching, a central service from which improvement actions of an academic institution should always begin. The article reviews and updates the previously developed Teaching Experiments and Student Feedback methodology. The methodology, which is primarily addressed to statistics teachers, allows practical aspects to be organized and decisions to be made based on data that has been collected from students and scientifically analyzed.<br><br>The steps for building a student satisfaction index are also described. This index, in its most complete version, takes into account possible correlations between importance of the evaluated aspect and scores, both of which are provided by the students. The paper presents an application of the methodology to a statistics course taught by one of the authors.
  • Author(s):
    Hettmansperger, T. P. &amp; Elmore, R.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    We first note that tests for interaction are missing in virtually all textbooks on nonparametric statistics. We will discuss some reasons why this is so. We then make a case for featuring tests for interaction in the course. By learning how to use median polish and graphical displays students can begin to conceptualize what an interaction means. This will strengthen their understanding of additive models as well. After a conceptual basis for understanding interaction is in place, we can then proceed to design tests for interaction. They will not be strictly nonparametric. This provides a good opportunity for discussion of what it means to have a nonparametric test and why it is impossible to construct an ordinary permutation test for interaction.
  • Author(s):
    West, Webster
    Year:
    2013
    Abstract:
    Technology allows us to offer great improvements on the traditional paper-bound textbook. I describe reasons for why electronic textbooks will become the norm in the near future.
  • Author(s):
    Warner, B. A., Pendergraft, D., &amp; Webb, T.
    Year:
    1998
    Abstract:
    Basic probability concepts are difficult for some students to understand initially. Through the use of a Venn diagram disguised as a pizza, we will discuss how to explain introductory probability concepts. Students are able to answer probability questions, including conditional probability, by simply looking at a picture. This tool not only enhances learning but retention as well.
  • Author(s):
    Clark, J. M., Kraut, G., Mathews, D., &amp; Wimbish, J.
    Year:
    2003
    Abstract:
    A goal of this study is to verify, or modify, the genetic decomposition of the Central Limit Theorem through the identification of students who had developed a viable understanding of this theorem. Another goal of the present paper is to add to the body of knowledge concerning the development of statistical knowledge in college students by building on the work done by Mathews and Clark.

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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