Literature Index

Displaying 61 - 70 of 3326
  • Author(s):
    Gelman, Andrew
    Year:
    2005
    Abstract:
    Teaching is an important part of the jobs of statistics professors and graduate students, but more of us receive little training for teaching in general or statistics teaching in particular. We have developed a course for statistics graduate teaching assistants that combines practice in statistics demonstrations and drills, discussion of teaching strategies, and feedback on classroom teaching. The goal is to get our graduate students to be more comfortable with engaging their students in active learning.
  • Author(s):
    Marcos Nascimento Magalhães and Maria Cecilia Camargo Magalhães
    Year:
    2014
    Abstract:
    In this paper, we report on the impact of four activities and two interviews on the organization of an introductory statistics course attended by future mathematics teachers at the University of Sao Paulo, Brazil. The activities were designed to enhance students’ learning and collaborative knowledge construction, based on Vygotsky’s Socio-Historical Theory. Data were collected in the course through the activities and the interviews. Analysis of the data suggests that the course improved students’ initiative, collaboration and intentional action, as well as their attitude as future mathematics teachers. Quantitative results comparing 2013 with earlier offerings of the course are also discussed. The transformation discussed here could be applied in other introductory statistics courses, and may lead to practical pedagogical improvements.
  • Author(s):
    Mvududu, N.
    Year:
    2003
    Abstract:
    This study investigated the relationship between a constructivist learning environment and students' attitudes toward statistics. The Constructivist Learning Environment Survey (CLES) and the Attitude Toward Statistics scale (ATS) were used to measure the environment and attitudes respectively. Participants were undergraduate students of an introductory college statistics course. They were drawn from Seattle Pacific University in the US and the University of Zimbabwe.<br>The study had two components. One component addressed hypotheses examining potential differences between groups and the other explored relationships between variables. The environment was not manipulated and the data was collected from courses that already existed in the form studied. For this reason, the overall design of the study had causal comparative and correlational elements. A constructivist learning environment was found to be significantly related to students' attitude toward statistics. Furthermore, there were significant differences between the groups based on location.<br>The study examined the similarities and differences in perceptions and attitudes of students from two very different learning milieus. Cross-cultural comparisons have the potential to generate new insights into statistical pedagogy and the role noncognitive socio cultural variables play in teaching statistics to college-age students.
  • Author(s):
    Burrill, G.
    Editors:
    Pereira-Mendoza, L.
    Year:
    1993
    Abstract:
    The need for mathematically literate students who can function on a technology driven society, together with the demonstrated lack of success of the current mathematics curriculum, has paved the way for major reform efforts in mathematics in the United States. One of the reform documents, Reshaping School Mathematics, a philosophy and framework for curricular change published by the National Research Council (1990), suggests, "Most obvious, perhaps is the need to understand data presented in a variety of different formats.... Citizens who cannot properly interpret quantitative data are, in this day and age, functionally illiterate" (p. 8). Leading proponents of change to school mathematics, including the National Council of Teachers of Mathematics (NCTM) and the Mathematics Science Education Board, emphasize that data analysis must be a key component of a revitalized curriculum if mathematics is to relate to the practical world of the student and if it is to provide the necessary skills for living in an information age. This paper describes the NSF funded project: " A Data Driven Curriculum," for students in grades 9 - 12. The project addresses two needs: how to use data analysis to motivate some of the essential topics of a restructured mathematics curriculum, and how to identify and teach those data analysis skills that are required for effective participation in society.
  • Author(s):
    Franklin, C., Kader, G., Mewborn, D., Moreno, J., Peck, R., Perry, M., &amp; Schaeffer, R.
    Year:
    2005
    Abstract:
    Statistical literacy is essential in our personal lives as consumers, citizens and professionals. Statistics plays a role in our health and happiness. Sound statistical reasoning skills take a long time to develop. They cannot be honed to the level needed in the modern world through one high school course. The surest way to reach the necessary skill level is to begin the educational process in the elementary grades and keep strengthening and expanding these skills throughout the middle and high school years. A statistically literate high school graduate will know how to interpret the data in the morning newspaper and will ask the right questions about statistical claims. He or she will be comfortable handling quantitative decisions that come up on the job, and will be able to make informed decision about quality of life issues.<br><br>The remainder of this document lays out a framework for educational programs designed to help students achieve this noble end.
  • Author(s):
    D'Argenzio, P., &amp; Pesarin, F.
    Editors:
    Davidson, R., &amp; Swift, J.
    Year:
    1986
    Abstract:
    No real introduction of statistics and probability into the classroom was really ever put into effect. The reasons for this are manifold. Teachers to whom the task of teaching statistics and probability is assigned, are in effect these who also have to teach mathematics, the natural sciences, physics and chemistry. In Italy there are no degree courses of a widely-varying subject matter ..., for which reason teachers come from degree courses of a much more specific nature such as mathematics, physics or chemistry. Thus we have tried to present the problem and bring the solution into prospect which, if clear and correct at the level of subject matter and didactics, would also in addition possess the characteristics for concrete realisation and hence generalisation for the greatest possible number of situations and teachers. Experimentation has also been carried out on the proposed curriculum in order to test not just certain aspects of content but also methodology and those aspects related to "time-linked resources".
  • Author(s):
    Beyth-Marom, R., &amp; Dekel, S.
    Year:
    1983
    Abstract:
    Recent evidence indicates that people's intuitive judgments are sometimes affected by systematic biases that can lead to bad decisions. Much of the value of this research depends on its applicability, i.e., showing people when and how their judgments are wrong and how they can be improved. This article describes one step toward that goal, i.e., the development of a curriculum for junior high school students aimed at improving thought processes, specifically, those necessary in uncertain situations (probabilistic thinking). The relevant psychological literature is summarized and the main guidelines in the curriculum development are specified: (a) encouraging students to introspect and examine their own (and other's) thought processes consciously, (b) indicating the circumstances in which common modes of thinking may cause fallacies, and (c) providing better tools for coping with the problems that emerge. Two detailed examples are given. In addition, the problem of training teachers is briefly discussed and a small-scale evaluation effort is described.
  • Author(s):
    Carr, R.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    XLStatistics is a set of Excel workbooks for analysis of data that has the various analysis tools and methods organized according to the number and type of variables involved. Most introductory courses in statistics start out with a discussion of the different types of variables, but very few data analysis packages are organized along these lines. This can make it difficult for students, and may be a contributing reason for the common "What test do I use?" question. We describe the XLStatistics package and show how it may help to overcome some of the common problems encountered by students.
  • Author(s):
    Rossman, A. J. &amp; Chance, B. L.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    We describe our project to develop curricular materials for a course that introduces students at the post-calculus level to statistical concepts, methods, and theory. This course provides a more balanced introduction to the discipline of statistics than the standard sequence in probability and mathematical statistics. The materials incorporate many features of successful statistics education projects that target less mathematically prepared students. The student audiences targeted by this project are particularly important because they have been overlooked by previous curricular reform projects. Most importantly, the proposed audience includes prospective teachers of statistics, introducing them to content and pedagogy that prepare them for implementing NCTM Standards with regard to statistics and probability and for teaching the Advanced Placement course in Statistics.
  • Author(s):
    Rossman, A., Chance, B., Ballman, K.
    Year:
    2000
    Abstract:
    We describe this NSF-funded project to develop a two-course sequence that introduces post-calculus students to statistcal concepts, methods, and theory. These courses provide a more balanced introduction to the discipline of statistics than the standard sequence in probability and mathematical statistics. The materials incorporate many features of successful statistics education projects that target less mathematically prepared students. Such features include developing students' conceptual understanding of fundamental ideas, promoting student explorations through hands-on activities, analyzing genuine data drawn from a variety of fields of application, and integrating computer tools both to enhance students' learning and to analyze data efficiently. Our proposed introductory course differes by utilizing students' calculus knowledge and mathematical abilities to explore some of the mathematical framework underlying statistical concepts and methods. Distinguishing the second course is the use of simulation, computer graphics, and genuine problems and data to motivate and illustrate statistical theory. In this presentation, we outline the goals, content, and pedagogy of this sequence. We also present examples of student activities from both 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