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This study examined students' development of reasoning about quantitative bivariate data during a one-semester university-level introductory statistics course. There were three research questions of interest: (1) What is the nature, or pattern of change in students' development in reasoning throughout the course?; (2) Is the sequencing of quantitative bivariate data within the course associated with differences in the pattern of change in reasoning?; and (3) Are changes in reasoning about foundational concepts of distribution associated with differences in the pattern of change? Covariational and distributional reasoning were measured four times during the course, across four cohorts of students. A linear mixed-effects model was used to analyze the data, revealing some interesting trends and relationships regarding the development of covariational reasoning. (Contains 4 tables and 3 figures.)

This paper provides practical examples of how statistics educators may apply a cooperative framework to classroom teaching and teacher collaboration. Building on the premise that statistics instruction ought to resemble statistical practice, an inherently cooperative enterprise, our purpose is to highlight specific ways in which cooperative methods may translate to statistics education. So doing, we hope to address the concerns of those statistics educators who are reluctant to adopt more student-centered teaching strategies, as well as those educators who have tried these methods but ultimately returned to more traditional, teacher-centered instruction.

A number of examples illustrate that large institutions, often criticized for not delivering high-quality undergraduate education, can use the faculty's applied research activities to improve the student experience. (Author/MSE)

This study examined students' development of reasoning about quantitative bivariate data during a one-semester university-level introductory statistics course. There were three research questions of interest: (1) What is the nature, or pattern of change in students' development in reasoning throughout the course?; (2) Is the sequencing of quantitative bivariate data within the course associated with differences in the pattern of change in reasoning?; and (3) Are changes in reasoning about foundational concepts of distribution associated with differences in the pattern of change? Covariational and distributional reasoning were measured four times during he course, across four cohorts of students. A linear mixed-effects model was used to analyze the data, revealing some interesting trends and relationships regarding the development of covariational reasoning. [ABSTRACT FROM AUTHOR]

The article presents a study on the effectiveness of teaching and learning statistics in mathematics classroom. Research suggests that statistical ideas need to be developed slowly and systematically through a designed sequence of activities in appropriate learning environment. The researchers found that the activities were effective in helping students develop an understanding of important statistical concepts. Thus, the author concluded that statistical concepts should not be introduced and defined before the students have an intuitive idea of what the concepts mean and represents.

The article highlights the essential concepts of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) project. The GAISE lays out a broad vision of statistics. It is an American Statistical Association (ASA)-endorsed guidelines for assessment and instruction in statistics in the grades pre-K-12 curriculum and for the introductory college statistics course. The six recommendations for the teaching of introductory statistics developed by the college group of the GAISE Project are also presented.

Comments on the efforts of academicians to change the statistics curricula in graduate programs from the point of view of an educational psychologist. Need for the faculty to be aware of teaching and learning techniques; Course work and experience on teaching as requisites for graduate students in statistics.