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asa.stat.educ.02


ASA Statistical Education Section

Session Slot: 8:30-10:20 Wednesday

Estimated Audience Size: 125-175

AudioVisual Request: Two Overheads


Session Title: Plugging In - Connecting Technology to the Classroom

Theme Session: No

Applied Session: Yes


Session Organizer: Short, Thomas H. Villanova University


Address: Dept. of Mathematical Sciences, Villanova University, Villanova PA 19085-1699

Phone: 610-519-6961

Fax: 610-519-6928

Email: short@monet.vill.edu


Session Timing: 110 minutes total (Sorry about format):

Opening Remarks by Chair - 0 minutes First Speaker - 30 minutes Second Speaker - 30 minutes Third Speaker - 30 minutes Discussant - 15 minutes Floor Discusion - 5 minutes


Session Chair: Short, Thomas H. Villanova University


Address: Dept. of Mathematical Sciences, Villanova University, Villanova PA 19085-1699

Phone: 610-519-6961

Fax: 610-519-6928

Email: short@monet.vill.edu


1. Dynamic Statistics(TM) - Learner Centered Visualization and Construction of Statistical Concepts

Finzer, William,   Key Curriculum Press


Address: Key Curriculum Press, P. O. Box 2304, Berkeley, CA 92702

Phone: 510-548-2304

Fax: 510-548-0755

Email: bfinzer@mail.keypress.com

Abstract: A constructivist outlook on the teaching and learning of statistics suggests that learners should be in charge of devising statistical measures and controlling visualizations of statistical ideas. When students construct their own statistical measures and graphs, they can appreciate the origins of the traditional measures and graphs. Dynamic dragging allows students to change data and observe the effect of the change during the drag. This paper focuses on visualization techniques, the importance of dragging in Dynamic Statistics(TM) software, and on the role of user-constructed measures in the learning of statistics. It includes results of research from the DataSpace project at Key Curriculum Press, an NSF-funded project to develop a computer learning environment and curriculum materials for use in teaching introductory statistics. Examples from classroom field testing are included.


2. Virtual Laboratories in Probability and Statistics

Siegrist, Kyle,   University of Alabama in Huntsville


Address: Dept. of Mathematical Sciences, University of Alabama in Huntsville, Huntsville AL 35899

Phone: 205-890-6470

Fax: 205-890-6173

Email: siegrist@math.uah.edu

Abstract: A widely accepted principle of the reform movement in mathematics education is that subjects be taught from multiple points of view with appropriate use of technology. This principle is particularly important in probability and statistics. For these subjects, the points of view should include mathematical analysis (the usual derivation of the theory and methods), data analysis (both graphical and numerical, and preferably with real data sets), and simulation analysis. It is unfortunate that the last component is often neglected in standard courses, because carefully designed computer "applets" can be of great value, illustrating the theory and techniques in an interactive and dynamic way that is impossible to achieve by other methods.

The "Virtual Laboratories" project (http://www.math.uah.edu/ stat/) consists of web-based modules that combine hypertext, graphics, interactive Java applets, and data sets. The web is an ideal medium for a project of this type, because the elements can be combined in a carefully designed way, and because the project is available to any student with web access, on any of the standard platforms. Moreover, the project can be linked to a vast array of related sites and can be continually improved and augmented. The ultimate goal of the project is to have modules that cover the core topics at the undergraduate level, as well as a continually expanding "virtual library" of special random processes.

In this presentation, we will discuss the overall structure of the project, see some examples, and discuss some of the finer design principles, including the special challenges involved in writing hypertext and Java applets.


3. Simulation and Bootstrapping for Teaching Statistics

Hesterberg, Tim,   MathSoft/Statistical Sciences


Address: MathSoft/Statistical Sciences, 1700 Westlake Ave. N, Suite 500, Seattle QA 98109-3044

Phone: 206-283-8802 x319

Fax: 206-283-0347

Email: timh@statsci.com

Abstract: Some key ideas in statistics and probability are hard for students, including sampling distributions. Computer simulation lets students gain experience with and intuition for these concepts. Bootstrapping can reinforce that learning, and provide a way for students (and future practitioners!) to estimate sampling distributions when they have data but do not know the underlying distribution. Bootstrapping also frees us from the requirement to teach inference only for statistics for which simple formulas are available--we can bootstrap robust statistics like the median as easily as the mean.

For the promise of simulation and bootstrapping to be realized, they must be available and easy to use in general-purpose statistical software, complete with the exploratory data analysis and inferential capabilities required in the course and practice. We discuss some of the available software.


Discussant: Lock, Robin   St. Lawrence University


Address: Mathematics Department, St. Lawrence University, Canton NY 13617

Phone: 315-229-5960

Fax: 315-229-5804

Email: rlock@vm.stlawu.edu


next up previous index
Next: asa.stat.educ.03 Up: ASA Statistical Education (3) Previous: asa.stat.educ.01
David Scott
6/1/1998