Newsletter for the Section on Statistical Education
Volume 2, Number 2 (Summer 1996)
As the editor of the special issue, I invited authors to submit papers on teaching or learning, with the one restriction that each manuscript describe empirical research on this issue. The papers were submitted for peer review and revision, and those that were eventually accepted cover a broad range of topics. All of the authors and I hope that many readers will find the contents of this special issue to be both thought-provoking and useful for those involved in (or simply interested in) the teaching and learning of statistics.
The issue begins with a paper on the evaluation of textbooks for statistics by Harwell, Herrick, Curtis, Mundfrom and Gold. The authors outline a scheme for rating statistics texts, based on the broader literature on text evaluation. They provide several instruments (printed in the issue) suitable for use by teachers, students, or independent "experts." The authors hope that readers will use these instruments with their own texts and classes, and communicate their results and suggestions for refinement of the evaluation scheme to the authors.
The next paper deals with instruction and learning. Cohen, Smith, Chechile, Burns and Tsai describe findings from an effort to teach and assess statistics learning with interactive computer software (ConStatS). They describe misconceptions held by students, based on an analysis of errors made by students using ConStatS. Their provocative claims should provide food for thought for all who teach statistics, whether using software or more traditional instructional methods.
In the third paper, Schram describes a meta-analysis of studies of gender differences in post-secondary statistics achievement. Many have wondered whether the male advantages observed in mathematics at lower grade levels persist in statistics classes in college or beyond. Schram finds small overall gender differences, but discovers that on average, females outperform males. However, the study results are not all consistent with a common gender effect, thus Schram explores several factors (including type of achievement outcome, department offering the course, and sex of the researcher) that explain variation in the sizes of gender differences.
The issue closes with an updated analysis of the literature on teaching statistics in education, with a focus on the literature as a resource for statistics instructors (Becker, 1996). Also I describe some of the electronic resources for teaching (as well as research on statistics instruction) now available on the Internet.
General information about the Journal of Educational and Behavioral Statistics can be found on the Internet at http://www.stat.ucla.edu/journals/jebs, and most editorial correspondence should be addressed to:
Jan de Leeuw, Editor
Journal of Educational and Behavioral Statistics
Department of Mathematics
Math Sciences Building, Room 8118
Los Angeles, CA 90024-1554