Literature Index

The current assessment reform movement in statistics encourages instructors to think more broadly about cognitive measures which assess student learning. In response, statistics instructors have begun incorporating innovative methods of assessment into their courses, the most common of these procedures being athentic assessment, performance assessment, and portfolio assessment. Thus, this paper will provide a typology of different effective ways of assessing performance in statistics classess for the various contexts (e.g., undergraduate vs. master's vs. doctoral), content (e.g., measurement vs. evaluation vs. research design), and pedagogical styles (e.g., web-based vs. traditional; theory vs. concepts vs. application).

This paper discusses the properties and characteristics that software should have (i.e., software that will support learning in statistics) and the features of software that aid teaching and learning.

In New Zealand, end-of-course examination based assessment is rooted in our past and while it may have served the past well, it is clear that it does not adequately serve our present needs. In 1991 the Education Subcommittee of the New Zealand Statistical Association suggested that these examinations may not be valid (unbiased) or reliable (have low variability) measures of ability. Further there is a growing concern that our examinations do not function equitably across all groups of students, and that they do not adequately measure either those skills needed by the general population for their everyday needs, or the skills needed to contribute to the country's economic growth. The debate on assessment procedures has, in part, arisen because of the differential performance of girls and boys in traditional mathematics examinations. In New Zealand a number of analyses of secondary school mathematics examination performance have been done (Stewart, 1987; Reilly et al, 1987; Forbes, 1988; Morton et al, 1988 and 1989; Forbes et al, 1990). These results all show a greater range of achievement within each gender than between the genders but typically the top grades are dominated my males. There are a number of forms of assessment in current use in statistics. Some types of assessment may unfairly advantage one group of students over another. A limited amount of research has been done comparing assessment methods to determine those which may best suit women, Maori (indigenous New Zealanders), or ethnic minorities. Women themselves cannot be classified as just one group. Forbes (1992) showed that a reduction in gender differences in performance in mathematics of one group of the New Zealand population (European) does not necessarily lead to a similar reduction in another group (Maori).

As part of an NSF funded project we developed new course materials for a general introductory statistics course designed to engage students in statistical discovery. The materials were designed to actively involve students in the design and implementation of data collection and the analysis and interpretation of the resulting data. Our overall goal was to have students begin to think like statisticians, to construct ways of thinking about data collection and analysis, to solve problems using data in context. During their development, the materials and related activities were field tested in a small special section of an introductory statistics course for two semesters. This field testing was a ``proof of concept,'' that is that the materials could work in the laboratory setting and that the materials showed promise for improving students' learning. As a first step in evaluating these materials, students who enrolled in regular sections of the introductory course were used as a comparison group. In this paper, the development and use of the course materials will be discussed briefly. The strategy for evaluating the materials while they were being developed and analysis of students' performance on common assessment questions and the course project will be presented. In addition, the relationship between student attitudes toward statistics and students' performance will be examined.<br><br>``Declare the past, diagnose the present, foretell the future; practice these acts