Literature Index

The community of statisticians and statistics educators should take responsibility for the evaluation and improvement of software quality from the perspective of education. The paper will develop a perspective, an ideal system of requirements to critically evaluate existing software and to prodcue future software more adequate both for learning and doing statistics in introductory courses. Different kinds of tools and microworlds are needed. After discussion general requirements for such programs, a prototypical ideal software system will be presented in detail. It will be illustrated how such a system could be used to construct learning environments and to support elementary data analysis with exploratory working style.

The overall goal of this chapter is to discuss perspectives for using technology in statistics education. For this purpose, we will analyse and illustrate new revolutionary developments in statistics itself. We intend to make sense of statistical software tools by relating them to subject matter developments and to analytical perspectives generated by the requirements of software from a didactical point of view. New developments in statistics education and curriculum dependent educational software tools will be critically related to the technological and subject matter changes outside school.

Described is a strategy that allows students to experiment with probability without applying formulas to solve problems. Students are able to intuitively develop concepts of probability before formal definitions and properties. Sample problems are included along with BASIC programs for some of the problems. (KR)

In many statistics courses homework exercises and examinations focus primarily on solving problems. Marks are assigned to students' responses according to the degree to which a problem solution is correct and/or to which a student's procedure employed in the solution is correct. When a statistics course has an applications or data analysis orientation, instructors often find that even though students can solve textbook and examination problems, they are frequently unable to apply probability and statistics to solve "real world" research problems in which judgments have to be made about the technique(s) to be used and in which substantive interpretations of the results of statistical analyses need to be made. The paper reviews several formats of examination questions and assessment procedures which have been used over the years in noncalculus courses in applied statistical methods which focus on data analyses, parameter estimation, and hypothesis testing. Among the types of assessment techniques reviewed are short-answer questions, essay questions, yes-no questions with student-provided justifications, concept-oriented multiple-choice items, masterlist items, analogical reasoning items, graphic inference items, free association tasks, and concept mapping tasks. The paper also reports on a computer-assisted test of knowledge structure called MicroCAM. This test allows students to create on a computer screen a spatial representation of the way in which they perceive key statistical concepts to be linked one to another. The test also permits students to specify the type of relationship which links two or more concepts together. In this way a student's unique knowledge structure is revealed. Implications of these different assessment methods for diagnosing students' learning difficulties and for teaching statistics to mathematically naive students are discussed.